Electrocatalytic acetylene semi-hydrogenation is an attractive route for ethylene production, but competing side reactions like hydrogen evolution, over-hydrogenation, and C–C coupling severely compromise its industrial viability. Here, we present a carbon-nanotube-supported metal phthalocyanine platform, MPc/XCNT (M = Cu, Co, Ni, Fe; X = O, N, S), to investigate the roles of metal centers and local coordination environments. Among these catalysts, CoPc-based structures exhibit markedly enhanced water dissociation kinetics and elevated C–C coupling energy barriers compared to conventional CuPc-based catalysts, thereby effectively suppressing undesired C4 by-products. Furthermore, molecular regulation of the Co center optimizes active hydrogen adsorption and utilization, mitigating both hydrogen evolution and over-hydrogenation. As a result, the optimized CoPc/NCNT catalyst delivers competitive performance under both high current densities and ethylene-rich conditions. At an industrially relevant −500 mA cm−2 under a pure ethylene feed, it achieves 86.7% Faradaic efficiency with a turnover frequency of 7019 min−1. Under simulated industrial crude conditions, it maintains 99.7% conversion and 99.5% selectivity during 110-hour continuous operation. This work provides a well-defined molecular strategy for advancing selective electrocatalytic transformations. Selective electrocatalytic acetylene-to-ethylene conversion is limited by competing side reactions over molecular catalysts. Here, the authors report a cobalt phthalocyanine catalyst that achieves 99.99% ethylene selectivity and a turnover frequency of 7019 min-1 at -500 mA cm-2.
Building similarity graph...
Analyzing shared references across papers
Loading...
Cao et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69df2b2ce4eeef8a2a6b02a3 — DOI: https://doi.org/10.1038/s41467-026-71339-6
Fengliang Cao
Wenting Feng
Debin Kong
Nature Communications
Peking University
China University of Petroleum, East China
Qingdao University of Science and Technology
Building similarity graph...
Analyzing shared references across papers
Loading...