From waste to resource: engineering microbial electrochemical technologies for a sustainable water-energy nexus

1 Introduction

The explosion in the global population, more people living in cities, and industrial progress have resulted in a huge increase in both waste and energy use. According to the World Bank, municipal solid waste will increase from 2.01 billion tons in 2016 to 3.40 billion tons by 2050, unless major actions are taken. Meanwhile, the worldwide demand for energy is rising, and most of it comes from fossil fuels, which are making greenhouse gas problems worse and speeding up climate change (Kaza et al., 2018). Traditional ways of managing waste, like filling landfills and burning rubbish (incineration), take up a lot of space and cause pollution to the environment through leachate, harmful gases, and a big carbon footprint (Mor and Ravindra, 2023). In addition, our reliance on non-renewable energy harms the goals of the Paris Agreement and puts the world’s ecosystems at risk. Since these crises are merging, we need to develop new, sustainable technologies that can take care of waste and make clean energy, supporting the shift to a circular economy. As a result, creating technology to recover resources from waste is gaining popularity, so that waste no longer harms the environment but becomes useful instead (Haar, 2024). Microbial electrochemical technologies (METs) use microorganisms that produce electricity and hydrogen to turn organic waste into useful products, making it a promising way to treat waste sustainably (Das et al., 2021).

As the need for sustainable energy from waste grows, microbial electrochemical technologies (METs) have come to the fore, connecting microbiology, electrochemistry, and environmental engineering. METs use electroactive microbes to turn organic waste into electricity, hydrogen, and methane, which are all valuable energy sources (Logan et al., 2019). In the early 20th century, the field started with microbial fuel cells (MFCs), but it has since grown to cover microbial electrolysis cells (MECs), microbial desalination cells (MDCs), and microbial electrosynthesis platforms for chemicals. They rely on the metabolic activities of microbes to move electrons to or from electrodes, which converts the energy in organic materials directly into utilizable forms (Schröder et al., 2015).

The development of METs is due to a better understanding of electron transfer in microbes and advancements in creating materials like high-surface-area electrodes, superior catalysts, and membranes. Their ability to be used in many ways, their environmental benefits, and their potential expansion make METs the leaders in new waste-to-energy technologies, used for wastewater treatment, treating industrial waste, using agricultural waste, and cleaning up contaminated sites (Grover and Doyle, 2024). Integrating METs with other renewable technologies, such as anaerobic digestion and solar systems, provides a means to develop hybrid platforms that result in recovering more resources and emitting less carbon. Regardless of the significant progress on a small scale, more work is needed in areas like low energy production, keeping the process stable, being financially viable, and expanding the technology to fully benefit from METs in the worldwide energy and waste industries (AlQattan et al., 2018).

This review critically examines the latest advancements, challenges, and future trends in microbial electrochemical technologies (METs) for waste-to-energy. It explores key concepts, recent technological progress, and performance in municipal, industrial, and agricultural waste streams, with a focus on reactor designs, electrode improvements, and microbial community engineering. The review highlights issues such as low energy recovery, electrode fouling, scalability limits, and high costs, while addressing the economic, regulatory, and technological hurdles to commercialization. It concludes with insights on how METs contribute to sustainable development, a circular economy, and climate change mitigation, offering valuable perspectives for researchers, engineers, and policymakers.

2 Fundamentals of microbial electrochemical technologies

Microbial electrochemical technologies depend on electroactive microorganisms to turn organic waste into different forms of energy by transferring electrons between the microbes and solid electrodes. It happens either directly with the help of cytochromes and nanowires or through redox mediators secreted by the microorganisms (Schröder et al., 2015). The basic structure of a MET is an anode, a cathode, and an external circuit, usually with a membrane between them. Microbes at the anode oxidize organic substances, which results in the release of electrons and protons. Electrons flow through the outside circuit, creating current, and protons reach the cathode to finish the redox reaction (Kalathil et al., 2018). Depending on the setup, METs can create energy in the form of electricity (MFCs), hydrogen (MECs), clean water (MDCs), or chemicals (MES). An important role in METs performance belongs to the electrode’s materials (conductivity, size of the surface, and biocompatibility), the microbes present, the design of the reactor, and how it is run. Efficiency in the system has gone up thanks to nanostructured electrodes, engineered communities of microorganisms, and better reactor designs. So, problems such as low power density, biofilm instability, and high costs of materials are still present, pointing out the need for more progress to make fully practical applications possible (Khan R. et al., 2024).

2.1 Principles of microbial electrochemical reactions

In METs, bacteria that transfer electrons are used to help the exchange of electrons with solid-state electrodes (Lovley, 2012). Using these systems, microbes change organic or inorganic substances and deliver the extra electrons, either directly or indirectly, to an anode, linking microbial processes with electrochemistry to support sustainable energy use from waste. If the system is set up differently, it can create electricity, turn water into hydrogen, or allow the creation of chemicals (Logan et al., 2019).

Microbial species and the design of the system determine the method of electron transfer. Direct electron transfer uses outer-membrane cytochromes and conductive pili (nanowires), whereas mediated electron transfer involves adding or producing soluble redox substances (Rabaey and Rozendal, 2010). In most METs systems, microorganisms oxidize substances at the anode, which causes the release of electrons and protons. Electrons move through the external circuit toward the cathode to generate electricity, and protons move through the electrolyte to react with them at the cathode. Microbial fuel cells (MFCs) use oxygen to reduce water, microbial electrolysis cells (MECs) produce hydrogen, and microbial electrosynthesis systems (MES) uses carbon dioxide (Christodoulou et al., 2017). How efficiently microbes react in electrochemical reactions depends on their electron carriers’ redox potential, how easily ions move through electrodes, the features of the electrode surface, and the presence of proper electron acceptors. Improving how these interactions happen helps electron transfer happen faster, saves energy, and boosts the system’s performance (Kumar et al., 2017).

2.2 Key components of METs systems

A standard microbial electrochemical technology (MET) system includes the anode, cathode, membrane (sometimes present based on the design), and the microbial catalyst. The anode is where microbes oxidize substances and gather electrons from the process (Wang and Ren, 2013). Anode materials should be highly conductive, have a large surface area, be compatible with body tissues, and be chemically stable without oxygen. Usually, carbon cloth, carbon felt, graphite, and newer nanostructured composites are used because they support microbial clinging and efficient electron transfer (Ghasemi et al., 2013).

In microbial fuel cells (MFCs) and microbial electrolysis cells (MECs), the cathode supports reduction processes such as oxygen being converted into water or hydrogen being formed, finishing the electrical circuit. A strong catalytic activity, good chemical stability, and less overpotential loss are important features for cathode materials (Zhou et al., 2013). Platinum-based catalysts are very effective, yet because they are costly, researchers are now looking into metal oxides, conductive polymers, and carbon-based catalysts. Proton exchange membranes (PEMs) or similar separators are sometimes placed between the anode and cathode chambers in MET systems to help transfer protons and keep oxygen away from the anode, which improves the system’s efficiency. Still, in single-chamber MFCs, the membrane is often removed to cut costs and reduce internal resistance, though this affects how stable the system works (Santoro et al., 2017).

The electroactive community of microbes is key to how METs functions. Geobacter sulfurreducens, Shewanella oneidensis, and many types of mixed microbial communities grow in a biomass layer on the anode and carry out oxidation reactions. System efficiency depends on how well electrons can be transferred to the electrode by the catalyst (Engel et al., 2019). How these biofilms are structured, function, and withstand changes in the environment is what mainly decides how effective and tough MET systems are in the long run. Researchers are still focused on optimizing the main parts, materials, architecture, and biological catalysts so that electron transfer can be improved, the system can be scaled up, expenses are cut, and practical larger use can be made possible (Dufour et al., 2010).

