Droplet microfluidics for energy and bioelectrochemical applications

1 Introduction

The development of miniaturised analytical systems has revolutionised many scientific fields, including biotechnology, electrochemistry, energy conversion, environmental monitoring, and biomedical engineering. Of these technologies, droplet microfluidics has proven to be an attractive tool for the control and analysis of individual droplets of fluid with unprecedented precision and efficiency (Shang et al., 2017). Droplet microfluidic systems create highly controlled microdroplets as independent microreactors to allow for fast reaction rates, better mass transfer, decreased reagent consumption, and parallelised experiments (Shang et al., 2017; Modestino et al., 2016). These unique properties have generated a lot of interest for single cell analysis, biosensing, materials synthesis and energy-related applications (Wu S. et al., 2014). The coupling of droplet microfluidics with electrochemical and bioelectrochemical systems has enabled enhancements in analytical performance, reaction efficiency, and device miniaturisation in recent years, creating new opportunities. In such developments, novel platforms that can solve important problems in sustainable energy production, environmental clean-up and next-generation biosensing technologies have emerged (Hou et al., 2011; Chen et al., 2012). The review covers the basics of droplet microfluidics, its technological advancements and potential applications in energy and bioelectrochemical systems, as well as recent developments, challenges and future prospects.

Droplet microfluidics is a special use of microfluidics technology that is used to generate, control and study discrete droplets in immiscible carrier fluids. (Seemann et al., 2012). Normally, the droplets are aqueous ones that are dispersed in continuous oil phases but sometimes other fluid systems can be used for specific applications (Zhu and Wang, 2016). In the microscale channels, droplet formation is controlled by the balance of interfacial tension, viscous forces, inertial effects and flow dynamics (Baroud et al., 2010). There are several common droplet generation geometries, such as T-junction, flow-focusing devices, co-flow and step emulsification systems, which all have unique features in droplet size control, production rate and stability of operation (Baroud et al., 2010; Li et al., 2018). The resulting droplets are isolated reaction chambers that can be used to contain cells, biomolecules, nanoparticles, catalysts or reagents, which allows for highly controlled chemical and biological processes (Li et al., 2018; Amirifar et al., 2021). The ability to precisely manipulate droplet generation, merging, splitting, sorting and incubation has made droplet microfluidics a versatile platform for conducting complex experiments with exceptional reproducibility and efficiency (Zhu and Wang, 2016; Baroud et al., 2010; Pit et al., 2015).

In recent decades, the evolution of microfluidic technologies has come a long way from merely moving fluids around at the microscale to complex integrated platforms that can undertake complex analytical and synthetic operations (Pecar et al., 2021). The first generation of microfluidic devices was mainly used for chemical analysis and miniaturized laboratory processes, primarily as a result of the technology used in the semiconductor industry for the fabrication of micro devices (Pecar et al., 2021; Convery and Gadegaard, 2019). Further advancements resulted in the development of lab-on-a-chip systems that combined several laboratory processes to a compact chip-based platform. As the field evolved, the need for continuous-flow microfluidics was identified as having drawbacks when working with applications that required compartmentalization, efficient screening and single particle analysis (Convery and Gadegaard, 2019; Queijo et al., 2026). These difficulties led to the development of droplet-based microfluidics where fluid is handled in a discrete manner, greatly enhancing the functionality of microfluidic systems. The development of microfluidic technologies has been further advanced with recent developments in materials science, microfabrication and automation, and computational modelling that has allowed the combination of microfluidics with electrochemical sensors, energy devices, artificial intelligence, and advanced manufacturing methods (Li et al., 2018; Convery and Gadegaard, 2019).

Droplet microfluidics has been recently used in energy and bioelectrochemical systems to control reactions, to improve mass transport, and to enable large-scale experiments (Modestino et al., 2016). For energy-related applications, droplet microfluidic platforms can be used to precisely control the reaction conditions, which helps for efficient production of functional nanomaterials, catalysts, electrode materials, and components for energy storage systems (Song et al., 2019; Ly et al., 2025). Droplet reactors are extremely small (microscale) and have a very large surface to volume ratio, which results in greater heat and mass transfer rates, and consequently better reaction rate and product uniformity (Schütt et al., 2016). Droplet microfluidics provides special opportunities for studying the behaviours of microbes, electron transfer mechanisms, enzymatic reactions, and cell-cell interactions in bioelectrochemical systems at the single-cell level (Song et al., 2019). Droplet manipulation combined with electrochemical detection can be used to achieve high sensitivity and temporal resolution of biological and electrochemical processes in real time (Ly et al., 2025; Shang et al., 2017). Moreover, the droplet-based method allows the fabrication of an environment monitoring system, a bio-electrosynthesis platform, biosensors, and miniaturised microbial fuel cells. This has made droplet microfluidics an important enabling technology for sustainable energy technologies and next-generation bioelectrochemical applications (Hou et al., 2011; Chen et al., 2012; Queijo et al., 2026).

With the growing number of research efforts at the droplet microfluidics-electrochemistry-energy science interface, it is important and timely to review recent advances in this area (Ly et al., 2025). The purpose of this review is to give a detailed overview of the basics of droplet microfluidics and the coupling with electrochemical/bioelectrochemical systems. Special attention is given to droplet generation methods, device design, electrochemical detection techniques and novel applications of the devices in energy conversion, energy storage, electrocatalysis, biosensing, microbial electrochemical technology and environmental monitoring (Ly et al., 2025). The review also explores the pros and cons of existing droplet-based platforms, reviews some new technologies, and proposes future research directions to enhance the scalability, automation, analytical capabilities, and practical application of the platforms. This review aims to highlight recent advances and also to pinpoint the challenges to be resolved by researchers in the area of microfluidics, electrochemistry, bioengineering and sustainable energy technologies (Lee et al., 2022; Thakur et al., 2021; Ibrahim et al., 2022).

Despite the rapid development of droplet-based microfluidics, existing reviews have largely examined the field from either a fundamental microfluidic perspective or from a specific application domain. Recent reviews have comprehensively discussed droplet generation, manipulation, trapping, sorting and biomedical applications, including microbial analysis and cell-based assays, but have not systematically addressed the role of droplets in electrochemical energy and bioelectrochemical systems. More recently, Ly et al. (2025) provided a focused review of electrochemical sensing integrated with droplet and digital microfluidics, establishing an important connection between droplet manipulation and electrochemical detection. However, this work is primarily centred on analytical electrochemical sensing and does not comprehensively examine droplet-enabled energy generation, energy conversion, microbial electrochemical processes, or the broader coupling of biological reactions with electrochemical energy systems (Ly et al., 2025). In parallel, recent reviews of microbial fuel cells and bioelectrochemical energy systems have concentrated on electrode and membrane materials, microbial metabolism, substrates, reactor configuration, wastewater treatment and power generation, while the specific contribution of droplet microfluidics remains largely outside their scope. Therefore, a focused assessment of the intersection between droplet microfluidics, electrochemistry, bioelectrochemistry, and energy applications is still lacking. The present review addresses this gap by examining droplet-based microfluidic systems specifically where droplet formation, confinement, compartmentalization, transport, manipulation or interfacing with electrodes provides a meaningful functional contribution to electrochemical reactions, bioelectrochemical processes, energy generation, energy conversion, energy-related screening or coupled sensing–energy platforms. Applications in which microfluidics is used only as a generic fluid-handling or sample-delivery technology, without a demonstrable role of the droplet architecture in the electrochemical or energy-related process, are excluded. This scope distinguishes the present review from general reviews of droplet microfluidics, electrochemical sensing and microbial fuel cells and enables a critical assessment of how droplet-level control can address specific limitations of conventional electrochemical and bioelectrochemical systems (Wang et al., 2023).

2 Principles of droplet microfluidics

The study of the precise control of discrete volumes of fluid in microscale applications is the basis of droplet microfluidics, which can be used to generate, transport, merge, split, sort and analyse highly uniform droplets (Lee et al., 2022). Such droplets serve as microreactors that can be employed for the controlled chemical, biochemical, biological or electrochemical reactions. These advantages of droplet-based systems (high surface-to-volume ratio, good mass and heat transfer, low reagent consumption, and exceptional throughput) have made them crucial tools in many scientific applications. (Thakur et al., 2021). Several fundamental principles are important for controlling the performance of droplet microfluidic platforms: droplet generation mechanism, fluid dynamics, material selection, fabrication methods, and surface wettability control. These principles are crucial in the rational design and optimisation of droplet microfluidic systems for energy, bioelectrochemical and analytical applications (Ly et al., 2025; Thakur et al., 2021; Ibrahim et al., 2022).

2.1 Droplet generation mechanisms

The key process involved in droplet microfluidics is droplet generation, which refers to the controlled break-up of one fluid phase into droplets within another immiscible continuous phase. The balance of forces involved in droplet formation, such as interfacial tension, viscous forces, inertial forces, and pressure gradients, in microscale channels dictates droplet formation. With careful control of these forces, it becomes possible to reproducibly generate highly monodisperse droplets of well-defined size and composition (Fergola et al., 2025; Pit et al., 2015). A number of geometric designs have been devised for droplet generation, most of which have been adopted: the T-junction, flow-focusing, co-flow and step-emulsification designs (Tan et al., 2004; Liu et al., 2020). Figure 1 shows the basic and commonly used geometries for droplet generation. T-junction devices involve a shearing action which causes droplets to form when the dispersed phase is orthogonal to the continuous phase. The flow-focusing geometries are those with converging streams of continuous phase that compress and shear the dispersed phase into droplets of controlled size. Co-flow systems produce droplets by flowing immiscible fluids in parallel, whereas step-emulsification devices rely on abrupt channel expansions to separate droplets (Seemann et al., 2012; Baroud et al., 2010; Pit et al., 2015). The type of droplet generator to use can be determined by droplet size, droplet generation frequency, fluid properties, droplet efficiency, and application. Recent developments in device design and flow control technologies have enabled the production of droplets with femtoliter-to microliter-scale volumes that are highly reproducible and support single-cell analysis, biosensing, material synthesis, and bioelectrochemical investigations (Fergola et al., 2025; Pit et al., 2015; Tan et al., 2004).

