Skip to content
DraconiticResearch
Search Sources API
201,683 studies31 sourcesUpdated 2 min ago
PreprintCC BYChemRxiv

Temperature-and pressure-dependent water stabilization of CO dimerization on Cu(100)

Abstract

The electrochemical CO(2) reduction reaction offers a pathway to producing fuels and high-value chemicals from waste CO2 using renewable electricity. Among known catalysts, only copper in aqueous electrolytes enables the formation of C2+ products with high activity. The process of the C-C coupling is believed to be limited by the dimerization of two adsorbed *CO to form a *OC-CO* intermediate. Experimental strategies to improve selectivity toward C2+ products have recently focused on increasing temperature and pressure in the system, but the origins of these effects remain poorly understood. In this work, the thermodynamic and kinetic stability of the *OC-CO* dimer at the electrochemical interface of Cu(100) has been investigated, as a function of temperature and pressure using machine-learning interatomic potentials trained on DFT data. Extended molecular dynamics simulations with an explicit aqueous interface show that increased water density stabilizes the *OC-CO* intermediate through increased hydrogen bonding between interfacial water and the dimer. In contrast, temperature has no direct effect on the CO–CO association barrier, but instead indirectly influences reactivity by destabilizing *CO adsorption. Introducing a potassium cation leads to a large reduction in the interface work function, but only minor changes were observed in the energetics of the dimer formation. No correlation between cation-dimer distance and energetics is observed, suggesting a limited role of local field effects. These results identify hydrogen bonding as the key factor governing the stabilization of the *OC-CO* intermediate under experimental conditions. This work demonstrates how machine-learning interatomic potentials can facilitate systematic analysis of dynamic interfaces, and can be a powerful tool in theoretical exploration of electrolyte effects on reaction intermediates across extended time and length scales.

Related

  1. pGM5P-26: A Polarizable Gaussian Multipole Water Model with Transferable Temperature-Dependent Thermodynamics.
    Yongxian Wu, Piotr Cieplak, Yong Duan +1
    Journal of chemical theory and computationPeer-reviewedCC BY-NC-NDFull textPhysical chemistryEurope PMC
  2. Surface-Modified Cellulose Nanofibers for Stabilization of Barite in Water-Based Drilling Fluids Under High Temperatures
    Ziheng Zhang, Dongqing Yang, Ziyan Li +3
    PolymersPeer-reviewedCC BYFull textMaterials & polymersEurope PMC
  3. Chemo-enzymatic synthesis, in vitro antioxidant activities and positive effects on oil-in-water emulsion Stabilization of phenolic acid-esterified phosphatidylcholines
    Hong Li, Xintian Qiao, Ran Ding +5
    Journal of Oleo SciencePeer-reviewedCC BYFull textGeneral chemistryJ-STAGE
  4. Patterning Conductive Aluminium onto Temperature Sensitive Polymers and Tattoo Paper at Room Temperature and Pressure
    Zhengyuan Li, Shreya Mrig, Wanqi Zhang +7
    ChemRxivPreprintCC BYFull textGeneral chemistryChemRxiv
  5. Construction of a Curated Literature Dataset and Machine Learning-Guided Exploration of Supported Metal Catalysts for Low- to Intermediate-Temperature Reverse Water–Gas Shift Reaction
    Umi Shin, Shinya Mine, Aritomo Yamaguchi +1
    ChemRxivPreprintLicence not statedGeneral chemistryChemRxiv
BibTeX
@misc{hoholdt2026temperatureand,
  title = {{Temperature-and pressure-dependent water stabilization of CO dimerization on Cu(100)}},
  author = {Alberte H. Høholdt and Alexander Bagger and Alberte Holm Høholdt},
  howpublished = {ChemRxiv},
  year = {2026},
  month = sep,
  doi = {10.26434/chemrxiv.15005749/v2},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15005749/v2},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Temperature-and pressure-dependent water stabilization of CO dimerization on Cu(100)
AU  - Alberte H. Høholdt
AU  - Alexander Bagger
AU  - Alberte Holm Høholdt
PY  - 2026
DA  - 2026/09/17
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15005749/v2
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15005749/v2
AB  - The electrochemical CO(2) reduction reaction offers a pathway to producing fuels and high-value chemicals from waste CO2 using renewable electricity. Among known catalysts, only copper in aqueous electrolytes enables the formation of C2+ products with high activity. The process of the C-C coupling is believed to be limited by the dimerization of two adsorbed *CO to form a *OC-CO* intermediate. Experimental strategies to improve selectivity toward C2+ products have recently focused on increasing temperature and pressure in the system, but the origins of these effects remain poorly understood. In this work, the thermodynamic and kinetic stability of the *OC-CO* dimer at the electrochemical interface of Cu(100) has been investigated, as a function of temperature and pressure using machine-learning interatomic potentials trained on DFT data. Extended molecular dynamics simulations with an explicit aqueous interface show that increased water density stabilizes the *OC-CO* intermediate through increased hydrogen bonding between interfacial water and the dimer. In contrast, temperature has no direct effect on the CO–CO association barrier, but instead indirectly influences reactivity by destabilizing *CO adsorption. Introducing a potassium cation leads to a large reduction in the interface work function, but only minor changes were observed in the energetics of the dimer formation. No correlation between cation-dimer distance and energetics is observed, suggesting a limited role of local field effects. These results identify hydrogen bonding as the key factor governing the stabilization of the *OC-CO* intermediate under experimental conditions. This work demonstrates how machine-learning interatomic potentials can facilitate systematic analysis of dynamic interfaces, and can be a powerful tool in theoretical exploration of electrolyte effects on reaction intermediates across extended time and length scales.
ER  -