2.3 Microbial communities involved in electron transfer

Proper function and efficiency of microbial electrochemical technologies (METs) rely on electroactive microbial communities. Exoelectrogenic bacteria in these communities can send electrons outside their cells to contact solid electrodes (Kumar et al., 2017). Electron transfer processes necessary for recovering energy in MET systems have been well studied in the major groups Geobacter, Shewanella, and Pseudomonas. There are many ways that microorganisms carry out electron transport. Most Geobacter species transfer electrons to electrodes using conductive pili and outer-membrane cytochromes and build up thick, conductive biofilms. Unlike the other species, Shewanella can perform electron transfer directly or with the help of flavins, which deliver electrons to the anode (Hu et al., 2021). Pseudomonas and other types of bacteria assist by moving electrons outside of their cells or by breaking down tough parts of waste, which raises the overall activity of bioelectrochemical systems. The stability and effectiveness of MET rely a lot on how various microbial species work together within mixed communities (Ivase et al., 2020). When complex waste is used in real systems, the competition between microbes, their synergies, and shifts in the community can influence how well and how long electron transfer occurs (Ishii et al., 2014). Often, fermentative and hydrolytic bacteria help break down complicated organic matter into products that exoelectrogens can use. Researchers are still working on finding ways to enhance the mix of microbes by using selective enrichment, controlling the environment, or bioaugmentation. To improve METs systems, we need to study how species interact, the structure of biofilms, metabolic pathways, and how the systems respond to different environmental factors (Thompson et al., 2005).

2.4 Major types of METs

Microbial Electrochemical Technologies (METs) include many systems that rely on the work of electroactive microorganisms to create electrical energy, produce hydrogen, or develop useful chemicals. They make use of the natural tendency of some microbes to move electrons between themselves and solid electrodes. With many different MET configurations, they can be used for energy, waste processing, carbon capture, and recovering resources (Acampora et al., 2025). This section investigates the main types of MET systems, what they do, and how they are used.

2.4.1 Microbial fuel cells (MFCs)

Microbial fuel cells (MFCs) are the METs setup that has been examined and developed the most. Microorganisms in MFCs break down organic matter (e.g., wastewater or organic waste) at the anode, producing electrons that go through an external circuit to the cathode, making electricity. Electroactive bacteria in MFCs take in organic substances and oxidize them to produce both electrons and protons. Electrons move from the anode to the cathode through the external circuit, and there, they react with oxygen, while other reactions may happen (Garbini et al., 2023). These systems have been examined a lot for wastewater treatment, covering municipal, industrial, and agricultural sources. They help produce energy and clean the air from pollutants, which makes them excellent for waste-to-energy use. They are applied in remote sensing, biosensors, and also for providing electricity to small devices where the grid is not available (Rani et al., 2023).

2.4.2 Microbial electrolysis cells (MECs)

Unlike MFCs, MECs work with an external voltage to allow microorganisms to convert substances whose oxidation is not spontaneous under standard conditions, such as acetate oxidation coupled to proton reduction, which carries a positive standard Gibbs free energy change and therefore does not proceed without an externally applied potential, into useful chemicals. Producing clean energy from organic matter using MECs is mainly done by making hydrogen gas. The extra voltage is provided to overcome the barrier for catalyzing reactions, for example, hydrogen evolution, where electrons and protons coming from the anode and cathode join to make hydrogen gas (Rozendal et al., 2006). MECs are valued for their role in producing biohydrogen, which meets the rising need for clean energy. They produce hydrogen sustainably and treat organic waste at the same time. Bioenergy systems using microbial electrochemistry have been tested using wastewater and agricultural residues, where they produce hydrogen and help clean up the waste. MECs can make biofuels and cut down on carbon emissions while generating hydrogen compared to conventional electrolytic methods (Li et al., 2018).

2.4.3 Microbial desalination cells (MDCs)

Microbial desalination cells (MDCs) use the reactions of microbes to remove salt from water and produce energy at the same time. Between the anode and the cathode in an MDC, a desalination chamber is placed, and membranes separate it. The operation of the system makes ions in saline water cross the membrane, which desalinates the water while releasing electrical energy at the anode using microbes (Cao et al., 2009). MDCs are helpful in places where there is little freshwater and plentiful saline water, such as in coastal and arid regions. Combining desalination with power generation in MDCs means they can help meet the needs for freshwater and energy with a single technology. Because they have been used to remove salt from brackish and seawater, these systems are very important in regions that are facing both drought and a growing population (Ghaffour et al., 2015).

2.4.4 Microbial electrosynthesis systems (MESs)

With microbial electrosynthesis systems (MESs), microbes at the cathode of the system use electrons to transform carbon dioxide (CO₂) or other substances into useful products such as acetate, methane, or alcohols. They provide a new way to use CO₂, changing it into biofuels and chemicals with electricity from renewable sources. MESs may help in stopping climate change by decreasing the amount of CO₂ in the atmosphere (Nevin et al., 2010). MESs is under development to make biofuels and chemicals such as methane, ethanol, and acetate from carbon dioxide. It supplies a clean, eco-friendly solution to the use of fossil fuels and petrochemicals. MESs might be used for clean energy, to store carbon emissions, and to make use of waste carbon dioxide in products (Rath et al., 2021).

2.4.5 Microbial reverse electrodialysis cells (MRECs)

Microbial reverse electrodialysis cells (MRECs) use microbes to work with reverse electrodialysis (RED) to generate energy using salinity gradients. In this system, seawater is placed in the anode chamber and freshwater is put in the cathode chamber, and these are separated by ion-exchange membranes. Because the salinity is different between the solutions, ions cross the membranes to produce electricity. The electrons from the anode move through the external circuit when microbial oxidation happens, closing the energy cycle (Pandit et al., 2023). MRECs play a big role where both salt water and organic waste are found close to the coasts. These systems may be applied to sustainable energy by generating electricity and desalinating water at the same time. Using MRECs is becoming popular for generating energy and treating water in coastline areas, which helps solve energy and water scarcity problems around the world (Harte, 2021).

2.4.6 Microbial bioelectrochemical system for nitrogen removal (MBES-N)

Microbial bioelectrochemical systems for nitrogen removal (MBES-N) rely on electroactive organisms to help eliminate nitrogen compounds like ammonium or nitrate from wastewater. Organic matter is oxidized by microbes at the anode, and the cathode is used to handle processes like nitrate reduction or various nitrogen transformations. MBES-N systems can take advantage of favorable conditions to remove nitrogen, which improves how wastewater is treated and helps reduce eutrophication in water bodies (de Andrade Correia, 2020). MBES-N systems are expected to enhance wastewater treatment by efficiently removing nitrogen compounds that harm water quality. Because of these systems, wastewater treatment plants can treat more municipal and industrial wastewater, which decreases nutrient pollution, makes wastewater management more sustainable, and reduces the impact of nitrogen runoff on nature (Patel, 2022).

2.4.7 Microbial electrochemical systems for resource recovery (MERS)

In microbial electrochemical systems for resource recovery (MERS), both valuable resources and electricity are produced from wastewater. Microorganisms oxidize organic substances at the anode in MERS, and important resources are obtained at the cathode or by reactions on its surface. It handles major environmental problems like nutrient pollution and resource loss, and produces energy too (Bajracharya et al., 2016). MERS has been researched to remove phosphorus, nitrogen, and metals such as copper and zinc from wastewater, since these are important materials in industry. They make it possible to manage nutrients, create energy, and recover materials, which helps build a circular economy (Wu et al., 2019). Figure 1 depicts that METs operate through the metabolic activity of electroactive bacteria, such as Geobacter species, which oxidize organic matter at the anode to release electrons and protons. These electrons travel through an external circuit to the cathode, while protons migrate through an exchange membrane, facilitating diverse energy-recovery and treatment processes tailored by the specific reactor configuration.

