Although CO₂ contributes significantly to global warming, it also offers potential as a raw material for the production of hydrocarbons such as CH₄, C₂H₄ and CH₃OH. Electrochemical CO₂ reduction reaction (eCO₂RR) is an emerging technology that utilizes renewable energy to convert CO₂ into valuable fuels, solving environmental and energy problems simultaneously. Insights gained at any individual scale can only provide a limited view of that specific scale. Multiscale modeling, which involves coupling atomistic‐level insights (density functional theory, DFT) and (Molecular Dynamics, MD), with mesoscale (kinetic Monte Carlo, KMC, and microkinetics, MK) and macroscale (computational fluid dynamics, CFD) simulations, has received significant attention recently. While multiscale modeling of eCO₂RR on electrocatalysts across all scales is limited due to its complexity, this review offers an overview of recent works on single scales and the coupling of two and three scales, such as “DFT+MD”, “DFT+KMC”, “DFT+MK”, “KMC/MK+CFD” and “DFT+MK/KMC+CFD”, focusing particularly on Cu‐based electrocatalysts as copper is known to be an excellent electrocatalyst for eCO₂RR. This sets it apart from other reviews that solely focus exclusively on a single scale or only on a combination of DFT and MK/KMC scales. Furthermore, this review offers a concise overview of machine learning (ML) applications for eCO₂RR, an emerging approach that has not yet been reviewed. Finally, this review highlights the key challenges, research gaps and perspectives of multiscale modeling for eCO₂RR.

Appropriate maintenance of Cu(I) homeostasis is an essential requirement for proper cell function because its misregulation induces the onset of major human diseases and mortality. For this reason, several research efforts have been devoted to dissecting the inner working mechanism of Cu(I)-binding proteins and transporters. A commonly adopted strategy relies on mutations of cysteine residues, for which Cu(I) has an exquisite complementarity, to serines. Nevertheless, in spite of the similarity between these two amino acids, the structural and functional impact of serine mutations on Cu(I)-binding biomolecules remains unclear. Here, we applied various biochemical and biophysical methods, together with all-atom simulations, to investigate the effect of these mutations on the stability, structure, and aggregation propensity of Cu(I)-binding proteins, as well as their interaction with specific partner proteins. Among Cu(I)-binding biomolecules, we focused on the eukaryotic Atox1-ATP7B system, and the prokaryotic CueR metalloregulator. Our results reveal that proteins containing cysteine-to-serine mutations can still bind Cu(I) ions; however, this alters their stability and aggregation propensity. These results contribute to deciphering the critical biological principles underlying the regulatory mechanism of the in-cell Cu(I) concentration, and provide a basis for interpreting future studies that will take advantage of cysteine-to-serine mutations in Cu(I)-binding systems.

Electrochemical reduction reaction of CO ₂ (eCO ₂ RR) to produce valuable chemicals offers an attractive strategy to solve energy and environmental problems simultaneously. We have mapped out entire reaction pathways of eCO ₂ RR to CO on Cu(100), including all intermediates and transition states using first‐principles simulations. To accurately account for the solvent effect, the reaction was investigated with and without explicit water molecules, highlighting the limitations of the often (mis)used vacuum reaction pathway simplification. The results show that the reduction reaction was initiated under neutral pH conditions at an applied potential of −0.11 V (RHE, reversible hydrogen electrode) and all elementary reactions were thermodynamically favorable, while an applied potential of −1.24 V is required to ensure that all reactions exhibit spontaneous behavior. Detailed analysis revealed that solvation significantly influences the stability of the adsorbates and intermediates. Its inclusion notably alters the calculated reaction kinetics and energetic parameters by lowering the barrier energies and Gibbs free energies of all reactions. CO production proceeded mainly via the COOH* pathway (CO ₂ → trans ‐COOH*→ cis ‐COOH*→CO*+OH*→CO*→CO). The use of water as a more sustainable and cost‐effective solvent is compared to other options such as organic solvents, ionic liquids and mixed solvent systems, which are less sustainable and more expensive.