As of today, reducing the anthropogenic release of greenhouse gases might be considered as humankind’s most pressing challenge. Moving away from fossil fuels to renewable energy technologies is an essential step, but will not suffice. The chemical industry is responsible for a significant 6.3% of all CO2 emissions, thus fossil-free chemicals production is also required. To that end, carbon capture and utilization (CCU) offers a way to reduce emissions in industrial processes, while converting captured CO2 into commodity and specialty chemicals. Under the umbrella of CCU technologies, microbial electrosynthesis (MES) offers a sustainable solution with minimal water usage and the capacity to increase the value of electrical energy produced from renewable sources.

The ability of microorganisms to accept and utilize electrons from an electrode to catalyze the reduction of CO2 is the basis of MES processes. Whilst significant progress on understanding its fundamentals has been achieved, performance improvements have been modest. To reach industrial viability, a major breakthrough is needed. Unraveling multi-scale interactions between microbial, electrochemical and engineering parameters within MES systems will allow for the rational design of scalable bioreactors. Still, it remains widely unknown what is limiting current setups. The work presented in this thesis aims to identify, understand, and tackle major key process parameters, allowing for a step-by-step design approach to develop scalable MES bioreactors.

How microorganisms adapt to changing operational parameters and different reactor environments was investigated in Chapter 2. A general framework for modeling microbial kinetics within MES reactors was developed, and results showed that CO2 availability may be a limiting factor in existing systems. An insufficient mass transfer capability led to partially limited biomass growth under reported operational conditions, either because of a low gas partial pressure or an inefficient gas delivery strategy. The dynamic reactor-scale model also revealed that in biofilm-driven reactors, a continuous operational mode markedly improved microbial growth and potentially led to denser biofilms and higher current densities. Simulations indicated distinct correlations between operational process conditions and critical performance indicators (e.g., productivity), underscoring existing process limitations and paving the way for future system optimization.

A major knowledge gap in MES is that biomass-specific rates such as microbial growth rates had not been experimentally elucidated and were thus unknown to date. In Chapter 3, a method using nitrogen balances and optical density to determine the amount of microorganisms in biofilm and in suspension at any given time was developed. This was necessary to allow further complex computational attempts, since biomass concentration was one of the major unmeasured variables within biofilm-based MES processes. Measured growth rates during the colonization stage ranged from 0.12 to 0.16 days-1, values in accordance with the ones obtained in previous mathematical simulations. Interestingly, results showed that biomass-specific production rates were relatively low (0.37 molC molX-1 day-1) when compared to syngas and chain elongation studies (up to 10 molC molX-1 day-1). Thus, this comparative analysis highlighted that there is room to significantly improve metabolic rates in MES.

After gaining insight on what major factors limit MES performance, a novel directedflow- through bioelectrochemical reactor (DFBR) with a serpentine flow-pattern entirely filled with a 3D carbon-based electrode was developed in Chapter 4. The elimination of free-flowing liquid in the cathode chamber allowed the DFBR design to substantially increase mass transfer as well as carbon and hydrogen utilization efficiencies. Results demonstrated a 3-fold higher volumetric current density (-28 ± 7 mA cm-3cathode) and productivity (43 ± 24 kgC m-3cathode day-1) than previously reported in biofilm-based MES studies. Most notably, volumetric productivities obtained were now comparable to lab-scale syngas fermentation, a technology that has been successfully scaled up to an industrial level. These findings serve as a milestone in developing MES and emphasize key design parameters for efficient bioelectrochemical CO2 reduction. Furthermore, results obtained with the novel DFBR design proved that a knowledge-driven step-by step approach allows for successful MES reactor development.

Collectively, this dissertation shows that it is possible to unravel the main limitations in currently used MES reactors. The subsequent utilization of such knowledge to design scalable reactors able to achieve industrially relevant performance is also demonstrated. Nonetheless, new challenges are sure to arise while further developing MES as a technology. Extensive research, accounting for a multiscale and multidisciplinary approach is therefore a must in order to bring MES to industrial production.
@en

Carbon-based products are essential to society, yet producing them from fossil fuels is unsustainable. Microorganisms have the ability to take up electrons from solid electrodes and convert carbon dioxide (CO₂) to valuable carbon-based chemicals. However, higher productivities and energy efficiencies are needed to reach a viability that can make the technology transformative. Here, we show how a biofilm-based microbial porous cathode in a directed flow-through electrochemical system can continuously reduce CO₂ to even-chain C2–C6 carboxylic acids over 248 days. We demonstrate a threefold higher biofilm concentration, volumetric current density, and productivity compared with the state of the art. Most notably, the volumetric productivity (VP) resembles those achieved in laboratory-scale and industrial syngas (CO-H₂-CO₂) fermentation and chain elongation fermentation. This work highlights key design parameters for efficient electricity-driven microbial CO₂ reduction. There is need and room to improve the rates of electrode colonization and microbe-specific kinetics to scale up the technology.

@en

Microbial electrochemical technologies (METs) employ microorganisms utilizing solid-state electrodes as either electron sink or electron source, such as in microbial electrosynthesis (MES). METs reaction rate is traditionally normalized to the electrode dimensions or to the electrolyte volume, but should also be normalized to biomass amount present in the system at any given time. In biofilm-based systems, a major challenge is to determine the biomass amount in a non-destructive manner, especially in systems operated in continuous mode and using 3D electrodes. We developed a simple method using a nitrogen balance and optical density to determine the amount of microorganisms in biofilm and in suspension at any given time. For four MES reactors converting CO₂ to carboxylates, >99% of the biomass was present as biofilm after 69 days of reactor operation. After a lag phase, the biomass-specific growth rate had increased to 0.12–0.16 days⁻¹. After 100 days of operation, growth became insignificant. Biomass-specific production rates of carboxylates varied between 0.08–0.37 mol_C mol_X⁻¹d⁻¹. Using biomass-specific rates, one can more effectively assess the performance of MES, identify its limitations, and compare it to other fermentation technologies.

@en

Up to now, computational modeling of microbial electrosynthesis (MES) has been underexplored, but is necessary to achieve breakthrough understanding of the process-limiting steps. Here, a general framework for modeling microbial kinetics in a MES reactor is presented. A thermodynamic approach is used to link microbial metabolism to the electrochemical reduction of an intracellular mediator, allowing to predict cellular growth and current consumption. The model accounts for CO₂ reduction to acetate, and further elongation to n-butyrate and n-caproate. Simulation results were compared with experimental data obtained from different sources and proved the model is able to successfully describe microbial kinetics (growth, chain elongation, and product inhibition) and reactor performance (current density, organics titer). The capacity of the model to simulate different system configurations is also shown. Model results suggest CO₂ dissolved concentration might be limiting existing MES systems, and highlight the importance of the delivery method utilized to supply it. Simulation results also indicate that for biofilm-driven reactors, continuous mode significantly enhances microbial growth and might allow denser biofilms to be formed and higher current densities to be achieved.

@en