The design of the droplet generator defines how the balance between the viscous, interfacial, and pressure forces affects the breakup and controls the droplet size, frequency of formation, monodispersity, and stability. For passive microdroplet systems, two key dimensionless numbers are capillary number (Ca = μcUc/γ), the ratio of viscous to interfacial forces, and the flow-rate ratio between the dispersed and continuous phases. Changing these dimensionless numbers results in transition from squeezing, dripping, and jetting modes. Thus, the same flow rate will result in different droplets depending on the channel size, wettability, viscosity ratio, and interfacial tension (Baroud et al., 2010; Cai et al., 2025). In the case of T-junction, the dispersed fluid enters the main channel at an angle perpendicular to the continuous fluid flow. Continuous fluid undergoes deformation and elongation of the dispersed fluid by pushing it against the downstream channel walls. At relatively low continuous phase capillary number, the dispersed fluid blocks the channel and due to increasing pressure upstream the interface gets squeezed and ultimately pinched off. Increases in the flow rate of the continuous phase or (Ca) will increase the viscous shear effect and might cause a transition to dripping mode of operation where local necking takes place. Hence, T-junctions are a simple and highly repeatable method for producing droplets, although droplet size becomes sensitive to any variations in flow rate and channel wetting characteristics (Baroud et al., 2010; Deng et al., 2015).

In the flow focusing process, the dispersed phase is injected via the central channel, while the continuous phase approaches from the side channels and acts on the dispersed phase by hydrodynamic constriction before entering the downstream channel. Strong shearing and pressure gradients formed by the two streams form a thin filament which breaks down into droplets. Increases in the flow rate of the continuous phase result in reduction in the diameter of the dispersed phase thread and hence reduction in the size of the droplets formed, although in excess amounts the dripping to jetting transition might occur. In the case of co-flow, the two fluids experience a nearly parallel motion in relation to each other, either in concentric capillaries or aligned microchannels. The difference with T-junction and planar flow focusing is that the dispersed phase is mainly stressed by viscous effects in an axisymmetric fashion. Depending on the respective capillary numbers and viscosity ratio, breakup can be induced through dripping, jetting or other types of capillary instability phenomena. In the case of low shear stresses experienced by the dispersed phase, co-flow is highly appropriate for encapsulating shear sensitive biological components and for generating uniform core-shell and multiple emulsions (Bi et al., 2025).

Step emulsification is entirely different from T-junction and flow focusing emulsifications, which rely on the shear effects of the continuous phase on the dispersed phase. Instead, in the step emulsification geometry, the dispersed phase flows in a confined channel and then meets a sudden change in depth or width of the channel. This causes a capillary pressure imbalance leading to the spontaneous deformation and break-up process occurring at the step. Droplet generation is dominated by interfacial tension and device geometry instead of direct shear by the continuous phase. But above a certain flow rate of the dispersed phase, the step regime can move into the jetting regime where larger drops will be formed. Parallelization of step emulsification devices is also another method for reaching higher throughput. In total, all these geometries constitute different methods for controlling the ratio of viscous forces, pressure gradients, capillary forces, and geometric confinement. T-junction and flow focusing systems provide strong hydrodynamic control, while co-flow systems provide soft interfacial deformation, and step emulsification takes advantage of geometric confinement and capillary pressure difference. Thus, the choice of the right geometry for the emulsion process depends on the target droplet size as well as other factors (Deng et al., 2015; Bi et al., 2025).

2.2 Flow regimes and fluid dynamics

In droplet microfluidic systems, the behaviour of the fluids is controlled by microscale fluid dynamics, which is vastly different from the behaviour in conventional macroscopic fluid dynamics systems (Liu et al., 2020). Fluid flow in microchannels is mostly laminar flow where the Reynolds number is low and the flow pattern is very predictable because of the small dimensions of the microchannels (Fergola et al., 2025). In such cases the viscous forces are more dominant than the inertial forces, and the fluid flow is stable and controllable. This laminar flow environment allows for a precise control in droplet formation, transport and manipulation which is necessary to ensure the reproducibility of microfluidic operations (Teo et al., 2019). Droplet microfluidics is characterized by several dimensionless numbers such as the Reynolds number, Capillary number, Weber number, and Bond number (Lee et al., 2022; Pit et al., 2015). Capillary number is one of these and is the ratio of the viscous forces to the interfacial tension and thus plays an important part in the dynamics of droplet formation (Shang et al., 2017). A variety of flows from squeezing to dripping to jetting to parallel flow modes can be achieved, depending on the flow rates and the channel geometries and the properties of the fluids at the interface. These regimes directly affect the droplet size distribution, frequency of droplet formation and the stability of the system (Pecar et al., 2021). Furthermore, droplets also have internal recirculation that will give better mixing and mass transfer in the droplet for faster reaction rates and analytical capabilities. Thus, for complex biological, electrochemical and energy-related applications, a comprehensive understanding of fluid dynamics and flow regimes is essential to optimise the droplet microfluidic systems (Zhu and Wang, 2016; Pit et al., 2015). Table 1 provides the details of governing parameters influencing the droplet microfluidics (Bourega et al., 2023; Hoang et al., 2024; Hoang et al., 2024; Venkateshwarlu and Bharti, 2021; Gai et al., 2016; Potdar et al., 2025; Loizou et al., 2018).

TABLE 1. Dimensionless parameters influencing droplet generation.

2.2.1 Governing principles and dimensionless parameters of droplet formation

Droplet generation in microfluidics is due to the effect of viscous, inertial, capillary, gravitational, and confinement forces acting on the fluid flow. Thus, flow rate does not provide a complete description of droplet size and dynamics and has to be analyzed using dimensionless hydrodynamic parameters, such as the Reynolds number (Re), Capillary number (Ca), Weber number (We), Bond number (Bo), viscosity ratio (λ), flow-rate ratio (ϕ), and confinement ratio (α). Recent reviews suggest that knowledge of these hydrodynamic parameters plays a significant role in achieving controlled droplet size, uniformity, frequency, and scalability (Nan et al., 2024).

The Reynolds number (Re = ρUDh/µ), describes the ratio between inertial and viscous forces in fluid flows. In conventional microfluidic droplet generators, the flow regime is laminar, as viscous forces prevent turbulent mixing and allow the reproducible creation of interfaces. Inertial forces are not necessarily low at all flow conditions, however, and increase with increasing flow velocity and/or the characteristic channel length scale. Experimental work spanning Re values from about 10^–2 to 10² reveals that droplets dynamics change from viscous-capillary to visco-inertial regime when Re and Ca increase (Ma et al., 2024). Capillary number (Ca = µc Uc/γ) is among the important parameters for controlling droplet deformation since it represents viscous stresses of the continuous phase to the interfacial tension. For low values of (Ca), interfacial tension plays a dominant role, and hence, it keeps the shape of the droplets small. As Ca increases, it leads to an increase in deformation of the dispersed phase due to viscous forces and faster droplet breakup. However, Capillary Number alone cannot define the flow regime. Recent investigations reveal that squeezing-to-dripping transition is also affected by the flow rate ratio and device geometry and hence, capillary number is modified in terms of geometric and flow parameters (Panwar and Roy, 2024).

Flow rate ratio (φ = Qd/Qc) defines the relative contribution of the volumes of the dispersed and continuous phases. Increase in (φ) increases the volume or length of the droplets generated in each cycle of droplet generation, especially in the squeezing regime. On the other hand, when continuous phase flow increases, droplet size is reduced because of increased interfacial shear stress. Most importantly, recent studies show that flow rate ratio affects not only droplet size but also flow regime transition, especially in case of constant (Ca) (Duan et al., 2024). The viscosity ratio (λ = µd/µc) represents the ratio between the viscous resistance of the two phases. The impact of λ depends on the regime. When the viscosities of the dispersed and continuous phase are similar, variations in λ affect neck thinning, interfacial deformation and droplet volume significantly. Under a very high viscosity contrast, the effect of λ on droplet size may be insignificant. Therefore, the viscosity ratio should be regarded in conjunction with Ca and flow-rate ratio rather than as a separate predictor of droplet size (Sapkota and Adams, 2024). Weber number (We = ρU2Dh/γ) is the ratio between the inertia forces and surface tension. It becomes increasingly relevant as the speed of the flow increases. A low value of We stabilizes the interface through capillary action, while the increase in We leads to the stretching of the interface, jet formation and finally satellite droplet formation under strong enough inertial forcing. Modern experiments studying the dripping-to-jetting transition show that the critical value of Weber number can be used to detect the regime transition from dripping to jetting (Chen et al., 2022).

The Bond number (Bo = δρgDh2/γ), is indicative of the gravitational and capillary forces. As microfluidic channel dimensions are small, Bo is always much smaller than unity, and gravity plays little role in the droplet formation. However, it gains importance with the increasing droplet/channel size, thus becoming important for the millimetric sized droplets and for scaling up. This factor is of great importance for energy droplet reactors as the variation of the dimension changes the relative importance of the forces (Zhang et al., 2025). The confinement is determined by the ratio (α = d/Dh), where d is the droplet diameter and (Dh) is the characteristic channel dimension. Small α corresponds to a less confined drop while α close to one means highly confined drop with elongated morphology and plug-like droplets. The latest experiments on confined monodisperse emulsions showed that such strong confinement affects both the morphology and velocity of droplets (Sapkota and Adams, 2024; Chen et al., 2022).