This comparative summary consolidates the product streams, typical performance ranges, and principal trade-offs of the MET configurations described above, synthesised from Fan et al. (2021), Garbini et al. (2023), Rozendal et al. (2006), Cao et al. (2009), Nevin et al. (2010), Pandit et al. (2023), de Andrade Correia (2020), Bajracharya et al. (2016), and the hydrogen-recovery and COD-removal benchmarks discussed in Sections 4 and 5.

3 Substrate for waste-to-energy conversion in METs

The efficiency, practicality, and scalability of microbial electrochemical technologies (METs) rely heavily on choosing the right substrates. Microorganisms need substrates to act as electron donors, and the way these substrates are biodegradable, how much organic load they possess, and if they contain inhibitors will affect the system’s performance (Marandola et al., 2024). Many different types of waste streams have been studied for use in METs, which helps achieve goals in resource recovery and environmental cleanup. Most METs use organic substrates, and municipal and industrial wastewater, food waste, and agricultural residues are their main options. They are rich in pollutants, so they give us energy and help clean up the environment at the same time. Though it needs pretreatment, lignocellulosic biomass can be used as a source of energy after its sugars are separated (Düring and Gäth, 2002). Hydrogen is produced in MECs using inorganic substrates, and inorganic substrates are also used in systems that reduce nitrate and sulfate in wastewater. Because of these substrates, METs can perform a wide variety of electron transfer reactions. Substrates, including paper mill waste, landfill leachate, and waste from the dairy industry, are useful in METs (Kadier et al., 2014). Since these wastes are rich in organic matter, they are ideal for use in microbial fuel cells (MFCs) and MECs to produce energy and manage waste. Also, the wastewater left by food processing companies is well suited to microbial oxidation, as it helps in handling pollution and generating energy (Munoz-Cupa et al., 2021). Gases, for example, CO₂ and methane, are used in MES with microorganisms to reduce them into acetate, methane, and alcohols, supporting both the removal of carbon from the air and the recovery of useful resources. Although these materials have great potential, there are some issues to solve, such as simplifying the substrates, keeping the community of microbes stable, and managing the amount of organic material put in (Rahimnejad, 2023).

3.1 Substrate selection criteria and a decision-making framework

Choosing among the substrate categories reviewed in this section is not simply a matter of availability; it requires weighing several criteria against one another, since no single waste stream is optimal across all dimensions. Four criteria recur most consistently across the literature discussed above: (i) organic strength and biodegradability, which determines the theoretical energy ceiling and the fraction of COD accessible to exoelectrogens without pretreatment (Pant et al., 2010); (ii) pretreatment burden, since recalcitrant lignocellulosic or high-solids streams (e.g., rice straw, animal manure slurry) require hydrolysis or fermentation steps that add cost and reduce net energy return (Galbe and Zacchi, 2012; Behera et al., 2014); (iii) inhibitor and toxicant load, which governs whether a waste stream (e.g., textile or pharmaceutical wastewater) can sustain a stable electroactive biofilm without bioaugmentation or dilution (Caracciolo et al., 2015; Mani et al., 2018); and (iv) feedstock consistency and seasonal availability, which affects whether a MET can be operated continuously or must be designed for batch or campaign-style processing (Sheets et al., 2015). Table 1 above and the discussion in Sections 3.1–3.9 indicate that substrates cluster into three practical tiers when these criteria are applied jointly. High-priority substrates combine high organic strength with low pretreatment burden and low toxicity, exemplified by dairy effluent and brewery wastewater (Werkneh et al., 2019; ElAidie and Khalifa, 2024), and are consistently associated with the highest reported energy recoveries. Medium-priority substrates offer high energy potential but require dedicated pretreatment or community adaptation, exemplified by lignocellulosic biomass and the organic fraction of municipal solid waste (Behera et al., 2014; Cesaro and Belgiorno, 2014). Lower-priority substrates present the greatest technical risk despite high value, exemplified by pharmaceutical and textile wastewaters, because inhibitory compounds necessitate specialised microbial consortia or dilution strategies that reduce volumetric efficiency (Caracciolo et al., 2015; Mani et al., 2018). This tiered view reframes substrate selection as an explicit trade-off exercise rather than a simple inventory of waste streams, and it is applied when appropriate throughout the substrate-specific discussion that follows.

TABLE 1. Comparative summary of the seven major METs Configurations.

3.2 Industrial wastewater

The high organic content and steady availability of industrial wastewater attract METs as good sources of energy. Effluents rich in biodegradable organics are produced by food and beverage processing, pulp and paper manufacturing, and chemical production industries, and these can be turned into electricity or useful chemicals (Singh, 2015). Microbial fuel cells (MFCs) and microbial electrolysis cells (MECs) have been shown to recover energy successfully from brewery wastewater, dairy effluents, and waste from the textile industry. But since not all industrial wastewaters have the same components and may contain toxins, proper preparation or a change in the microbial population is necessary for the process to perform consistently (Brunschweiger et al., 2020).

3.3 Agricultural and food wastes

Agriculture and food industries create a lot of waste, which can be used as cheap materials for METs. Carbohydrates, proteins, and lipids are usually found in high amounts in these wastes, which is good for microbes to use up (Pant et al., 2010). Examples of substances used in METs include fruit and vegetable leftovers, whey from dairy, and crop waste such as rice straw. The use of agricultural and food wastes is a challenge, as they are available only seasonally, contain high levels of solids, and need to be pretreated so microbes can better access them (Sheets et al., 2015).

3.4 Municipal solid waste and sewage

Organic matter from municipal solid waste (MSW) and sewage sludge can be given value through METs. Sewage-derived organics are promising since they are produced regularly and are relatively easy to decompose (Zheng et al., 2024). Studies have been carried out at pilot and field levels on MFCs, which treat wastewater while generating energy from sewage. Besides, VFAs can be produced from fermenting organic materials in MSW, and these can be used as a microbial electrochemical system’s substrate. Since MSW is mixed and may be contaminated, it leads to hard-to-handle operations that call for flexible and resilient systems (Gurjar and Behera, 2020).

3.5 Emerging substrate (e.g., pharmaceutical waste, lignocellulosic biomass)

New sources like pharmaceutical waste and lignocellulosic biomass give METs more uses. Pharmaceutical wastewater contains many organic compounds that can serve as electron donors for METs, although certain constituents are toxic to electroactive biofilms and recalcitrant to biodegradation (Vasić et al., 2023). It is possible to treat pharmaceutical residues and produce energy at the same time using microbes adapted to MFCs. Materials such as corn stover, wheat straw, and forestry waste, which are part of lignocellulosic biomass, are plentiful but are difficult to use. Lignocellulosic materials usually need to be pretreated with enzymes or acids before microbes can use the sugar in MET processes (Galbe and Zacchi, 2012).

3.6 Slaughterhouse and animal manures

Proteins, fats, and carbohydrates found in slaughterhouse waste and animal manure are valuable for the functioning of METs. These materials can be broken down by bacteria and have a great opportunity for recovering energy. Microbial fuel cells have been shown to work well with animal manure, especially cow and chicken waste, to produce electricity. One difficulty with using slaughterhouse waste and animal manure in METs is that they have high solids, so they may first need to be treated with fermentation or hydrolysis (Dahunsi, 2020).

