Work

Cellulose-Derived Cu-N-C Hybrid for Potential-Regulated CO2-to-CH4 Electroreduction

Year: 2026
Type: preprint
Abstract: Electrochemical CO2 reduction to methane (CH4) offers a promising route for carbon utilization and renewable fuel production, yet achieving high-rate and selective CH4 formation remains challenging because of the complex multi-electron reaction pathway and the competing hydrogen evolution reaction. Herein, marine biomass-derived carbon (MBC) obtained from sea pineapple tunics is integrated with copper phthalocyanine (CuPc) to construct a CuPc/MBC hybrid for CO2 electroreduction. The optimized catalyst achieves a CH4 selectivity of 67.9%, a maximum CH4 partial current density of −538.4 mA cm-2, a CuPc-normalized mass activity of 13,460 A g-1, and stable operation for over 49 h, outperforming most previously reported Cu–N–C catalysts. Structural and spectroscopic characterization shows that the highly crystalline cellulose nanofibers form an interconnected carbon framework after vacuum carbonization, while the local Cu–N4 coordination of CuPc is largely preserved. The resulting hybrid structure promotes CuPc dispersion, electron transport, and intimate catalyst–support interfacial contact, accompanied by interfacial electronic coupling and charge redistribution. Electrochemical measurements further reveal a distinct potential dependence of CH4 selectivity, with CH4 formation and H2 evolution exhibiting opposite trends as the applied potential becomes increasingly cathodic. Density functional theory calculations indicate that more negative potentials thermodynamically favor CO2 hydrogenation toward CH4 while simultaneously enhancing the competing hydrogen evolution reaction, leading to an optimal potential window for CH4 production. This work demonstrates a sustainable molecular catalyst/carbon hybrid platform for high-rate CO2-to-CH4 electroreduction and highlights the combined roles of biomass-derived carbon architecture, catalyst–support coupling, and applied potential in regulating catalytic selectivity.
Source: ChemRxiv
Language: English
Field: Energy
Open Access status: green
OpenAlex ID: W7223066145
Cites: 60
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Related to: 10