In aggregate, the above parameters delineate three regimes that frequently come up: squeezing, dripping, and jetting. The squeezing regime is characterized by low Ca and We values, wherein capillary forces take precedence over the rest and result in very consistent drops albeit in terms of throughput, lower. In the dripping regime, viscous forces start to deform the dispersed phase and break-up happens close to the junction, creating a good balance between droplet size, monodispersity, and rate of production. When viscous or inertial forcing is strong enough, the interface extends to form a jet prior to breaking apart into drops, which could result in high throughput but also in satellites and polydispersity. Notably, the demarcation between these regimes is not fixed and varies with channel geometry, phase properties, flow-rate ratio and confinement. The functional implications of the above hydrodynamic parameters are particularly significant for energy and bioelectrochemical applications. The droplet size influences the diffusion distance and the surface area to volume ratio, while the flow rate ratio affects the amount of reagent or substrate in each droplet. The frequency of droplet generation is responsible for the number of independent reaction environments per unit time, while monodispersity ensures reproducibility in the electrochemical results from the droplets. This implies that when optimizing droplet microfluidic devices for electrochemical and bioelectrochemical applications, multiple hydrodynamic parameters need to be optimized simultaneously (Duan et al., 2024; Sapkota and Adams, 2024). Table 2 illustrates the influence of the dimensionless parameters on droplet size, monodispersity and throughput (Zhu and Wang, 2016; Singh, 2018; Loizou et al., 2013; Pang et al., 2022; Christopher et al., 2008; Roberts et al., 2012; Alessio et al., 2016; Lee et al., 2008; Gai et al., 2016; Erb et al., 2011; Samadder et al., 2022; Bourega et al., 2023; Venkateshwarlu and Bharti, 2021).

TABLE 2. Influence of governing parameters on droplet size, monodispersity and throughput.

2.3 Materials and fabrication techniques

Choosing appropriate materials and manufacturing processes is an important aspect that affects the performance, durability, and function of droplet microfluidic devices. The ideal material for microfluidic fabrication should have strong mechanical properties, good chemical compatibility, optical transparency, biocompatibility, and processability. A variety of materials have been used for the fabrication of microfluidic devices over the years, such as silicon, glass, polymers, ceramics and hybrid composite materials (Shang et al., 2017; Pit et al., 2015). Polydimethylsiloxane (PDMS) is one of the most popular polymeric substrates because it is optical transparent, soft, permeable to gas and can be easily fabricated using soft lithography. The process of manufacturing a PDMS-based microfluidic chip includes four major steps: pre-fabrication, mold fabrication, PDMS device fabrication, and its application. In the first step, the microfluidic design is created on the computer using the CAD software and simulated for Multiphysics analysis. After that, SU-8 photoresist is spin-coated on the silicon wafer, and after soft baking and photomask alignment, UV exposure creates a microchannel pattern on the mold. Next, the pattern is developed, baked, and rinsed for obtaining the required microstructures. Then, PDMS is poured on the mold, cured at about 80 °C, and peeled from it. Figure 2 indicates the stepwise process for fabrication of PDMS microfluidic chip. Glass and silicon devices are highly resistant to chemicals, temperature and have excellent dimensional stability and precision and are very suitable for analytical and electrochemical applications. However, thermoplastic materials like polymethyl methacrylate (PMMA), cyclic olefin copolymer (COC) and polycarbonate materials have also received much attention because of their compatibility with large-scale manufacturing processes and low production costs (Li et al., 2018; Tan et al., 2004). To make microfluidic architectures with high precision, various microfabrication techniques have been developed. Traditional micromachining techniques are photolithography, soft lithography, wet etching, dry etching, micromachining and laser ablation. More recently, new methods of additive manufacturing (3D printing) have come to the fore as viable alternatives to the rapid prototyping and customized device manufacturing. These technological developments have greatly broadened the reach and scope of droplet microfluidics, and have led to the creation of ever more complex platforms for energy conversion, bioelectrochemical investigation and biomedical diagnosis (Li et al., 2018; Pit et al., 2015). Table 3 presents a comparison of the materials used in the fabrication of the droplet microfluidics system (Makamba et al., 2003; Zhu et al., 2015; Mehta et al., 2007; Shirtcliffe et al., 2013; Brennan and Eddington, 2014; Borók et al., 2021; Alrifaiy et al., 2012; Aralekallu et al., 2022).

TABLE 3. Comparison of materials used for droplet-based microfluidic systems.

2.4 Surface functionalization and wettability control

The performance and stability of droplet microfluidic systems is very sensitive to surface properties (Subramanian et al., 2011). The wettability, surface energy, roughness and chemical composition of droplets directly affect the droplet generation, transport, coalescence and interaction with the channel walls (Li et al., 2021). Therefore, good control of these properties is crucial for good droplet formation and stable operation over the long term (Yang et al., 2022). Surface functionalization can be used to modify the physicochemical properties of channel surfaces for specific applications (Li et al., 2021; Ashok et al., 2024). To control the fluid behaviour and to produce water-in-oil or oil-in-water emulsions, commonly used surface treatments are hydrophobic or hydrophilic (Chen et al., 2017). There are many methods used to change the wettability of the surface, such as plasma treatment, chemical vapour deposition, salinization, polymer grafting, and self-assembled monolayer formation, which have been used to enhance the performance of devices (Subramanian et al., 2011; Baret, 2012). Surface modification strategies can also be applied for the immobilization of biomolecules, enzymes, antibodies, nucleic acids, nanoparticles and electroactive materials for biosensing and bioelectrochemical applications (Yang et al., 2022; Zhou et al., 2012). In recent years, wettability control in microfluidics has been further extended by the emergence of new technologies, including new types of nanostructured coatings, stimuli-responsive materials and coatings and bioinspired surface engineering (Ashok et al., 2024; Chen et al., 2017; Salva et al., 2021). These innovations allow droplet properties to be dynamically controlled, nonspecific droplet adsorption to be minimized, biocompatibility to be improved, and analytical sensitivity to be enhanced (Ashok et al., 2024). However, as droplet microfluidics is further developed into more complex and multifunctional devices, new advanced surface functionalization strategies will be crucial for improving the performance and expanding the application potential of the devices in energy, environmental and biomedical applications (Subramanian et al., 2011; Yang et al., 2022).

3 Droplet manipulation and detection strategies

However, the real strength of droplet microfluidics is in its ability to precisely manipulate and analyse individual droplets. These sophisticated methods of handling droplets provide a high efficiency, reproducible complex chemical, biological, and electrochemical processes to be conducted in microscale compartments (Convery and Gadegaard, 2019; Shang et al., 2017). Droplet microfluidic systems are now highly versatile systems in analytical chemistry, biotechnology, energy research and bioelectrochemical applications due to their selective merging, splitting, sorting, transporting and monitoring of droplets (Fergola et al., 2025; Pit et al., 2015). In addition, advanced detection techniques and biosensing technology have been developed that allow for the monitoring of reactions and biological processes in a droplet-by-droplet manner. These have made droplet microfluidics a powerful platform for high-throughput screening, single-cell analysis, diagnostics, and next-generation sensing applications (Zhu and Wang, 2016; Schütt et al., 2016).

3.1 Droplet merging, splitting, and sorting

Precise control of droplet contents, composition and functionality is a fundamental component of droplet microfluidics, which can be accomplished by manipulation of droplets (Xi et al., 2017). Droplet merging, splitting and sorting are widely used manipulation techniques for complex analytical and biochemical operations (Xi et al., 2017; Agnihotri et al., 2025; Ding et al., 2019). These processes allow for reagent mixing, sample dilution, reagent compartmentalization, and selective separation of targeted droplets for further analysis (Niu et al., 2009). The merging of two or more droplets to start chemical reactions, add more reagents or mix biological samples is called droplet merging (Chung et al., 2017). Controlled droplet fusion has been achieved by a variety of techniques, such as passive channel geometries and active techniques based on electric, magnetic, acoustic, thermal, or optical forces (Xi et al., 2017; Ding et al., 2019). Droplet splitting on the other hand allows for the splitting of larger droplets into smaller daughter droplets, which makes it easier to dilute the sample, run parallel processing and do high throughput experimentation. With respect to the splitting ratio, it can be optimized by the channel design and flow regulation (Agnihotri et al., 2025; Jin et al., 2017). The applications of interest that are associated with the rare event detection, single-cell screening, and biomarker identification are particularly emphasized in the context of droplet sorting (Xi et al., 2017; Chung et al., 2017). The optical, electrical, magnetic, or fluorescent characteristics of individual droplets are typically used in sorting mechanisms. Selective separation of droplets containing desired targets is possible with active sorting methods, including dielectrophoresis, acoustic waves, magnetic field and pneumatically driven droplets. Such high level of manipulation flexibility and functionality is particularly advantageous for droplet microfluidic systems in biological, electrochemical and energy applications (Fergola et al., 2025; Pit et al., 2015; Agnihotri et al., 2025).

3.2 Digital and continuous-flow microfluidics

Based on their operating principles and benefits, droplet microfluidic systems can generally be categorised as either digital or continuous-flow microfluidic systems (Sun et al., 2020). Continuous-flow microfluidics is based on the continuous flow of fluid through interconnected microchannels in controlled flow conditions (Wu et al., 2021). Droplet-based continuous flow systems rely on droplet formation and flow within the continuous carrier phase, enabling efficient processing and control of reaction processes (Wu et al., 2021). Such systems are capable of generating thousands of droplets per second with a very uniform droplet size, making them ideal for dynamic monitoring, material synthesis, and large-scale screening applications. (Zhou et al., 2020). Unlike digital microfluidics, however, which relies on externally applied forces to manipulate droplets on planar surfaces, digital microfluidics relies on the manipulation of flow in channels (Ahmadi et al., 2019). One of the most commonly used digital microfluidic technologies, Electrowetting-on-dielectric (EWOD), enables control of droplet flow, merging, splitting, and dispensing by applying an electric field (Liu et al., 2023; Wu et al., 2023). The lack of fixed microchannels provides greater operational freedom and enables complex fluidic workflows to be reconfigured via software control (Arshad et al., 2024). Each method has its own merits, depending on the specific use. Continuous-flow systems are ideal for large-scale and uniform reaction conditions, while digital microfluidics offers high programmability, flexibility, and integration with analytical platforms (Coelho et al., 2023). Recently, hybrid systems that integrate the benefits of both technologies have been a research hotspot to realize more functional and efficient advanced microfluidic systems (Coelho et al., 2023). Table 4 shows the comparative analysis of CFDM and DMF (Fouillet et al., 2006; Hassan et al., 2019; Levent et al., 2006; Arshad et al., 2024; Haselmayr et al., 2019; Shi et al., 2021; Nelson and Kim, 2012).