3.7 Paper and pulp industry waste

Most of the organic waste from the paper and pulp industry comes from discarded lignocellulosic fibers and effluent with high chemical oxygen demand (COD). It is possible to make energy out of this waste through METs. MFCs are effective in treating paper mill wastewater, generating power, and cutting down on pollutants (Gopal et al., 2019). A main difficulty with waste from paper and pulp is that it contains chemicals that can reduce the activity of microbes. Applying bioaugmentation or certain microbial groups can help improve the working of wastewater treatment systems on these contaminants (Sumathi and Hung, 2004).

3.8 Landfill leachate

The decomposing organic waste in landfills produces landfill leachate, which contains many organic compounds and can be used for waste-to-energy conversion. Using MFCs, organic waste in leachate is changed into electricity, and at the same time, the environmental effects of releasing leachate are lowered (Kumar et al., 2023). Landfill leachate cannot be easily used as a substrate because its makeup can change greatly based on how old the landfill is and the types of waste it contains. In most cases, you have to pre-treat the waste or adapt the microbes to obtain the best results (Schiopu and Gavrilescu, 2010).

3.9 Organic waste from textile industries

The textile industry creates large amounts of waste that can harm the environment, such as dyes, chemicals, and solvents. Even so, organic pollutants may act as materials for METs to use. Microbial fuel cells are now used in the textile industry to treat its effluent, breaking down the complex materials and making electricity (Sivaram et al., 2019). The main issue with these chemicals is that they are toxic, so microbes may need to change or further treatment may be necessary to increase their cleaning ability. METs that use textile waste help treat the waste and recover energy, giving the textile industry a sustainable choice (Khandaker et al., 2022).

3.10 Gaseous substrate (Co₂, methane, volatile fatty acids)

Microbial electrosynthesis systems (MES) is now also using gaseous substrates such as CO₂, methane, and volatile fatty acids (VFAs). MESs use microorganisms at the cathode to convert CO₂ or methane to useful products like acetate or ethanol by using electricity. As a result of this process, carbon is captured and resources can be recovered, dealing with environmental issues caused by greenhouse gas emissions (Noori et al., 2021). Using VFAs as substrates allows the production of biofuels and chemicals from materials that would otherwise be waste. MES with gaseous substrates could greatly contribute to the circular economy and lessen CO₂ emissions (Vázquez-Fernández et al., 2022). To achieve sustainable waste-to-energy conversion, selecting appropriate feedstocks is critical, as visualized in the ‘Substrate Roadmap’ in Figure 2. This figure acts as a strategic taxonomy, mapping distinct conversion pathways from complex lignocellulosic polymers and gaseous CO₂ to high-value bio-chemicals and electricity, thereby validating the role of METs as the ‘Biochemical Conversion Engin’ in a closed-loop circular bioeconomy.

4 Recent technological advances

METs have become more effective, can be expanded to larger uses, and are more flexible due to recent advancements. Advances in materials, engineering, biology, and how these are combined are helping METs become ready for the market.

4.1 Electrode material innovations

The advancements in electrode quality have greatly supported MET. Now, nanomaterials, biocompatible coatings, and 3D shapes have replaced carbon cloth and graphite to increase how well electrodes conduct electricity, how much surface they cover, and whether or not they attract microbes (Chilakamarry et al., 2021). Carbon nanotubes, graphene, and metal-organic frameworks, which are nanostructured, have improved current densities due to their better ability to transport electrons (Khan Z. U. et al., 2024). Polymers and biofilms that are compatible with biology allow the microbes to attach and remain on surfaces for a long time. The presence of carbon foams and aerogels, which give more surface for bacteria, results in a larger effective reaction area and enhances the system’s performance (Berillo et al., 2021).

4.2 Reactor design improvements

There are now modern reactor systems that overcome the problems with older MET systems. The ability to stack MET units one after another produces more energy than just using one, and this arrangement gives industry added flexibility. Streamlining the process inside MFCs has resulted in increased voltage and power densities (Lund et al., 2015). Modern hoop house designs use flexible materials and allow air to flow, which helps the substrate, oxygen use, and upkeep. This means reducing both the price and the amount of space needed for MET installations, but keeping or raising their effectiveness (Thompson et al., 2012).

4.3 Microbial community engineering

Engineering communities of microbes is now popular for making systems more reliable and productive. The use of microbial consortia made up of microbes that complement each other helps in regulating electron flow and maintaining system stability. Experts are researching changing certain genes in electroactive bacteria to boost how much and how fast electrons are moved, what substances they can work with, and their tolerance to harmful chemicals (Ben Said and Or, 2017). Engineering the genomes of Geobacter and Shewanella makes them better at moving electrons out of the cell, which improves the efficiency of MET. In this manner, different methods can be used to change microbial actions based on the type of waste and how the facility is run (Hu et al., 2021).

4.4 Integration with other technologies

The use of METs has broadened because they are used together with other biotechnology tools. To give an example, when anaerobic digestion is used with METs, there is a better breakdown of organic matter, and the process produces electricity and biogas (De Mes et al., 2003). Doing experiments with photosynthetic microbes in photobioreactors helps to accomplish both carbon dioxide capture and biofuel production together (Jaiswal et al., 2023). Besides, using forward osmosis and microbial desalination cells, also possible to desalinate, treat water, and produce energy within the same process. They seek to ensure there are more resources retrieved, less waste is created, and MET becomes more successful financially (ElMekawy et al., 2014).

4.5 Nanotechnology in METs: new frontiers

Nanotechnology is making it possible to enhance both the materials and the results of microbial electrochemical technologies (METs). Carbon nanotubes, graphene oxide, gold nanoparticles, and metal-organic frameworks (MOFs) increase electrode conductivity, surface area, and how quickly electrons are transferred. Coatings also stop biofouling, which makes systems more dependable and long-lasting (Khan Z. U. et al., 2024). Carbon nanotubes and graphene have been shown to facilitate microbial attachment and electron movement when included in microbial fuel cells (MFCs) and microbial electrolysis cells (MECs), which leads to more efficient generation of current (Yazdi et al., 2016).

Using very small materials accelerates the way microbes metabolize and carry out reactions. Using quantum dots and metal-based nanoparticles is known to increase the amount of energy that microorganisms produce from organic material, since it increases EET and microbial activity. Using nanocatalysts in MES means that CO₂ and methane can be changed into acetate, which improves the efficiency of the process (Quraishi et al., 2021). Nanotechnology can be used to develop sensors that check voltage, pH, and microbial levels in real time. The use of sensors made from carbon nanotubes improves the way processes and systems are controlled. METs perform more efficiently and are produced with less effort after adding nanomaterials, which also reduces their cost for renewable energy and waste treatment (Luo and Stutzenberger, 2008). The rapid evolution of METs is driven by an interdisciplinary convergence of materials science and synthetic biology, as detailed in Figure 3. By integrating nanostructured electrodes with CRISPR-engineered microbial catalysts and hybrid reactor configurations, current research is effectively overcoming traditional bottlenecks in power density and operational stability, moving the technology closer to industrial-scale commercialization.

5 Performance metrics and evaluation

Assessing microbial electrochemical technologies (METs) accurately involves looking at their energy efficiency, what they can break down, what products they produce, and their effect on the environment. Using standard metrics is required to assess how systems match up, how they can be enhanced and if they are suitable for commercial use (Savla et al., 2021).

