Mathematical modelling of electron transfer modes in electroactive microorganisms

Abstract

Electroactive microorganisms (EAMs) are known to function in a variety of systems, and receive strong focus in scientific investigation; microbial fuel cells (MFCs) and microbial electrolysis cells (MECs) are two key fields utilising these microorganisms to date. Microbially influenced corrosion (MIC) and the conduction of filamentous bacteria in ocean sediments also make use of external electrical currents to enable growth in what otherwise may be an abiotic environment. With the discovery of more of these systems and a growing understanding of their relevance over the past couple of decades, research into them has been steadily increasing. Electrochemical techniques such as cyclic voltammetry and impedance analysis have been used to gain a greater understanding of the system. However, mechanistic model-based analysis has lagged behind, with the fundamentals and consequences of electron transfer still not fully understood. Mechanistic investigation is vital for the progression and furthering of related research, and for highlighting the interactions occurring within EAMs, as many processes occur at a level that cannot be resolved by experimental systems. While a number of models have described extracellular electron transfer, in particular, for MFCs, none have analysed short-range electrontransfer mechanisms on a comparative basis. This thesis uses common finite element and electrochemical diffusive-reactive modelling techniques to investigate electroactive organisms in highly diverse environments. One such system is a filamentous sulfide-oxidising system in ocean sediment. Filamentous bacteria grow between sulfide-rich and oxygen-rich regions, transferring electrons between self determined anodic and cathodic zones. Splitting of the metabolic pathway between partners allows growth to be determined thermodynamically rather than empirically, with bacteria releasing or consuming electrons depending upon the available substrate. This modelling approach determined that the bacteria, while electroactive, cannot grow with the rates seen experimentally, and highlighted that the current conceptual picture is incomplete. A similar approach is used to investigate microbially influenced corrosion, showing that direct electrical uptake greatly exacerbates corrosion when compared to a purely chemical system, due to the shifting of the electrical potential of the metal and the subsequent increase in electrochemical rates. This model of corrosion rates in carbon steel showed the variability with changing environmental conditions and bacterial activity, ranging from as little as 0.05 mm/yr to a very significant 1.5 mm/yr with highly aggressive biofilms. Finally, these methods are combined and expanded to provide a model of a bioanode inclusive of all currently known mechanisms, providing realistic, experimentally comparable results of cyclic voltammetry and trumpet plots. From this, insight into the conductive mechanistic regime provides evidence that our current understanding of nanowire-electrode interactions may need examining, as the resistance provided by electrode-nanowire contact produces results that are outof-line with experimental observations. Ultimately, this demonstrates the applicability of the modelling platforms described and lays the foundation for advanced modelling in parallel with industrial or lab-scale systems.