TABLE 4. Comparison between Continuous-flow droplet microfluidics and Digital microfluidics.

3.3 Optical, electrochemical, and impedance detection

It is important to use sensitive and reliable detection methods to obtain information from droplet microfluidic systems. Different analysis methods have been coupled to the droplet platforms to monitor chemical reactions, biological activities, cellular responses, and electrochemical processes inside individual droplets in real-time (Liu and Zhu, 2020). Of these, optical, electrochemical, and impedance sensing are the most popular since they are sensitive, versatile, and can be used in microscale systems (Yan et al., 2024; Solvas et al., 2011; Hengoju et al., 2021). Fluorescence microscopy, absorbance spectroscopy, chemiluminescence, Raman spectroscopy, and surface-enhanced Raman scattering are some of the highly sensitive techniques used for optical detection of biomolecules, cells, and chemical species (Yan et al., 2024; Solvas et al., 2011). However, fluorescence-based methods remain widely used for their high sensitivity and potential for screening applications. Optical systems, however, can be very complex and use a variety of instrumentation and labelling strategies that can make assays more expensive and complicated to operate (Solvas et al., 2011).

In turn, electrochemical detection has been widely studied as a promising alternative because of its speed of response, portability, low power consumption, and being small-scale compatible (Liu et al., 2008). Electrochemical methods like amperometry, voltammetry, potentiometry and chronoamperometry provide highly sensitive detection of electroactive species and interactions in droplets (Liu et al., 2008; Thomas et al., 2023; Sangam et al., 2020). Microelectrodes are integrated into droplet microfluidic devices to be able to monitor the oxidation/reduction process, cellular metabolism, and bioelectrochemical processes in real time (Kemna et al., 2012). Label-free analysis of cellular properties, particle concentrations, and interfacial phenomena in droplets can be achieved using impedance-based detection. Changes in electrical impedance between microelectrodes provide useful information on cell viability, microbial growth, particle encapsulation, and biomolecular interactions (Sobahi et al., 2014; Liu et al., 2024). These detection modalities have greatly enhanced the analytical capabilities of droplet microfluidic devices and have led to their use in many scientific and technological applications (Thomas et al., 2023; Ma et al., 2023; Srisa-Art et al., 2007). Table 5 presents a comparative performance assessment of optical and electrochemical detection methods (Tavakoli et al., 2022; Mazzaracchio and Arduini, 2025; Kumar et al., 2013; Chen et al., 2020; MohamedSikkander, 2014; Pour et al., 2023; Chaoran, 2023; Tamayo, 2018; Jang et al., 2016; Arora et al., 2018).

TABLE 5. Comparative performance of optical and electrochemical detection methods.

3.4 Integration with biosensing platforms

Nevertheless, when combined with biosensing, droplet microfluidics has led to highly powerful platforms for biological analysis, which allow rapid, sensitive and multiplexed analysis of biological samples (Ly et al., 2025). Biosensors are devices that integrate biorecognition with transduction processes that transform a biological interaction to a measurable signal (Villalonga et al., 2020; Bao et al., 2025). These systems, in conjunction with droplet microfluidics, have a number of advantages such as improved control of the reactions, lower sample consumption, better mass transport, and high throughput. Several types of biosensors have been integrated into droplet microfluidic systems, such as electrochemical, optical, piezoelectric, and field-effect transistor (FET) sensors (Villalonga et al., 2020; Palchetti and Mascini, 2012). The electrochemical biosensors are ideal for miniaturized systems, ease of integration and have excellent analytical performance. Droplets can be used to compartmentalize individual events in biology, enabling strong sensitivity and cross-contamination avoidance, and loss of sample (Gegen et al., 2025; Shang et al., 2026). Advances in the past few years have allowed for the inclusion of antibodies, aptamers, nucleic acids, enzymes, microbial cells, and synthetic recognition elements in droplet-based biosensing systems (Reaño and Escobar, 2024). These are used for detection of pathogen, antimicrobial susceptibility testing, single cell analysis, screening for biomarkers, environmental monitoring, and bioelectrochemical investigation (Khan et al., 2025). Moreover, the rapid progress in microfabrication, wireless communication, artificial intelligence and automated data process are enabling the creation of full integrated sample-to-answer devices for conducting complex analysis in real-time. Therefore, droplet microfluidics is expected to be a key contributor toward the development of next-generation diagnostic, environmental, and energy-related analytical systems in combination with biosensing technologies (Liu et al., 2021).

4 Energy applications of droplet microfluidics

With the growing worldwide demand for sustainable and efficient energy technologies, there has been significant research on advanced platforms that can enhance processes of energy conversion, storage and utilization. Of these new technologies, the technology of droplet microfluidics has attracted great interest for its ability to control fluid behavior, reaction rates, mass transport and microscale compartmentalization with high accuracy. Droplet microfluidic systems allow for highly controlled chemical and electrochemical processes with reduced amounts of reagents and increased reaction efficiency by manipulating discrete droplets as if individual microreactors. These benefits have facilitated a variety of applications such as fuel cells, energy capturing devices, batteries, supercapacitors, hydrogen generating systems, etc., and advanced functional materials synthesis. Droplet microfluidics combined with energy technologies presents novel opportunities to discover materials, enhance device performance and develop sustainable energy solutions (Jiang, 2022). Figure 3 shows the droplet-based electrochemical system for applications in energy processes.

4.1 Microfluidic fuel cells

Microfluidic fuel cells (MFCs) are innovative type of energy conversion devices which are powered by chemical fuels in micro-scale fluidic architectures. In a conventional fuel cell, a membrane is used to separate fuel and oxidant streams, but in microfluidic fuel cells, the stable separation of fuel and oxidant streams is achieved by linear flow in microchannels. This membrane free design allows a simpler architecture of the device, decreases the complexity of fabrication and eliminates the problems of membrane degradation and crossover (Thakur et al., 2020; Chen et al., 2018). The exact regulation of the flow of fluid inside the micro channels improves the mass transfer rate and enables the efficient use of reactants to improve the overall performance of the fuel cell. A variety of fuels, such as hydrogen, methanol, formic acid, ethanol, and biological substrates, have been explored in microfluidic fuel cell systems. In addition, droplet based have been used to introduce discrete fuel and oxidant chambers to allow more control over the reaction and to lead to a reduced fuel mass. Power density and operational stability have also been improved in recent years by developing more effective electrode materials, catalysts, and designing microchannels. The small size, low fuel consumption and portability of microfluidic fuel cells make them attractive for miniature electronic devices, wearable electronic devices and remote sensing systems (Jiang, 2022; Thakur et al., 2020). Yang et al. (2018) has discussed the generation of electricity using the microfluidic biofuel cell (Yang et al., 2018).

It is necessary to differentiate between traditional microfluidic energy devices and microfluidic droplet energy devices due to the different fundamental transport and reaction processes in each case. Traditional microfluidic fuel cell energy devices commonly make use of laminar flow streams of the fuel and oxidant inside microchannels, where the stream interface provides the primary method for reactant separation for membrane less devices. The devices provide advantages of small diffusion lengths and large electrode-to-volume ratios, but no droplets are involved. As an illustration, membrane less microfluidic fuel-cell arrays have achieved efficiency of 93% for parallel configuration and 82% for serial configurations, while a micro direct methanol fuel-cell stack has attained a maximum power density of 27.5 mW cm^-2. Thus, such studies can be regarded as traditional continuous-flow microfluidic energy devices (Hou et al., 2011; Chen et al., 2012).

On the other hand, droplet-based microfluidics creates discrete spatially isolated droplets in an immiscible carrier fluid. Droplets can act as single compartment reaction vessels, screening compartments, or microreactors offering benefits including precise volume control, fast internal mixing, lower consumption of reagents, and parallelization. The droplet-based microfluidic devices have the ability to form monodisperse droplets with frequencies up to kHz and hence can handle a lot of independent reaction compartments in parallel. Therefore, any research in which the droplets play an active role in energy conversion, bioelectrochemical reactions, electrochemical analysis, or the synthesis of energy materials is considered a droplet-based approach. There is another category for droplet-assisted energy systems in which the droplets are used in synthesis or processing of functional energy materials and then integrated into the existing fuel cell, battery, or biofuel cell technology. This avoids confusion between microfluidic fuel cells and real droplet-based systems.

4.2 Droplet-based energy harvesting systems

Droplet-based energy harvesting systems use the motion, the deformation or the interaction of a liquid droplet to generate electric power from mechanical, thermal, solar, and chemical energy (Chen et al., 2018). These systems have become promising alternatives to powering low-power electronic devices and autonomous microsystems. The controlled motion of droplets in microfluidic environments can be achieved by leveraging the characteristics of these unique phenomena, such as triboelectric, piezoelectric, electrostatic and electrokinetic effects, among others (Cheng et al., 2015). The electrical charges created during the periodic contact and separation of the droplets and functionalized surfaces can be harvested as usable electrical energy in droplet-enabled triboelectric nanogenerators (Zhong et al., 2020). Finally, electrostatic energy harvesting systems use the redistribution of charges that is generated by droplet motion over conductive surfaces. Due to the tiny scale of droplet microfluidic platforms, droplet path manipulation, droplet frequency, and droplet-manipulation control are precisely controlled, leading to better energy conversion efficiency (Cheng et al., 2015). Moreover, droplet-based systems can be combined with ambient energy sources like rain, humidity changes, liquid flow and mechanical vibrations to produce a sustainable energy source. It is because of the characteristics of the energy harvesting technology using droplets that make them suitable for use in self-powered sensor networks, wearable electronics, environmental monitoring, and autonomous microscale systems (Chen et al., 2018). In addition to this, Li et al. (2024) designed an energy harvesting system that uses total current nanogenerator for self-powered electronic system (Li et al., 2024).