5.1 Power output and energy efficiency

Power output is a key factor in assessing performance, mainly for both microbial fuel cells (MFCs) and microbial electrolysis cells (MECs). Power density is commonly defined as watts per square meter or cubic meter (unit reactor volume) to show how much electrical energy is produced based on the system’s size (Scott, 2019). The power output is strongly affected by the characteristics of the electrodes, how fast microbes transfer electrons, the reactor’s setup, and its internal resistance. Recently, progress in using three-dimensional electrodes and highly conductive coatings has led to much higher power densities in batteries (Wang S. et al., 2023). The energy efficiency of a MET is measured by looking at the relationship between the electricity generated and the amount of chemical energy in the substrate, which is often reported as Coulombic efficiency (CE). CE is the measure of how many electrons from an oxidized substrate are converted into electricity. Though high CE values are good, it is not easy to achieve and maintain them in real waste situations because competing microbial processes like methanogenesis occur (Adams et al., 2018). The amount of hydrogen and how efficiently energy is used are both considered in assessing MECs. A cathodic hydrogen recovery exceeding 80% has been reported in single-chamber membrane-free MECs fed with acetate as the sole carbon source and operated at an applied voltage in the range of 0.6–1.0 V, conditions under which substrate limitation and methanogenic competition are minimised (Ndayisenga et al., 2023).

5.2 Waste removal efficiency

METs are important since they can both manage waste and generate usable energy. The effectiveness of removing waste is often reported as the percent drop in chemical oxygen demand (COD) or biological oxygen demand (BOD) of the inlet stream. When experiments are performed with synthetic or readily biodegradable wastewaters in a laboratory, COD removal rates of 80% or more are common (Nwaigwe and Enweremadu, 2015). Industrial and municipal wastewater that has a high number of stubborn substances generally results in poorer removal efficiency. The addition of enzymatic hydrolysis or co-metabolism is sometimes used to help bacteria break down the chemicals. Measuring COD reduction and power produced at the same time helps find out how well METs turn waste into energy. Such a metric is key to understanding if a system will survive for large-scale projects (Fagan et al., 2010).

5.3 Product yields (hydrogen, methane, chemicals)

Microbial Electrochemical Technology (METs) can additionally make bio-products such as hydrogen, methane and acetate, ethanol, and butyrate. Hydrogen gas is created at the cathode in a membrane electrode cell when a small voltage is added from outside (Blasco Gómez, 2020). Hydrogen production of 3.0 m³ H₂/m³ reactor/day has been observed when optimizing conditions and using simple substrates such as acetate. The process known as microbial electro-methanogenesis turns CO₂ and electrons into methane using special microbes at the cathode. This way, renewable natural gas can be produced, but it calls for close attention to the electrodes and the bacteria in the system (Pawar et al., 2022).

Specially designed systems called microbial electrosynthesis systems (MES) help bacteria produce valuable chemicals by reacting at the cathode using reductive metabolism. Some studies have pointed out that acetate, formate, and medium-chain carboxylates can be made directly from CO₂ and electricity, which could help capture and make use of carbon. These metrics are important for checking if different MET methods are technically and economically suitable, mainly for systems using solar energy to produce chemicals or fuels instead of producing electricity (Coridan et al., 2015).

5.4 Life cycle assessment and environmental footprint

In the laboratory, MET research mostly looks at output and waste burning, but when scaling for the real world, it is important to consider how such solutions impact nature. LCA methodologies allow for assessing the environmental effects of METs, looking at resources used, emissions given off, and the treatment of discarded materials. Studies so far have found that compared to conventional systems, METs release much less carbon and generate more valuable biochemicals or energy when electricity is recycled (Bueno et al., 2015). The environmental benefits are based mainly on the type of electrode used, the system design, and how stable it is. Some of the main things that influence METs’ environmental impact are the use of rare metals or synthetic nanomaterials which could result in higher environmental effects and more embodied energy if they are not sustainably harvested. Because MECs use external voltage, the type of electricity source (renewable or fossil) is very important for the overall environmental impact of these systems (Omer, 2009). Durability and stability of materials and microbes help extend the life of MET installations and reduce their environmental impact. Further LCA studies are intended to improve the effectiveness of impact categories (like eutrophication and freshwater use) and suggest better ways to scale MET processes in factories and cities (Milà i Canals et al., 2009). As summarized in Figure 4, the accurate evaluation of METs requires a balanced assessment of energy capture, waste degradation kinetics, and product yields. This multidimensional matrix identifies the critical trade-offs between high power output and Coulombic efficiency, while underscoring the necessity of life-cycle sustainability metrics to validate the technology’s role in a low-carbon wastewater infrastructure.

5.5 Benchmarking METs against conventional wastewater treatment technologies

The performance indicators discussed above are only meaningful when placed against the incumbent technologies that METs would need to displace or supplement. Table 2 compares the energy demand, organic removal, and resource-recovery potential of METs with activated sludge and anaerobic digestion, drawing on independently reported pilot- and full-scale data rather than laboratory best cases.

TABLE 2. Comparison of Different Waste Types Used in Microbial Electrochemical Technologies (METs).

This table summarizes various waste types utilized as substrates in METs systems, highlighting their key properties, energy generation potential, associated challenges, and corresponding references. It reflects the diversity of available feedstocks and emphasizes the importance of substrate selection and pretreatment strategies for optimizing MET performance.

These figures indicate that MFCs are, on a per-volume energy basis, generally competitive with or superior to activated sludge, primarily because they avoid the aeration demand that dominates conventional aerobic treatment; however, their absolute power densities remain one to two orders of magnitude below what would be required for METs to function as net energy exporters at full scale, and anaerobic digestion continues to outperform MFCs on energy recovered per unit of COD removed where a downstream digester is already in place. A land-footprint comparison could not be constructed from consistently reported units across the sources reviewed here and is flagged as a specific data gap rather than omitted silently; pilot-scale MET installations to date have generally been smaller than full activated sludge trains, but no standardised area-normalised metric (e.g., m2 per population equivalent) is yet reported across enough independent studies to support a quantitative comparison. A quantitative benchmarking of METs against conventional wastewater treatment technologies is presented in Table 3.

TABLE 3. Quantitative benchmarking of METs against conventional wastewater treatment technologies.

5.6 Reproducibility of reported performance values

A recurring limitation evident across Sections 4–5 is that power density, Coulombic efficiency, and product yield values vary considerably across studies that nominally test the same MET configuration and substrate class. This variability arises from at least four sources that are frequently under-reported: inoculum origin and pre-enrichment history, which determines the starting electroactive community composition (Singh and Kaushik, 2021); reactor geometry and electrode spacing, which governs internal resistance independently of electrode material (Singh and Kaushik, 2021; Madondo et al., 2023); the external resistance or applied potential at which power density is measured, since polarisation curves are sensitive to this choice; and whether reported values reflect peak instantaneous output or a time-averaged, steady-state condition. For example, MFC power densities reported across the literature span nearly four orders of magnitude depending on configuration, ranging from roughly 0.04 mW/m3 in tubular designs to over 6,000 mW/m3 in double-chamber systems (Gholamali Zadeh et al., 2024), a spread attributable more to these methodological and configurational differences than to genuine differences in the underlying technology. Cross-study comparison is further complicated by the absence of standardised testing protocols and reporting units, an issue also identified in Table 2 (Jafary et al., 2026). Improving reproducibility going forward will require the field to converge on standardised reporting practices, including polarisation-curve-derived rather than single-point power density, explicit hydraulic retention time and temperature reporting, and open deposition of raw electrochemical data alongside summary statistics, consistent with recommendations made elsewhere in this review for standardisation and benchmarking (Table 4).

TABLE 4. Recent Breakthroughs in Microbial Electrochemical Technologies (METs).

This table categorizes recent advancements in METs into material innovations, reactor design improvements, and microbial community engineering. It summarizes key breakthroughs, their impact on system performance, and supporting references, providing an overview of technological progress driving MET optimization and scalability.

