April 13, 2026 article Estimating Potential-Dependent Physicochemical Properties at Metal–Electrolyte Interfaces Using Machine Learning Interatomic Potentials ACS electrochemistry. DOI: 10.1021/acselectrochem.5c00540 OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 3 References 3 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Absence of CO2 electroreduction on copper, gold and silver electrodes without metal cations in solution 2021 Nature Catalysis article Energy CO2 Reduction Techniques and Catalysts Open access cited by 2 patents 1,004 citations The Intricacies of Computational Electrochemistry 2025 ACS Energy Letters article Physics and Astronomy Advanced Chemical Physics Studies Open access 28 citations Benchmarking short-range machine learning potentials for atomistic simulations of metal/electrolyte interfaces 2026 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access 1 citations 3 results