4.3 Battery and supercapacitor research

Energy storage systems that exhibit high-performance characteristics are vital to fulfilling the energy requirements of portable devices and electric vehicles as well as renewable energy source integration. An emerging application of droplet microfluidic technology is its utilization as an experimental platform for battery and supercapacitor studies, which makes it possible to control material synthesis, electrode preparation, and electrochemical analysis of the resultant products. The droplets are placed in a chamber, whereupon the products obtained exhibit uniformity in reaction conditions due to their nanoscale structure and other properties (Ma et al., 2020). Microfluidic techniques have been widely used to fabricate electrode materials, including metal oxides, carbon nanostructures, conductive polymers, and hybrid nanocomposites, for lithium-ion, sodium-ion, and supercapacitors. High mass and heat transfer rates in droplets lead to fast nucleation and growth processes, thereby creating highly homogeneous materials and, consequently, better electrochemical performance. Furthermore, droplet microfluidics can be used to screen electrolyte formulations, electrode designs, and energy storage materials in a highly efficient, controlled experimental environment. In addition, recent advances have enabled the development of microfluidic batteries and micro supercapacitors integrated directly into lab-on-chip systems. The miniaturised energy storage devices can be charged quickly, have high power density and are suitable for portable and wearable applications. The development of such energy storage technologies will make droplet microfluidics increasingly relevant for the rapid discovery of materials and the optimisation of energy storage devices in the near future (Thakur et al., 2020; Ma et al., 2020). He et al. (2022) have fabricated a microfluidic-based ionic hydrogel battery for various electrically driven applications (He et al., 2022).

4.4 Hydrogen production and electrolysis

Hydrogen is well-known as a clean and sustainable energy carrier and has great potential for future energy systems. Renewable-energy-based hydrogen production and electrochemical water splitting are important research topics. Droplet microfluidics offers many potential benefits over production research for hydrogen, as it enables control of reaction conditions, evaluation of catalysts, gas-liquid interactions, and electrochemical processes at the microscale. Conventional bulk electrolysis systems can be improved by using microfluidic electrolysis systems, which offer improved mass transport, efficient gas bubble management, and improved electrode utilisation (Gregoire et al., 2013). The high surface-to-volume ratio is a characteristic feature of microfluidic environments that enables faster movement of reactants and products, leading to less concentration polarisation and more efficient electrolysis. Moreover, droplet-based microreactors can provide highly controlled platforms for evaluating electrocatalysts in both Hydrogen Evolution Reaction (HER) and Oxygen Evolution Reaction (OER). In recent years, droplet microfluidics has been used to screen catalyst compositions, optimise reaction conditions, and study fundamental electrochemical mechanisms in hydrogen production. Using minimal reagent volumes to perform multiple parallel experiments greatly accelerates catalyst discovery and process optimisation. Therefore, droplet microfluidic technologies have been gaining momentum as useful tools for enhancing hydrogen generation systems and contributing to the shift towards sustainable energy infrastructures (Yang et al., 2025). Anita Šalić and Zelićet al. (2022) have explained the microfluidic technology for enhancing the biohydrogen production (Šalić and Zelić, 2022).

4.5 Nanomaterial and catalyst synthesis for energy devices

The efficiency, longevity and performance of current energy conversion and storage technologies are directly influenced by nanomaterials and catalysts. The ability to precisely control droplet microfluidic synthesis has successfully made it a platform of choice for the production of advanced functional materials with customised physicochemical properties. In contrast to the typical batch synthesis approaches, droplet-based microreactors offer highly uniform reaction environments that allow for control of reaction time, temperature, concentration gradients, and mixing regimes (Gago et al., 2012). Improved heat and mass transfer in droplets promote controlled nucleation and growth, leading to a narrower size distribution, better crystallinity, and improved reproducibility of the nanomaterials. Various functional materials have been produced on droplet microfluidic platforms, such as metallic nanoparticles, metal oxides, quantum dots, carbon-based nanomaterials, metal-organic frameworks, and heterogeneous catalysts. They have been used in a wide range of applications, such as fuel cells, batteries, supercapacitors, solar energy conversion devices, and hydrogen production systems (Koh, 2017). In the future, the development of next-generation catalysts and nanomaterials for energy technologies will increasingly rely on droplet microfluidics in order to satisfy the demand for advanced energy materials (Gupta and Khan, 2026; Guo et al., 2021). Figure 4 shows the various applications of droplet microfluidic system for different energy processes.

5 Bioelectrochemical applications

Bioelectrochemical systems and droplet microfluidics are now converging to investigate biological processes, develop advanced biosensors, and enhance diagnostic technologies. Bioelectrochemical systems provide an interface between biological and electrochemical components and enable a biochemical event to be translated into an electrical signal. Droplet microfluidics has greatly improved the performance of bioelectrochemical platforms, due to unique capacity for precision manipulation, compartmentalisation, high efficacy, and single-cell resolution. Droplet-based systems provide a highly controlled microenvironment for detailed studies of cellular behaviour, enzymatic reactions, microbial metabolism and biomolecular interactions. These developments have enabled the creation of innovative applications such as biosensing, microbial/enzymatic fuel cells, point-of-care diagnostics, organ-on-chip and pathogen detection, demonstrating the increasing relevance of droplet microfluidics in the current research on Bioelectrochemistry (Gu et al., 2014).

5.1 Bioelectrochemical sensors and biosensors

One of the most interesting applications of droplet microfluidics is the development of bioelectrochemical sensors which are used to detect biological and chemical analytes with sensitive and selective electrochemical signal transduction. Such devices are usually made up of biological recognition element, which may be enzymes, antibodies, nucleic acids, aptamers or microbial cells, and an electrochemical transducer that receives the biochemical interactions and translates the interaction to an electrical signal that can be measured. (Gu et al., 2014; da Silva Junior et al., 2024). The fast mass transfer and the minimal diffusion barrier of the microscale environment drops into droplets result in high sensor response time and high analytical sensitivity. In the field of droplet-based biosensing, several electrochemical methods, including amperometry, voltammetry, potentiometry and impedance spectroscopy, have been successfully applied to detect metabolites, proteins, nucleic acids, toxins and environmental contaminants. Figure 5 shows the various biorecognition elements used for pathogen detection. Moreover, generating and analysing large numbers of droplets allows large-scale screening and multiplexed analysis. The analytical capabilities of droplet-based bioelectrochemical sensors have been further improved recently through the development of new nanomaterials, microelectrode fabrication and integrated electronics, which have enabled these sensors to be useful tools for a wide range of applications, including healthcare, environmental monitoring and industrial biotechnology applications (Narakathu et al., 2009; Yu et al., 2024; Song et al., 2019).

5.2 Microbial fuel cells and enzymatic fuel cells

Bioelectrochemical technologies are important that harvest biochemical energy to electrical energy with biological catalytic process such as microbial fuel cells (MFCs) and enzymatic fuel cells (EFCs). Microbial fuel cells, where the electrons generated by electroactive microorganisms are transferred to the electrode, which causes the current in the cell. Enzymatic fuel cells on the other hand use particular enzymes as biocatalysts to enable oxidation and reduction reactions at the surface of the electrodes. The coupling of droplet microfluidics with these has led to better control of the biological and electrochemical processes, thus providing improved device performance and mechanistic understanding (Lee and Kjeang, 2010). Microbiological studies of the metabolism, extracellular electron transfer pathways, enzyme kinetics, and biofilm formation of microorganisms have been advanced using droplet microfluidic platforms. Microbial cells or enzymes are encapsulated in each droplet, providing a way to investigate the biological heterogeneity and catalytic activity at the microscale. Moreover, droplet-based methods allow for screening a large number of microbial strains, enzyme variants, substrates and electrode materials, which can significantly speed up the optimization of bioelectrochemical systems. Advances in the past few years have shown the feasibility of miniaturized microbially and enzymatically fueled electrocatalytic devices embedded in microfluidic platforms, which could be used in self-powered biosensors, portable electronics, and environmental monitoring systems. They represent the current capabilities of droplet microfluidics for the creation of next-generation bioenergy technologies (López-González et al., 2014; González-Guerrero et al., 2016).

5.3 Point-of-care diagnostic systems

The applications of point-of-care (POC) diagnostic systems have grown important for quick disease diagnosis, decentralized healthcare delivery and personalized medicine. Combining droplet microfluidics and bioelectrochemical sensing technologies has opened the door to highly sensitive, portable and cost-effective diagnostics platforms which can carry out complex analytical processes in non-laboratory environments. Droplet microfluidics is a technology that is very attractive to clinical diagnostics because it allows for manipulation of minute sample volumes with high precision and the ability to analyze the contents within a short period of time (Sun and Hall, 2018). Multiple functions can be carried out simultaneously on a single droplet-based bioelectrochemical diagnostic system, such as sample preparation, target enrichment, detection of biomarkers, and signal transduction. Completely compatible with miniaturized instrumentation and portable electronic devices, electrochemical detection methods are also rapid and quantitative. In recent years, new technologies have allowed for the identification and detection of disease biomarkers, nucleic acids, proteins, metabolites, and infectious agents with great sensitivity and specificity. Additionally, incorporating smartphone interfaces, wireless communication modules, and cloud-based data analysis systems have made point-of-care diagnostics easier and more versatile to use. These advances will be increasingly significant to promote access to healthcare, especially in resource poor areas and remote locations (Scott et al., 2022; Qiu et al., 2025).

