Multi-fidelity computational screening of high-entropy MBenes for electrochemical CO2 reduction

High-entropy MBenes (HE-MBenes) are two-dimensional transition metal borides whose metal sublattice is occupied by five or more principal elements, forming a largely unexplored class of electrocatalysts for CO 2 electroreduction. These materials combine the lone-pair-driven CO 2 activation intrinsic to MBenes with the configurational stabilization and chemical diversity of high-entropy systems, circumventing the linear scaling relationships (LSRs) that constrain monometallic surfaces. We report a multi-fidelity computational screening of all 56 equiatomic quinary HE-MBene compositions from a {Ti, V, Cr, Mo, Nb, Ta, Zr, Hf} elemental pool. A sequential funnel integrating DFT relaxation, formation-energy filtering, PDOS-guided active-site identification, and computational hydrogen electrode (CHE) free-energy profiling, accelerated by a MACE machine-learning interatomic potential across 1375 surface environments, narrows the space from 56 to 18 viable catalysts. Three compositions, CrNbZrMoTiB 5 , MoZrHfNbCrB 5 , and MoZrHfTaCrB 5 , exhibit spontaneously downhill CO 2 -to-CO free-energy profiles at zero applied potential ( U L = 0.00 V vs. RHE), surpassing all previously reported CHE-computed limiting potentials for MBene and high-entropy-alloy catalysts. Bader charge analysis reveals that Hf/Zr-mediated electron donation to Cr-centred active sites stabilizes the rate-determining COOH * intermediate, decoupling LSRs. These findings establish HE-MBenes as a generalizable catalyst platform and provide a transferable multi-fidelity framework for multicomponent 2D materials discovery.

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Publication Details

Journal
npj Computational Materials
Published
2026-08-17
DOI
https://doi.org/10.1038/s41524-026-02287-4
Primary Topic
CO2 Reduction Techniques and Catalysts
Type
article
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article

Multi-fidelity computational screening of high-entropy MBenes for electrochemical CO2 reduction

Raghavan Ranganathan, Sree Harsha Bharadwaj H
npj Computational Materials
CO2 Reduction Techniques and Catalysts
article

Multi-fidelity computational screening of high-entropy MBenes for electrochemical CO2 reduction

Raghavan Ranganathan, Sree Harsha Bharadwaj H
article en

Abstract

High-entropy MBenes (HE-MBenes) are two-dimensional transition metal borides whose metal sublattice is occupied by five or more principal elements, forming a largely unexplored class of electrocatalysts for CO 2 electroreduction. These materials combine the lone-pair-driven CO 2 activation intrinsic to MBenes with the configurational stabilization and chemical diversity of high-entropy systems, circumventing the linear scaling relationships (LSRs) that constrain monometallic surfaces. We report a multi-fidelity computational screening of all 56 equiatomic quinary HE-MBene compositions from a {Ti, V, Cr, Mo, Nb, Ta, Zr, Hf} elemental pool. A sequential funnel integrating DFT relaxation, formation-energy filtering, PDOS-guided active-site identification, and computational hydrogen electrode (CHE) free-energy profiling, accelerated by a MACE machine-learning interatomic potential across 1375 surface environments, narrows the space from 56 to 18 viable catalysts. Three compositions, CrNbZrMoTiB 5 , MoZrHfNbCrB 5 , and MoZrHfTaCrB 5 , exhibit spontaneously downhill CO 2 -to-CO free-energy profiles at zero applied potential ( U L = 0.00 V vs. RHE), surpassing all previously reported CHE-computed limiting potentials for MBene and high-entropy-alloy catalysts. Bader charge analysis reveals that Hf/Zr-mediated electron donation to Cr-centred active sites stabilizes the rate-determining COOH * intermediate, decoupling LSRs. These findings establish HE-MBenes as a generalizable catalyst platform and provide a transferable multi-fidelity framework for multicomponent 2D materials discovery.

npj Computational Materials
Indian Institute of Technology Gandhinagar (IN)
Affordable and clean energy
Openalex Percentile: Top 26%
CO2 Reduction Techniques and Catalysts
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