6 Challenges in scaling-up and commercialization

Although microbial electrochemical technologies (METs) have proven successful in smaller-scale studies, it is still difficult for them to scale up to be used in large commercial projects. Overcoming these challenges is key to using METs properly in sustainable waste-to-energy and for the environment (Hsu et al., 2024). Challenges and potential solutions for MET commercialization are summarized in Table 5.

TABLE 5. Challenges, potential solutions for MET (commercialization).

6.1 Technical challenges

The lack of high-output power and products compared to traditional methods is one of the biggest hurdles to using METs more widely. Although new electrodes and designs have improved output levels, the power produced in operating plants is usually insufficient for industrial advantages. Internal resistance caused by electrode problems, a weak membrane, and slow electron transfer between microbes is still a major issue (O’driscoll & O’donnell, 2013). Maintaining the right conditions for growth, such as pH, temperature, and salinity, is more challenging in big systems, and this can lead to changes in how the reactors perform. Biofouling and the passivation of electrodes are significant technical obstacles. As time goes by, the buildup of inactive or non-conductive biofilms on electrodes can greatly decrease the efficiency and lifespan of the system (Bandaru et al., 2020). Polarity reversal, cleaning with brushes, or using antifouling coatings all introduce difficulties and expenses into the system. Being able to scale the reactors also requires that they are modular, reliable, and easy to maintain. Most current MET designs do not offer enough mechanical strength or flexibility in the hydraulic system for successful expansion in a variety of industries (Saleh et al., 2009).

6.2 Economic feasibility

Whether a technology can be successfully launched depends greatly on its economic viability. The main reason for the high capital cost of MET systems is that electrodes, membranes, and system components are all more expensive than those used in standard treatment. Since platinum-based cathodes are costly when used outside of the lab, scientists have looked for cheaper alternatives (Huang et al., 2021). Running costs for MECs tend to be more affordable than traditional aerated systems due to not needing outside aeration, but they sometimes cost more due to the need for regular electrode changes and an external power source. The revenue generated by METs through electricity, hydrogen, methane, or chemical production should be enough to cover their capital and operational costs (Balogun et al., 2024). However, the low overall energy anaerobic digestion and the changing quality of waste make it hard to predict and keep up steady economic results. Research suggests that including METs with other units, such as anaerobic digestion or resource recovery, in hybrid systems brings economic advantages by improving the variety of revenues and lowering the period it takes to recover costs (Beegle and Borole, 2018).

6.3 Environmental and regulatory issues

Environmental and regulatory issues, not just technical and economic aspects, play a part in deciding the chances of bringing METs to the market. Even though METs use less greenhouse gas and chemicals during the process, a full review of METs’ environmental footprint from production to final disposal should be done with life cycle analysis (LCA), which was suggested by Patil et al., in 2011 (Serafini et al., 2023). Using rare elements or advanced nanomaterials to build electrodes raises fears about the availability of these substances as well as the risk of toxicity, so it is important to research more sustainable materials. In addition, issues like electrode corrosion, the spread of pathogens, and safety during open procedures should be properly managed (Ferdiana et al., 2023). According to laws, MET products (including hydrogen, treated water, and recovered chemicals) are often categorized in several ways, which can lead to uncertainty in regulations and requirements for permitting and compliance. Neither standardization bodies nor policymakers have provided clear structures for accepting, regulating, and certifying MET-based systems. Wastewater rules in several regions are written mainly for older technologies, making it hard for METs to meet them; for instance, the US EPA’s National Pollutant Discharge Elimination System permitting framework and effluent guidelines were developed around conventional activated sludge and anaerobic digestion performance benchmarks and do not yet define discharge or resource-recovery classifications specific to bioelectrochemical output streams, while the EU’s Urban Wastewater Treatment Directive similarly lacks provisions that formally recognise electricity, hydrogen, or chemicals recovered via METs as regulated co-products rather than treatment by-products. Reducing requirements for approval and using incentives could make it easier for municipalities and industries to adopt MET technology (Moretto and Quong, 2022). As illustrated in Figure 5, the transition of METs from TRL 3 to TRL 7 is impeded by a significant ‘Scaling-Up Bottleneck’ involving technical, economic, and regulatory barriers. Current research suggests that the integration of Industry 4.0 solutions, such as AI-driven process control and Digital Twins, is essential to bridge this gap, allowing for the optimization of resource recovery revenue and the mitigation of high CAPEX constraints in industrial-scale installations.

6.4 Root causes underlying scaling and commercialisation barriers

The technical, economic, and regulatory barriers catalogued in Sections 6.1–6.3 and Table 4 share a small number of underlying root causes rather than being independent problems. First, most barriers trace back to the fundamental thermodynamic and kinetic limits of extracellular electron transfer (Lovley, 2012): exoelectrogenic respiration is a slower and lower-energy-yielding metabolic pathway than aerobic respiration, which places a ceiling on achievable power density regardless of electrode or reactor engineering, and explains why materials innovation (Table 2) has raised current densities incrementally rather than by orders of magnitude. Second, the absence of standardised testing protocols and reporting units, discussed in Section 5.6 above, is itself a root cause of the lack of standardisation and benchmarking listed in Table 4, since regulators and investors cannot compare competing MET designs on a common basis. Third, capital intensity is disproportionately driven by legacy reliance on precious-metal catalysts and ion-exchange membranes carried over from fuel-cell engineering rather than optimised for wastewater conditions; polymeric membranes alone have been estimated to account for approximately 40% of MFC fabrication capital cost, and platinum-group-metal-free cathode catalysts have been shown to deliver comparable performance at substantially lower cost (Santoro et al., 2018), indicating that this is a design-inheritance problem rather than an inherent limitation of bioelectrochemical systems. Fourth, regulatory uncertainty (Section 6.3) stems from METs not fitting cleanly into existing permitting categories built around either energy generation or waste treatment, rather than from any demonstrated safety or performance deficiency. Recognising these as root causes rather than as a flat list of independent challenges indicates that coordinated progress on protocol standardisation and non-precious-metal catalyst development would address several downstream barriers in Table 4 simultaneously.

6.5 Economic feasibility in developing countries

The economic case for METs differs substantially between high-income and developing-country contexts. In many low- and middle-income settings, the relevant comparison is not METs versus a fully aerated activated sludge plant, since a large share of wastewater in such settings receives minimal or no treatment at all: while approximately 52% of wastewater is treated globally, treatment rates fall to around 26% in lower-middle-income countries and to roughly 4%–8% in low-income countries (Jones et al., 2021). The counterfactual in these settings is therefore untreated discharge rather than an energy-intensive incumbent technology. This changes the economic calculus in favour of METs and related decentralised bioelectrochemical systems in several respects: lower grid-electricity reliability in many developing regions makes the low or negative net energy demand of MFCs (Table 2) more valuable than in grid-secure settings; the smaller capital base of municipal utilities in these contexts favours modular, incrementally scalable MET units over large centralised aerated infrastructure; and the co-benefit of nutrient and resource recovery (Section 6, MERS) can offset a portion of capital cost where fertiliser or metal inputs are otherwise imported. Against these advantages, developing-country deployment faces its own constraints, including limited local capacity for electrode and membrane manufacturing, which raises effective capital costs once import duties and shipping are included, and a shortage of the analytical infrastructure needed to operate and troubleshoot bioelectrochemical systems, a workforce-development gap rather than a technology gap. Pilot deployments in decentralised or rural sanitation contexts, of the kind reviewed by Rani et al. (2023) for agro-waste-to-energy applications, illustrate that METs are most economically defensible in developing-country settings as targeted, off-grid or semi-centralised solutions rather than as direct substitutes for large urban wastewater treatment plants.