5.4 Single-cell and organ-on-chip bioelectrochemistry

There has been growing interest in understanding biological processes at the single-cell level to advance biomedical research, drug discovery, and personalized medicine. Droplet microfluidics is a powerful platform for single-cell analyses as it allows individual cells to be encapsulated and isolated in discrete microdroplets. Detailed study of cellular heterogeneity, metabolic activity, gene expression, and electrochemical behaviour that might be obscured in bulk population studies is possible with this compartmentalization (Trouillon and Gijs, 2016). The combination of electrochemical sensing and single-cell droplet platforms enables real-time monitoring of cellular responses, secretion profiles, and metabolic processes with unprecedented sensitivity. These have enabled the study of individual-cell electron transfer, cellular respiration, neurotransmitter release, and enzymatic activity. At the same time, a new generation of micro physiological systems, known as organ-on-chip, which can recapitulate the structural and functional properties of human tissues and organs, has been developed. Bioelectrochemical sensing can be integrated into organ-on-chip systems to monitor physiological parameters, tissue responses, and biochemical processes in real time. These technologies have the potential to serve as useful alternatives to traditional in vitro and animal-based models, as they offer greater physiological relevance to disease modelling, toxicological testing, and drug discovery and development. Thus, droplet microfluidics is emerging as an important tool to enhance the potential of contemporary bioelectrochemical studies (Trouillon and Gijs, 2023; Wu R. et al., 2014).

5.5 Pathogen and biomarker detection

In clinical diagnostics, food safety, environmental monitoring, and public health surveillance, rapid and efficient detection of pathogens and disease biomarkers remains a significant challenge. Manipulation of droplets has become a powerful tool to overcome these challenges because droplet-based microfluidics enables sensitive detection within isolated microscale compartments. Confinement of target analytes in droplets results in high local concentrations, high reaction rates, and high signal generation, leading to high analytical sensitivity (Kaushik et al., 2018). Droplet microfluidic systems combined with electrochemical detection methods have enabled the detection and identification of bacterial pathogens, viruses, fungi, nucleic acids, proteins, toxins, and various disease-associated biomarkers. Electrochemical methods have many advantages: they are fast, offer low detection limits, can be miniaturized, and are portable. Droplet-based systems also enable efficient screening and multiplexed detection, allowing multiple targets to be analysed simultaneously on a single platform. There has been a recent advancement in the use of droplet bioelectrochemical devices in antimicrobial susceptibility testing, pathogen identification, cancer biomarker analysis, and infectious disease diagnostics. The ability to precisely control droplet manipulation, sensitive electrochemical transduction, and automated data processing has the potential to further improve the performance of pathogen and biomarker detection systems, thereby advancing the next-generation of diagnostics for use in healthcare and environmental applications (Campuzano et al., 2017; Garg et al., 2022). Figure 6 shows general applications of droplet microfluidics in bioelectrochemical processes.

6 Integration of artificial intelligence and automation

As droplet microfluidics is becoming a vast field, experimental and theoretical data have rapidly accumulated, enabling the integration of droplet microfluidics with artificial intelligence (AI), machine learning (ML), and automatic control. The power of droplet microfluidic platforms for efficient experimentation, single-cell analysis, and complex biochemical investigations aligns with the fact that the amount of generated data continues to grow and become increasingly sophisticated, which often makes traditional analytical methods underperform. These innovative computational tools are incredibly powerful and, by harnessing AI, can interpret data, identify patterns, build predictive models and make autonomous decision-making to enhance the efficiency and reliability of microfluidic systems. In parallel, droplet microfluidics has become a highly complex technology platform capable of executing complex experimental workflows with minimal human involvement. AI, machine learning, robotics and microfluidic technology are helping to create intelligent systems which can help speed up discovery, optimise experimental conditions and monitor processes in real time, across energy, biomedical and bioelectrochemical applications (Del Giudice, 2026).

AI and ML are increasingly being used within microfluidics to deal with the massive amount of data obtained from droplet operations. There are five levels of functional application of AI/ML in microfluidics: image analysis, signal processing, predictive modeling, process optimization, and autonomous control. The significance of such a division lies in the fact that the current research mainly uses ML for analysis and predictions rather than fully autonomous droplet control. Some recent review articles refer to the combination of AI/ML with microfluidics as intelligent microfluidics, where ML could assist in biosensors’ signals decoding and microfluidic processes (Zheng et al., 2021). AI-supported image analysis is now one of the most developed methods. Deep neural networks could perform droplet detection, occupancy detection, morphology quantification and classification of cellular phenotypes by microscopy images. Thus, Vanhoucke et al. (2024) have developed a ResNet-50 model for label-free cell-containing droplets classification with >90% classification accuracy (Vanhoucke et al., 2024).

Signal processing using ML is another application which is especially interesting when dealing with electrochemical and biosensing systems. In addition to taking only one parameter (current, potential, impedance) into account, ML could help to analyze multi-dimensional features from cyclic voltammetry (CV), differential pulse voltammetry (DPV), square-wave voltammetry (SWV), amperometric and EIS measurements in order to classify analytes or physiological conditions. Recently developed methods based on the integration of ML, biosensors and microfluidics proved the capability of this approach. Predictive modeling and process optimization are two applications that integrate ML even further. The machine learning models may correlate flow rates, fluid characteristics, channel geometry and dimensionless parameters with droplet diameter, generation rate and flow regime. Recently developed data-driven framework assessed 11 prediction tasks for droplet-microfluidic systems and reported about 5-fold and 7-fold improvements in mean absolute errors for the prediction of droplet diameter and generation rate correspondingly, along with over 4% improvement in flow regime classification compared to earlier approach. However, the reliability of such models is still depending on training data (Sun et al., 2023).

The next level involves closed-loop control in which sensor or imaging data are provided on a continuous basis to an ML controller that tunes the flow rate, pressure, voltage or other control parameters. Multistate droplet control has been shown using AI-enabled digital microfluidics, suggesting the movement from data-driven to manipulation of droplets. Nonetheless, completely autonomous systems still seem at an early stage relative to image analysis and prediction. Nevertheless, certain limitations are still hindering implementation in practice. An ML model requires adequate training data; variability in imaging conditions, channel geometry, surface chemistry, fluid physics and fabrication tolerances result in device-to-device domain shift. High internal accuracy does not guarantee generality to different devices or operating conditions. As such, model validation should involve independent datasets and ideally external validation through experiment. Other issues to consider include uncertainty quantification, interpretability, reproducibility of pre-processing and hyperparameters, drift due to long term operation and the computational overhead required for real-time inference. Physics informed ML, transfer learning, standard datasets, uncertainty aware prediction and explainable AI can be useful in overcoming such limitations. Thus, AI should be viewed not simply as a tool for automating droplet image analysis, but as a potential framework connecting measurement → prediction → optimization → feedback control → autonomous operation (Samari et al., 2025; Barnes et al., 2023).

6.1 AI-assisted droplet analysis

AI has become a powerful tool for improving droplet analysis by interpreting complex data from microfluidic assays quickly and automatically. Manual image analysis and data processing for traditional droplet characterisation can be time-consuming and labour-intensive, and are prone to user-dependent variability. However, these limitations can be overcome by using AI-based methods, which utilise advanced computational algorithms capable of identifying, tracking, and characterising droplets in real-time with increased accuracy (Vanhoucke et al., 2024). Automated droplet detection, droplet size measurement, droplet shape analysis, occupancy sensing, and droplet behavioural tracking are increasingly used in machine vision and deep learning techniques. These methods allow the analysis of thousands of droplets in a single shot with high accuracy and repeatability. In the biological sector, AI-based image analysis aids in detecting and tracking encapsulated cells, as well as quantifying biochemical reactions within single droplets. Moreover, AI can help optimise droplet generation parameters, continuously monitor system performance, and dynamically adapt operational parameters to ensure stability and uniformity. These capabilities improve the analytical throughput and reliability of droplet microfluidic systems and make droplet analysis with AI an essential tool for next-generation, intelligent microfluidic platforms (Gardner et al., 2022; Gelado et al., 2023).

6.2 Machine learning for signal processing

As the signals produced by droplet microfluidics become more complex, machine learning is becoming a more valuable tool in processing and interpreting the signals. Often, data from biosensors, electrochemical analysis, optical detection, and bioelectrochemical monitoring together constitute multidimensional data with subtle patterns and relationships that are difficult to discern with traditional analysis methods. These datasets offer the potential to be analysed and utilised effectively using machine learning algorithms (Park et al., 2024). Signal classification, feature extraction, noise reduction, anomaly detection and predictive modelling are applications to which supervised and unsupervised learning techniques have been applied. In electrochemical and biosensing applications, machine learning algorithms can be used to discriminate between similar analytes, increase sensitivity of the detection system, and even recognize minute differences in signal characteristics for diagnostic purposes. Likewise, analysis of droplets with optical and imaging techniques can be enhanced by advanced pattern recognition techniques which are able to detect complex biological and chemical phenomena. Machine learning can also be used to optimize the parameters of the experiments, so that researchers can predict the behavior of the system and make it more efficient. With the growing power of computers, machine learning is projected to become increasingly relevant to data-to-information transformation of raw microfluidic data into scientific and diagnostic information (Park et al., 2024; Srikanth et al., 2021).

6.3 Automated high-throughput screening

One of the most important benefits of droplet microfluidics is that it can facilitate the effective screening and evaluation of thousands to millions of independent reactions in highly controlled microscale compartments in a short amount of time. These capabilities have been further bolstered by the incorporation of automation technologies, which have reduced manual workload, increased experimental reproducibility and sped up experimental workflows. Complex workflows such as droplet generation, reagent dispensing, mixing, incubation, sorting, detection and data acquisition can be performed with high precision and repeatability by automated droplet microfluidic platforms (Ott et al., 2026). Fully integrated screening systems can operate continuously, with programmable microfluidic architectures, automated imaging platforms, and real-time feedback mechanisms. These technologies are especially relevant for drug discovery, catalyst screening, enzyme engineering, synthetic biology, biomarker identification, and the development of energy materials. Automated workflows, along with artificial intelligence, optimize performance by allowing the system to adapt to new experiments based on the analysis of the collected data and predictions, dynamically adjusting system parameters as they are monitored. This smart screening technology saves a lot of time and resources in the experiments, and heightens the odds of discovering the optimal conditions and candidates. As a result, the combination of droplet microfluidics and automation/artificial intelligence (AI) is predicted to be an integral component in future high throughput research, personalized medicine, advanced manufacturing, and sustainable energy innovation (Ott et al., 2026; Sesen and Whyte, 2020).

