Abstract

As the human population surges exponentially, the global appetite for critical metals is bound to expand. The rate of mining is inevitably going to increase due to depletion of high grade ores increasing stripping ratios for important commodities such as copper, gold, silver, etc. In 2020, more than 800 million tonnes of mine tailings and waste rock were generated equating to $2.4 billion in annual reclamation costs. 

Microbial fuel cells (MFCs) have emerged as a promising technology for remediation of acid rock drainage (ARD). MFCs generate electrons from organic material through biological processes which can then be used to reduce dissolved metals into deposits on an electrode. In the past years several researchers have demonstrated recovery of heavy metals, such as arsenic, copper, cadmium, selenium, silver, and gold, in MFC-based technologies. Challenges in MFC technology deployment arise from the complexity and kinetics of the underlying physical processes such as electrochemistry, hydrogeochemistry, and biochemical phenomena. As such, scale up of MFCs with faster recovery rates has to be accompanied with developments rooted in MFC design, analysis of ion transport and fundamental understanding of processes occurring inside the MFC. Such an understanding can require a large amount of time and resources to achieve, but can be accelerated through numerical modelling, machine learning, and rapid prototyping. 

Scaling MFCs that can be deployed to neutralise ARD and recover the valuable metals therein, can be approached by considering a simplified system using only a single specie model and a synthetic ARD bearing copper and iron. Our experiments were carried out in flow and batch reactors with a focus on understanding how current production impacted ion transport and performance of the MFCs. We explored several design parameters to increase metal recovery such as reactor design, materials, and flow rates. This bore consequences on ARD treatment that not only originated from the hydrogeochemistry itself but also from bacterial population dynamics at the anode side.

The convolution of these effects present challenges to modelling, analysis, and design of MFC systems which can be addressed through iterative design, rapid prototyping, and numerical simulations. Numerical simulations aided us in predicting reliable, long-term performance of our designs by allowing us to understand current distribution and evolution in the MFC system.