6.6 Comparison with other emerging waste-to-energy technologies

METs are one of several competing waste-to-energy pathways, and their relative merit depends on the feedstock and product slate under consideration. Anaerobic digestion remains the more mature and generally higher energy-recovery pathway for high-solids, high-strength organic waste (Table 2; Beegle and Borole, 2018), and is likely to remain the incumbent choice wherever biogas end-use infrastructure already exists. Incineration and gasification offer higher volumetric energy recovery for dry, low-moisture waste fractions than any bioelectrochemical route, but at the cost of higher capital investment, emissions-control requirements, and unsuitability for dilute aqueous waste streams, which is precisely the niche METs are best positioned to fill (Foster et al., 2021). Compared with these alternatives, METs offer three distinctive advantages rather than a general performance superiority: they operate effectively on dilute aqueous streams (COD in the hundreds to low thousands of mg/L) that are energetically unfavourable for combustion-based routes; they can be configured for targeted product recovery (hydrogen via MEC, chemicals via MES, nutrients via MERS) rather than heat or electricity alone; and they avoid the flue-gas treatment burden associated with thermal waste-to-energy routes. The appropriate role for METs within a waste-to-energy portfolio is therefore as a complement to anaerobic digestion and thermal conversion for dilute or resource-recovery-oriented streams, rather than as a wholesale replacement for either.

6.7 The role of government subsidies and carbon credits

Because MET revenue from electricity, hydrogen, or chemical sales alone is currently insufficient to recover capital costs at most scales (Section 6.2), policy instruments that monetise the avoided-emissions and reduced-sludge benefits of METs are likely to be decisive for early commercialisation. Renewable energy credit schemes and feed-in tariffs, where extended to cover MFC- and MEC-generated electricity and hydrogen on the same basis as other distributed renewable sources, would directly improve project economics; Foster et al. (2021) identify inadequate tariff banding and the lack of government subsidies as concrete barriers that have already slowed anaerobic digestion uptake in an otherwise comparable bioenergy sector, and at present, most such schemes were not designed with bioelectrochemical systems in mind and require case-by-case interpretation, contributing to the regulatory uncertainty discussed in Section 6.3. Carbon credit mechanisms present a complementary opportunity, since METs reduce both direct greenhouse gas emissions associated with aeration-derived electricity demand and indirect emissions associated with sludge transport and disposal; life cycle assessments indicate, however, that such sustainability gains are contingent on improved energy yields and optimised materials (Jafary et al., 2026), and generating verifiable carbon credits requires standardised measurement, reporting, and verification protocols that, per Section 5.6, do not yet exist for MET performance data. Targeted capital subsidies or green-infrastructure grants for pilot and demonstration-scale installations, of the kind already used to de-risk early-stage renewable energy technologies, would address the specific problem that MET capital costs remain dominated by non-optimised, fuel-cell-derived materials (Section 6.4) until manufacturing scale is reached. Coordinated policy support along these three channels, tariff or credit access, carbon-market eligibility, and capital de-risking, is likely to be more consequential for MET commercialisation timelines than further incremental gains in laboratory-scale power density.

7 Future perspectives and research directions

Microbial electrochemical technologies should evolve to play a bigger role in environmental and energy applications by overcoming their drawbacks and finding new scientific and engineering directions. Future studies are planned that may move laboratory ME systems into fields where their impact is noticed, and they can provide commercial value (Kumar et al., 2018).

7.1 Designing high-performance microbial consortia

For METs to succeed in the future, engineers must create microbial communities that are reliable, strong, and efficient at transferring electrons. Although naturally enriched communities are effective, using artificial consortia gives more chances to control and design. Designing consortia to fit the waste type, the conditions in the system, and the electrodes used can boost the reliability and function of the system (Jia et al., 2016). Spotting key electroactive organisms and their interactions will become easier due to the use of techniques like metagenomics, metatranscriptomics, and single-cell analysis. Synthetic biology techniques and CRISPR editing can help make improved microbes that easily interact with their surroundings, handle a wide range of substances, and resist harsh environments (Yaashikaa et al., 2022).

7.2 Advanced bioelectrode

Researchers are still focusing a lot on making improved bioelectrodes for the future. New materials that enhance conductivity, increase surface area, are safe for the body, strong, and environmentally friendly are required. Newly developed composite materials with graphene, complex porous structures, and biodegradable conduction polymers are promising areas (Han et al., 2022). Using natural redox molecules or mimicking biomineralization could be other ways to boost communication between microbes and electrodes. In addition, research needs to improve the process of producing advanced electrodes on a large scale, so they can be successfully used in large METs systems (Schröder et al., 2015).

7.3 Integration with circular economy models

Future studies should make sure that METs are designed and tested within circular economic principles for optimization. METs are helpful for both turning waste into energy and for collecting resources, capturing carbon, recycling nutrients, and reclaiming water. If METs are used together with anaerobic digestion, photobioreactors, membrane bioreactors or algal cultivation, it maximizes resources and brings in high returns (Srivastava et al., 2025). Combining microbial fuel cells with microalgae reactors will allow us to deal with wastewater, produce power, sequester CO₂, and make biofuels. Additional work can build on lifecycle approaches and cost-benefit assessments to quantify what these integrated systems provide to the environment and economy when used in different ways (Kusmayadi et al., 2020).

7.4 Policy support and incentives

Modern technology is not enough to guarantee that METs will be successfully commercialized. To boost adoption, policies should be supportive, financial rewards should be offered, and regulations should be modernized. Regulatory authorities should accept METs as technologies that can be included in renewable energy credits, projects funded for creating green infrastructure, and programs for waste recycling. Clearly outlined rules for certifying systems and all benchmarks used during operation must be created to help reduce uncertainty for everyone. In addition, setting up large-scale METs in public utilities or industries can help convince others by serving as real examples (Wolsink, 2010).

7.5 Role of artificial intelligence (AI) and digital twin technologies in METs optimization

Artificial intelligence (AI), machine learning (ML), and digital twin frameworks play an important role in shaping the future of METs research. They can support constant monitoring, maintenance planning, and the best use of METs under various waste and work patterns. The use of machine learning in bioreactors allows for finding hidden connections between microbial communities, electricity, and the substances they consume, which is essential for increasing energy and waste recovery (Rojas et al., 2025). Virtual replicas called digital twins help predict issues, simulate different conditions, and show how design can be improved at a much lower cost than an experimental setup. Future projects should work on AI tools that unite biological, electrochemical, and environmental information to allow METs systems to operate smartly on their own (Mihai et al., 2022).

7.5.1 Machine learning algorithms applicable to METs optimisation

Several classes of algorithm have been applied to bioelectrochemical and closely related fermentation systems, each suited to different aspects of METs optimisation. Tree-based ensemble methods, including random forest, gradient boosting, XGBoost, and CatBoost, have been used to predict power density and COD removal from operational parameters such as Pt loading, membrane sulfonation degree, and cathode aeration rate (Abdollahfard et al., 2023), and are generally favoured for tabular METs datasets because they handle nonlinear interactions and are comparatively robust to the small sample sizes typical of laboratory and pilot studies. Support vector regression and Bayesian-optimised SVR models have been applied to MFC power output prediction with reported gains in accuracy over simpler regression baselines. Artificial neural networks and multilayer perceptrons capture more complex nonlinear relationships between multiple operating variables and system outputs but require larger training datasets than tree-based methods to avoid overfitting. Explainable AI techniques, particularly SHAP (Shapley Additive Explanations) analysis, have increasingly been layered onto these models to identify which operating parameters most strongly drive predicted performance; a recent benchmarking study of seven supervised algorithms (including 1D-CNN, gradient boosting, AdaBoost, and stacking regressors) applied to microbial electromethanogenesis found SHAP-based feature attribution essential for distinguishing genuine operational drivers from dataset-specific artefacts (Gadkari et al., 2025), addressing the interpretability requirement discussed below rather than treating the model purely as a black box.