7 Advantages and challenges

The new breakthrough technology of droplet microfluidics has tremendous potential to outperform traditional macroscale systems in many chemical, biological, electrochemical and energy-related applications. Increased control over the handling of small amounts of fluid leads to better control of reaction manipulations, increased mass transfer, high throughput processing and efficient use of reagents and samples. These have made the development of sophisticated analytical platforms possible for biosensing, diagnostics, material synthesis and bioelectrochemical studies. In spite of these benefits, there are still some technical and practical challenges that hinder the wider adoption and commercialization of droplet microfluidic technologies. The difficulties with deployment on a large scale involve device fabrication, the complexity of operation, device size and scalability, standardization, and integration into existing industrial procedures. It is therefore critical to have a good understanding of its strengths and weaknesses in order to inform the future development of the technology and a rapid translation from the research lab to market (Shang et al., 2017). Figure 7 includes the various advantages and challenges of droplet microfluidics in the energy and bioelectrochemical applications.

7.1 Miniaturization and reduced reagent consumption

The key advantage of droplet microfluidics technology is the ability to conduct complicated chemical and biological processes in small volumes. Droplet microfluidics enables reactions to occur in the picolitre to microliter droplets, which makes sample, reagents, catalysts and biological material consumptions minimal. This will not only lower operation costs, but also make it possible to conduct experiments on substances that would be unobtainable or expensive in a traditional lab setting. The reduction of volumes of the entire process increases analytical efficiency through reduction of diffusion distances and increases the ratio of surface to volume, and therefore enhances heat and mass transfer characteristics. The features mentioned above provide fast reaction rates, quick analyses, and increased efficiency of the processes conducted. Because of the reduced size of droplet microfluidic devices, it becomes possible to integrate these devices into portable equipment, and develop point-of-care diagnostics, wearable sensors, and field-portable analyzers. Moreover, conducting many parallel reactions in a small volume provides an increase of throughput of experimental researches, when reaction conditions are controlled accurately. Thus, miniaturization and less reagents consumption are still the key issues in the growing usage of droplet microfluidics technology (Ma et al., 2024).

7.2 Sensitivity and multiplexing capability

The main advantage of droplet microfluidics is its ability to confine analytes at a microscale level, thereby providing exceptional analytical sensitivity. Localization of target molecules, cells, enzymes or nanoparticles in droplets leads to higher local concentrations and higher efficiency of interaction, which is reflected in higher signal generation and lower detection limits. These features are especially desirable when dealing with rare analytes, single-cell analysis, early detection of disease and trace-level environmental monitoring. Droplet microfluidic systems also have remarkable multiplexing capabilities, as well as an increased sensitivity. Single droplets can serve as discrete reaction chambers and contain different reagents, biological samples or experimental conditions, allowing thousands of parallel analyses to be performed. This is a very high level of multiplexing that is suitable for drug screening, enzyme engineering, pathogen identification, biomarker profiling, catalyst discovery and materials optimization. In addition, advanced detection technologies such as optical, electrochemical, and spectroscopic detection can be used to allow for simultaneous detection of multiple targets from a single platform. The high sensitivity and multiplexing potential have made droplet microfluidics one of the most promising techniques for high-throughput experiments and next-generation analytical systems (Ma et al., 2024; Yew et al., 2020).

7.3 Fabrication and scalability challenges

Even with remarkable achievements in technology, it has not been easy to manufacture droplet microfluidic devices at large scales. Several microfluidic platforms are fabricated through special techniques such as photolithography, soft lithography, micromachining, and microelectromechanical system (MEMS) fabrication processes which might be very complicated and necessitate sophisticated equipment, clean room and special personnel. This may lead to increased cost of production and limitation in accessibility especially when it comes to manufacturing at an industrial level. There are also the issues with material choice; the common materials used may lack mechanical robustness, chemical inertness, gas impermeability or long-term stability. The application of prototyping technologies such as soft lithography and 3-D printing has eased the process of making devices, but it is not an easy process to go from prototype devices to mass manufactured commercial products. Besides that, there may be a challenge in achieving consistency in droplets sizes, fluid content and performance of the devices due to variation in quality of fabrication and operating conditions (Bi et al., 2025; Lee et al., 2026). Another key restriction is scalability. While droplet microfluidics is well suited to conducting experiments at the microscale, the process optimization needed to scale up into a commercial production process can be significant. Developing strong manufacturing strategies that retain the benefits of microfluidic systems but deliver high throughput and economic viability continues to be a key research focus.

7.4 Standardization and commercialization barriers

In addition to the technical performance, standardized protocols, regulatory frameworks and manufacturing practices are essential for the successful commercialization of droplet microfluidic technologies. There is considerable variation in the range of devices, their architecture, their fabrication procedure, their operating conditions and their performance evaluation methods, among different research groups and applications. The absence of the standardisation makes comparing studies difficult and makes it harder to create universally agreed performance benchmarks. The challenge of regulatory approval is especially great for biomedical and diagnostic applications. Reliability, reproducibility, safety and analytical accuracy of the device are essential for use in a clinical setting and must be achieved by extensive validation studies. These conditions may take a long time and be costly to achieve, especially for new technologies that include advanced microfluidic structures and sensing elements. Moreover, sustained stability, quality control and usability need to be considered to ensure adoption by healthcare providers and end users (Bi et al., 2025; Yew et al., 2020).

Economic factors such as manufacturing expenses, market demand, intellectual property rights protection and integration with the existing technological infrastructure also affect the commercialisation activities. There are many prototypes that have shown considerable lab performance, but very few have made it to commercial products. The healthcare, energy, environmental monitoring, and industrial biotechnology sectors will greatly benefit from the utilization of droplet microfluidics, but the challenges of standardization, regulatory compliance, manufacturing scale and market acceptance will be important to overcome in order to realize the full potential of this technology. Ongoing research and development, industry involvement, regulatory authorization, and technology development will be key to addressing these challenges and speeding up the commercialization of next-generation droplet microfluidic platforms (Shang et al., 2017). Figure 7 indicates the advantages and current challenges associated with the droplet-based microfluidic system in energy and bioelectrochemical applications.

8 Recent advances and emerging trends

The advancement of droplet microfluidics has been facilitated through continued innovation in material sciences, manufacturing techniques, digital manufacturing, flexible electronics, and sustainable engineering. Over the last decade, there has been tremendous enhancement in the capabilities of droplet-based systems, which have subsequently found application in the fabrication of portable, wearable, eco-friendly, and very highly integrated analytical systems. These advancements have facilitated the design of next-generation microfluidic systems for improved access and functionality in different fields including energy conversion, bioelectrochemical sensing, diagnostics in healthcare, and environmental monitoring. Furthermore, the use of advanced manufacturing technologies, materials for substrate, and innovative sensor structures has been instrumental in transforming droplet microfluidics from mere laboratory demonstration into commercial products. The field of droplet microfluidics has developed quite quickly and several emerging trends will determine its future trajectory and applications in diverse scientific and technological domains (Silva-Neto et al., 2022; Park et al., 2025).

8.1 3D printing and flexible microfluidics

Three-dimensional (3D) printing has become a game-changer for microfluidic device fabrication due to the high level of design flexibility, the ability to quickly produce prototypes, and the cost savings it provides. By using 3D printing, complex microfluidic structures can be directly fabricated with less processing step than conventional microfabrication techniques, which typically need cleanroom facilities and complicated lithographic processes. This ability has shortened the device development process and enabled the manufacture of customized microfluidic devices designed for particular applications (Lingadharini et al., 2025; Padash et al., 2020). Hu et al. (2025) developed a 3D printed microfluidic fuel cell for enhancement of energy harvesting with innovative multichannel geometry (Hu et al., 2025). With the rapid development of such droplet microfluidic architecture, recent advances in the fabrication of sophisticated designs with integrated channels, mixers, valves, reservoirs, and sensing are now possible, using additive manufacturing technologies. Being able to quickly change the design of the devices and to create complex three-dimensional geometries has opened up new possibilities for optimizing the transport of fluids, the manipulation of droplets, and the analytical performance. Simultaneously, the flexible and stretchable microfluidic device is being developed, resulting in new opportunities for wearable and implantable applications. Microfluidic systems can be flexible and conform to curved surfaces and dynamic biological environments such as elastomers, polymers, hydrogels, and conductive composites. The marriage of 3D printing and flexible materials is therefore paving the way for the next-generation of microfluidic platforms for use in personalized healthcare, wearable biosensing, soft robotics, and portable energy systems (Lingadharini et al., 2025; Anshori et al., 2024).

8.2 Paper-based and wearable systems

Paper-based microfluidic devices have received a great deal of interest as a cost-effective, eco-friendly alternative to the conventional microfluidic devices. These systems use the capillary properties of porous paper substrates to move fluid around the device, thus eliminating the need for external pumps and complex fluid control systems, which often add to the complexity of device operation and increase manufacturing costs. Due to the ease of fabrication, disposability, portability, and compatibility with various analytical methods, paper-based microfluidics is especially appealing for resource-limited environments and point-of-care use (Silva-Neto et al., 2022). Paper-based platforms have been combined with droplet microfluidics to create simple, yet powerful analytical devices for biosensing, environmental monitoring, food safety assessment and clinical diagnostics. At the same time, interest in continuous health monitoring and personalized medicine has led to the development of wearable microfluidic systems, which are also an emerging research field. These devices can be used to continuously sample and process physiologic fluids like sweats, saliva, tears, and interstitial fluids. By embedding electrochemical sensors, wireless communication components, and flexible electronics into wearable microfluidic devices, continuous monitoring of biomarkers, metabolites, electrolytes, and physiological parameters can be achieved. These innovations are likely to make a major contribution to preventive healthcare, disease management and the monitoring of patients from afar in future healthcare systems (Silva-Neto et al., 2022; Zhang et al., 2026).

