Fe-Rich Biomass-Derived Hierarchically Porous Capacitive Electrodes as Electron Repeaters to Boost Power Generation in Microbial Electrochemical Systems.

Authors

Yujie Zhu, Yuanyuan Li, Ning Wang, Yuan Wen, Dandan Liang, Weihua He, Yujie Feng

Published in

ACS applied materials & interfaces. Sep 09, 2026. Epub Sep 09, 2026.

Abstract

Microbial electrochemical systems (MESs) present a promising approach for simultaneous water treatment and electricity generation. However, their performance is constrained by limited chemical-to-electrical energy conversion efficiency. Anode materials are central to this conversion process. Here, a self-supporting dual-precursor-derived carbon anode with excellent mechanical strength was developed by combining iron-rich biomass-derived heteroatom self-doping and pyrolytic pore formation with the intrinsic pore-forming ability and high carbon yield of phenolic resin. The resulting high-capacitance anode integrates hierarchically porous, heteroatom-doped carbon scaffolds with a mechanically robust matrix. The high capacitance generated by the synergistic effect of the porous architecture and endogenous Fe/N heteroatoms from the biomass precursor functions as both an electron repeaters and a capacitive buffer to support high biocurrent generation. Electrode materials derived from Enteromorpha sp. (E-MPR) exhibit a maximum capacitance of 1.67 ± 0.004 F cm-2 and supported a biomass loading of 1873.7 ± 74.1 μg cm-2, compared with 324.3 ± 12.1 μg cm-2 on carbon felt. The electroactive biofilm was dominated by Geobacter (81%). The functionally coupled electrode design optimizes the structure-performance relationships among the electrode material, the electroactive biofilm, and overall system efficiency. Consequently, a breakthrough in power and current densities was achieved, with values reaching 6138 ± 118 mW m-2 and 22 ± 1.2 A m-2, respectively. This work provides a notable enhancement in MES performance, suggesting that the high-performance anode is a promising candidate for engineering-scale applications of MES.

PMID:
42710040
Bibliographic data and abstract were imported from PubMed on 09 Sep 2026.

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