7.5.2 A worked example: machine learning applied to METs optimisation

A concrete illustration of this approach is provided by Houmsi et al. (2025), who applied CatBoost, XGBoost, AdaBoost, and multiple linear regression models to predict power density in microbial fuel cells treating landfill leachate. Their MFCs achieved 62% chemical oxygen demand reduction and 78% nitrogen reduction, with an optimal power density of 283.38 mW/m2 and Coulombic efficiency of 24.98% identified at an ammonium-nitrogen concentration of 800 mg/L, COD of 1325 mg/L, pH 6.88, and a voltage of 528.59 mV. The CatBoost model achieved the highest predictive accuracy (R-squared of 0.999), substantially outperforming the multiple linear regression baseline, and the analysis identified COD concentration as the dominant driver of power density through a near-linear relationship. This example demonstrates the practical value machine learning offers over conventional one-factor-at-a-time experimentation: rather than requiring an exhaustive experimental sweep across ammonium, COD, and pH combinations, the trained model allows operators to identify near-optimal operating conditions computationally, reducing the number of physical trials required to tune a MET for a new feedstock. Complementary work applying multivariate principal component analysis and machine learning to link COD and pH with voltage, current density, power density, and Coulombic efficiency in wastewater-fed MFCs has reached similar conclusions regarding the dominant role of organic loading and pH in governing bioelectrochemical output.

7.5.3 Practical challenges: data scarcity and model interpretability

Despite this promise, two practical challenges limit the routine deployment of machine learning in MET operation. The first is data scarcity: individual laboratories typically generate datasets of tens to low hundreds of operating points per reactor configuration, which is small by machine learning standards and increases the risk of overfitting, particularly for high-capacity models such as deep neural networks. This is compounded by inconsistent reporting practices across the field (Section 5.6), which restricts the ability to pool datasets across independent studies to reach the sample sizes that more complex models require. The second challenge is interpretability. Ensemble and neural network models can achieve high predictive accuracy while offering limited mechanistic insight into why a given operating point performs well, which is a barrier to operator trust and to regulatory acceptance in contexts where process decisions must be justified. SHAP-based and other post hoc explainability methods partially address this by ranking feature importance, but they explain correlations captured by the model rather than establishing causal mechanisms, and their conclusions can be sensitive to the training data distribution, a limitation demonstrated when Gadkari et al. (2025) found that SHAP attributions for the same bioelectrochemical process shifted noticeably across algorithm families trained on the same dataset. Progress on both fronts will likely require community-level data-sharing initiatives, of the kind already recommended for reproducibility in Section 5.6, paired with hybrid modelling approaches that combine mechanistic bioelectrochemical models with data-driven correction terms rather than relying on purely data-driven models trained on scarce data.

7.5.4 Hardware and software requirements for digital twin implementation

Implementing a digital twin for MET operation requires infrastructure at three layers. At the sensing layer, continuous, low-drift instrumentation for voltage, current, pH, temperature, and, where feasible, COD or its optical proxies is required to supply the twin with real-time input; this is a nontrivial requirement given that many of the nanomaterial-based sensors discussed in Section 4.5 remain at laboratory demonstration stage rather than being available as ruggedised field instruments. At the data and connectivity layer, an industrial IoT stack (edge data logging, secure transmission, and a time-series database) is needed to capture and store the sensor stream at a resolution sufficient for model retraining. At the modelling and computation layer, the digital twin itself combines a calibrated mechanistic or hybrid model with the trained machine learning components described above, and requires either cloud-based or on-premises computing resources for model retraining as operating conditions drift; cloud deployment is more accessible for small utilities but raises data-sovereignty considerations for municipal operators, while on-premises deployment avoids this but requires dedicated IT capacity that many wastewater utilities, particularly in developing-country contexts (Section 6.5), do not currently maintain. These layered requirements mean that digital twin adoption is likely to proceed unevenly, with well-resourced utilities in high-income settings able to pilot full implementations while smaller or resource-constrained operators adopt simplified, single-parameter predictive tools first.

7.5.5 Cost-benefit trade-offs of AI-driven control: small-scale versus large-scale systems

The economic case for AI-driven control scales differently for small decentralised MET units than for large centralised installations. For small-scale or off-grid systems of the kind discussed in Section 6.5, the fixed cost of sensing infrastructure, connectivity, and computation is spread over a small treatment volume, making full digital twin implementation difficult to justify economically; the more realistic near-term application at this scale is a lightweight, pre-trained predictive model deployed on low-cost embedded hardware to recommend set-points without requiring continuous cloud connectivity or on-site retraining. For large, centralised MET installations, by contrast, the same fixed infrastructure cost is amortised across a much larger treated volume, and the operational savings from AI-optimised set-point control (reduced energy input to MECs, improved Coulombic efficiency, earlier fouling detection) are more likely to exceed the infrastructure investment within a reasonable payback period, consistent with the general capital-intensity pattern noted for other advanced materials and controls in Section 6.2. This asymmetry suggests that AI and digital twin adoption will likely follow a bifurcated pathway: simplified, low-infrastructure predictive tools for small and developing-country deployments, and full digital twin implementations concentrated at large, centralised installations where the fixed infrastructure cost can be justified by scale. Figure 6 shows that the transition of METs from laboratory settings to high-scale modular plants relies on four foundational research pillars. Innovations in synthetic biology allow for the engineering of specialized microbial consortia, while advancements in porous composite electrode materials significantly improve system performance and conductivity. To ensure long-term viability, METs are being integrated into circular economy systems, utilizing carbon-capture units and microalgae photobioreactors, and optimized through digital twin frameworks that provide predictive modeling and real-time control. This technological evolution is further bolstered by supportive policies and increased industrial investment.

8 Conclusion

METs represent a vital, multidisciplinary frontier at the intersection of microbiology, electrochemistry, and environmental nanochemistry, offering an eco-friendly paradigm for turning waste into clean energy. Over the past two decades, significant breakthroughs have advanced our understanding of extracellular electron transfer kinetics, molecular-scale interfaces, and nanostructured electrocatalysts. Despite these successes, industrial deployment remains constrained by scaling limitations, biofouling, high capital costs, and complex operational dynamics in real-world settings. Overcoming these bottlenecks requires the strategic integration of next-generation nanomaterials (such as quantum dots and 3D graphene composites), green-synthesized electrodes, designer microbial consortia, and comprehensive circular economy frameworks. Moving forward, research must prioritize cross-disciplinary collaboration spanning materials science, systems engineering, data science, and policy development. Future milestones should focus on engineering resilient electroactive biofilms, developing cost-effective and non-toxic nano-architectures, integrating METs with secondary clean energy systems, and deploying AI-driven digital twins for real-time operational optimization. Concurrently, establishing robust environmental risk assessment frameworks, supportive regulatory guidelines, and proactive public awareness campaigns will be essential for driving commercial adoption. Supported by targeted innovation and careful environmental governance, nano-enhanced METs are uniquely positioned to address the global water-energy nexus, mitigate climate change, and serve as a cornerstone of the future sustainable circular bioeconomy.

Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. During the preparation of this work, the author(s) used Gemini in order to assist with language refinement, improve clarity, and enhance the overall presentation of the manuscript. Additionally, AI was utilized to conceptualize and render high-resolution technical infographics (Figures 1–6) based on the review’s core themes. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

Edited by: Suresh Babu Naidu Krishna, Durban University of Technology, South Africa

Reviewed by: Nelson Oshogwue Etafo, Universidad Carolina, Mexico

Hanfeng Jiang, Nanjing University of Science and Technology, China