In paper-based microfluidics, the process of liquid transport driven by capillary forces is dictated by the balance between capillary pressure, wetting properties, porous network configuration and viscous effects. In an idealized model, the imbibition process obeys the Lucas-Washburn equation, where the penetration distance increases with the square root of time, and this process is favoured by high surface tension, high pore radius and high wettability, while liquid viscosity hinders it. But real papers have an intricate porous network with variable sizes of interconnected pores, hence it is more appropriate to use Darcy-like models, involving permeability, porosity and tortuosity to predict the flow. Thus, the flow rate of liquids is influenced not only by the properties of the liquid itself but also by the average pore size, pore-size distribution, porosity, tortuosity, paper thickness and wettability of the surface. High interconnected pores lower the hydraulic resistance and increase permeability, and tortuosity enhances the effective path of liquid transport. These variables play a vital role in the design of paper-based enzymatic fuel cells due to capillary flow being responsible for supplying glucose and oxygen to the bioelectrode (Ye et al., 2023).

Experimentally, it has been proved that management of capillary flow could lead to significant enhancement in the efficiency of biofuel cells. In a glucose/O₂ fuel cell using paper substrates as an anodic/cathodic enzyme matrix operating at 5 mM glucose and pH 7.4, a capillary flow in the range 0.22 ± 0.01 μL s^-1 to 2.68 ± 0.30 μL s^-1 was obtained using different absorbent papers. The increased flow caused an increase in the convective mass transport that increased anode and cathode current densities by 91% and 50%, respectively, and a 56% increase in the total generated power. Likewise, by varying the texture of paper channels, it was found that increasing the average size of pores caused an increase in the electrolyte flow rate as well as the performance of the fuel cell, with an open circuit voltage (OCV) of 0.86 V and maximum power density of 7.10 mW cm^-2. Therefore, the porous substrate is an active fluidic component of the fuel cell, not just a mechanical one (Ye et al., 2023; del Torno-de Román et al., 2018).

8.3 Sustainable and green microfluidics

With the ever-growing awareness of environmental sustainability around the world, much research has been focused on the creation of sustainable and environmentally friendly microfluidic technologies. The conventional microfluidic preparation techniques are typically synthetic polymer-based and involve high-energy methods and non-renewable resource materials, potentially causing environmental problems in the preparation and disposal. Therefore, researchers have begun to investigate green alternatives that will minimize the impact on the environment, but still have a functional device (Ge et al., 2026). The materials used, renewable resources, recyclable substrates and the fabrication processes are all sustainable microfluidic approaches. In recent years, natural polymers, cellulose based materials, bio plastics and bio-derived composites are found to be promising alternatives for the fabrication of microfluidic devices with eco-friendly nature. Furthermore, optimization of reagent use, waste production and energy use during the device manufacturing and use are underway. The inherent attributes of droplet microfluidics also enable it to support sustainability goals, such as conducting microscale reactions that consume substantially less chemicals and biological materials than do traditional laboratory processes. As a result, the incorporation of green chemistry principles with microfluidic technologies will be a major factor in the evolution of sustainable analytical, biomedical and energy-related systems are anticipated (Brito‐Pereira et al., 2022; Lingadharini et al., 2025).

8.4 Hybrid electrochemical platforms

Combining several analytical and sensing modalities in a single microfluidic platform has become a strong trend in the development of droplet microfluidics. The hybrid electrochemical platforms integrate electrochemical sensing with other technologies for optical detection, spectroscopy, microfluidics, nanotechnology, artificial intelligence and wireless communication systems to provide superior analytical capabilities and multifunctionality. The advantage of these integrated systems is that they combine the best aspects of the various techniques and balance out the disadvantage of each technique used for sensing (Ottevaere et al., 2025). The benefits of electrochemical detection are especially significant for hybrid platforms, where high sensitivity, rapid response, low power consumption and miniaturized device compatibility are significant. Recent advances in the use of nanostructured materials, microelectrode arrays and sophisticated signal-processing algorithms have further enhanced the analytical capabilities of electrochemical microfluidic systems. In recent years, hybrid platforms have been created for a variety of applications, such as pathogen detection, detection of biomarkers, environmental monitoring, antimicrobial susceptibility testing, and bioelectrochemical investigations. The ability to acquire real-time data, communicate wirelessly, and make decisions using artificial intelligence is making intelligent analytical systems more autonomous and remotely monitored. In the years to come, as the technologies continue to converge, hybrid electrochemical platforms are likely to be at the heart of future diagnostic, environmental and energy applications, with unprecedented levels of sensitivity, automation and operational versatility (Li et al., 2026; Poorahong et al., 2016).

9 Future perspectives

The impressive developments made in droplet microfluidics in the last 20 years have made it one of the most promising technologies to be used in diagnostic, bioelectrochemistry, materials synthesis, and energy system applications. While there have been significant improvements in device design, fabrication, automation and integration of sensing, there are still many opportunities for additional technological progress and implementation. Future research should aim to make the devices more robust, scalable, more automated, more interoperable and deal with manufacturing, standardization and regulatory issues. The integration of droplet microfluidics with AI, next-generation materials, digital health and renewable energy systems is expected to drive the creation of intelligent, autonomous platforms to solve new scientific, industrial and societal needs. With the ongoing development of the field, droplet microfluidics is likely to move from a research-based technology to a common and broadly adopted tool in the fields of healthcare, environmental monitoring, industrial biotechnology and sustainable energy.

9.1 Clinical and industrial translation

One of the key objectives for the future in droplet microfluidics is to transfer this technology from the laboratory to clinical and industrial use. While a lot of systems have been developed and demonstrated to exhibit great analytical capability, very few of them have reached a commercial scale. The following is required for further development of this area of research and practice, the user should ensure that the devices have better reliability, reproducibility, availability and manufacturability. This is done through the standardization of manufacturing process, quality control and regulations so that their performance characteristics are consistent regardless of the operating conditions. From the clinical point of view, droplet microfluidics provides huge prospects for the diagnosis, monitoring, therapeutic testing and precision medicine. One of the areas of development in the upcoming years will be creation of all-in-one systems that will not require much human interaction and will provide the same precision as the lab experiments do. The same concerns various industrial applications in drug development, biotechnology, chemical synthesis, environmental monitoring and advanced material synthesis (Zhang et al., 2023).

9.2 Smart integrated lab-on-a-chip systems

Droplet microfluidics is becoming increasingly important with the emergence of intelligent integrated lab-on-a-chip devices that can perform complex workflows in an automated and integrated system. Advances in microfabrication, embedded electronics, biosensing, wireless communication and artificial intelligence technologies are making it possible to design highly complex systems which can integrate functions such as sample preparation, fluid handling, biochemical assays, data processing and result reporting into one platform. The next-generation lab-on-a-chip platforms would need to integrate multiple sensing techniques such as electrochemical, optical and biological to provide multiplexed analysis. Moreover, the use of AI technologies would further enhance the functionality of the device by making the system fully autonomous, adaptive optimization of processes, data analytics and decision-making capabilities in real-time. Connectivity with cloud and internet-of-things (IoT) technologies can help to create interconnected network of analyzers which can be utilized for healthcare or environmental monitoring applications or process controls in industries. Lab-on-a-chip platforms will certainly play an important part in the future ecosystems of diagnostics and analytics as integration and miniaturization continues (Kumar et al., 2022).

9.3 Opportunities in personalized healthcare and renewable energy

The future use of droplet microfluidic technology holds a lot of potential regarding applications in the realms of personalized medicine and renewable energy. Within medicine, as the trend toward personalizing diagnosis and treatment increases, a need emerges for analytical technologies capable of providing a rapid evaluation of biological data related to an individual patient. Among the key advantages of the droplet microfluidics in personalized medicine are the possibility to analyze a large number of cells, to perform a single cell analysis, biomarkers profiling, and drug response tests using an extremely low volume of samples. The future platforms will be capable of performing the real-time monitoring of the disease progression, therapy efficacy, and physiological reactions. On the other hand, the transition to sustainable energy production worldwide gives rise to novel possibilities in the realm of energy-related research and innovation through droplet microfluidics. Namely, the ability to control the reaction conditions inside the microdroplets can be applied for rapid screening of catalysts, optimization of electrochemical reactions, and synthesis of advanced materials for energy generation and storage. Potential developments in the future might extend into energy systems such as fuel cells, batteries and super-capacitors, hydrogen generation techniques, and bioelectrochemical energy generation. In addition, the combination of AI and automation with the technology of droplet microfluidics is likely to accelerate the discovery of the next-generation of materials required for the development of renewable energy systems. Hence, within the coming decade or so, droplet microfluidics is likely to emerge as an increasingly critical tool in addressing healthcare and sustainability challenges (Modestino et al., 2016; Jiang, 2022).

10 Conclusion

The field of droplet microfluidics possesses significant potential as an advanced tool for multiplex bioassays. However, moving beyond proof-of-principle demonstrations is constrained by the absence of standardized procedures regarding fabrication, droplet formation, surface phenomena, detection and assay standardization. Therefore, future research efforts should emphasize the development of standardized procedures, benchmarks and reference standards that would improve reproducibility across platforms. The creation of robust electrochemical electrodes operating under defined fluidic, thermal and electric conditions will yield closed-loop devices, and hence reduce inter-user variability. Afterwards, self-driving AI-assisted experimental procedures should be created to enable adaptability, real-time decision-making without losing transparency and applicability of models. In addition, research effort should be put into resource management, recycling and economy of such technology.

In general, droplet microfluidics is a promising and quickly developing platform that has a wide range of possibilities for the future for scientific research, industrial processes, and society. This innovative technology that combines precise fluid handling, advanced sensing, automation, and high throughput experimentation into miniaturized systems makes it a vital technology for the future of personalized medicine, renewable energy, environmental sustainability, and smart analytical systems. The future of droplet microfluidics is likely to be even more exciting as further research and technological developments are expected to make the technology more widely available and applicable to a number of the 21th century’s most pressing global challenges.

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Footnotes

Edited by: Sumit Kumar Mehta, SRM University AP, India

Reviewed by: Giridhar Raveendar, Indian Institute of Technology Guwahati, India

Prateechee Padma Behera, Indian Institute of Technology Bombay, India