Insights into microbial community in microbial fuel cells simultaneously treating sulfide and nitrate under external resistance

Machine Learning in Bioelectrocatalysis

At present, the global energy crisis and environmental pollution coexist, and the demand for sustainable clean energy has been highly concerned. Bioelectrocatalysis that combines the benefits of biocatalysis and electrocatalysis produces high-value chemicals, clean biofuel, and biodegradable new materials. It has been applied in biosensors, biofuel cells, and bioelectrosynthesis. However, there are certain flaws in the application process of bioelectrocatalysis, such as low accuracy/efficiency, poor stability, and limited experimental conditions. These issues can possibly be solved using machine learning (ML) in recent reports although the combination of them is still not mature. To summarize the progress of ML in bioelectrocatalysis, this paper first introduces the modeling process of ML, then focuses on the reports of ML in bioelectrocatalysis, and ultimately makes a summary and outlook about current issues and future directions. It is believed that there is plenty of scope for this interdisciplinary research direction.

Condition optimization of iron-air fuel cell to treat phosphate-containing wastewater regarding sustainable development

Increasing use of phosphorus products and excessive exploitation of phosphorus resources become two major problems in perspective of phosphorus sustainable development. Phosphorus recovery is the shortcut to solve this dilemma. Combining electrochemistry, an iron-air fuel cell was adopted to recover phosphate and electricity from phosphate-containing wastewater in our previous studies. The present study focused on investigating the effects of catholyte/anolyte conductivity, external resistance, and anolyte pH on the performance of iron-air fuel cell, and obtaining the optimized conditions. Furthermore, the electrochemical methods of phosphate recovery were compared and assessed, and it is concluded that iron-air fuel cell has great potential for energy recovery. The phosphate removal efficiencies and vivianite yield roughly positively correlated with the catholyte conductivity and the anolyte pH, but negatively correlated with the external resistance and the anolyte conductivity. The electricity generation roughly positively correlated with the catholyte conductivity and anolyte conductivity, but showed limitations in the test range of anolyte pH and external resistance. To pursue high phosphate removal efficiencies and vivianite yield, the catholyte conductivity, external resistance, anolyte pH and anolyte conductivity were suggested to be 35 g-NaCl/L, 10 Ω, 8 and 0 g-NaCl/L. While if electricity generation was the primary goal, these parameters should be 35 g-NaCl/L, 220 Ω, 5 and 70 g-NaCl/L. The optimized conditions will help to improve the phosphate removal efficiency, vivianite yield and electricity generation, and to promote the development of iron-air fuel cell technology.

Iron cobalt-doped carbon nanofibers anode to simultaneously boost bioelectrocatalysis and direct electron transfer in microbial fuel cells: Characterization, performance, and mechanism

A self-supporting electrode (FeCo-MOF/CNFs) combining iron cobalt bimetallic metal-organic frameworks (FeCo-MOFs) with carbon nanofibers (CNFs) was applied as the anode of a microbial fuel cell (MFC). The introduction of FeCo-MOFs enhanced graphitization degree and electrical conductivity, which endowed FeCo-MOF/CNFs with excellent electrocatalytic performance and good biocompatibility. The hierarchical porous structure of FeCo-MOF/CNFs provided abundant attachment sites for electroactive bacteria (EAB) and facilitated rapid electron transfer. The MFC equipped with FeCo-MOF/CNFs anode (FeCo/CNFs-MFC) exhibited considerable power generation output (maximum power density: 5.3 ± 0.2 W/m², coulombic efficiency: 54 ± 4 %). In addition, FeCo/CNFs-MFC achieved a direct electron transfer (DET) catalytic current density of 0.63 A/m². FeCo-MOF/CNFs could simultaneously enhance the bioelectrocatalysis activity and promote the DET process of EAB, which provided an effective way to improve the sluggish extracellular electron transport process of the MFC anode.

Temporal changes of microbial community structure and nitrogen cycling processes during the aerobic degradation of phenanthrene

Phenanthrene (PHE) is frequently detected in worldwide soils. But it is still not clear that how the microbial community succession happens and the nitrogen-cycling processes alter during PHE degradation. In this study, the temporal changes of soil microbial community composition and nitrogen-cycling processes during the biodegradation of PHE (12 μg g^-1) were explored. The results showed that the biodegradation of PHE followed the second-order kinetics with a half-life of 7 days. QPCR results demonstrated that the bacteria numbers increased by 67.1%-194.7% with PHE degradation, whereas, no significant change was observed in fungi numbers. Thus, high-throughput sequencing based on 16 S rRNA was conducted and showed that the abundances of Methylotenera, Comamonadaceae, and Nocardioides involved in PHE degradation and denitrification were significantly increased, while those of nitrogen-metabolism-related genera such as Nitrososphaeraceae, Nitrospira, Gemmatimonadacea were decreased in PHE-treated soil. Co-occurrence network analysis suggested that more complex interrelations were constructed, and Proteobacteria instead of Acidobacteriota formed intimate associations with other microbes in responding to PHE exposure. Additionally, the abundances of nifH and narG were significantly up-regulated in PHE-treated soil, while that of amoA especially AOAamoA was down-regulated. Finally, correlation analysis found several potential microbes (Methylotenera, Comamonadaceae, and Agromyces) that could couple PHE degradation and nitrogen transformation. This study confirmed that PHE could alter microbial community structure, change the native bacterial network, and disturb nitrogen-cycling processes.