Anion Effect in Electrochemical CO2 Reduction: From Spectators to Orchestrators.

The electrochemical CO2 reduction reaction (eCO2RR) offers a pathway to produce valuable chemical fuels from CO2. However, its efficiency in aqueous electrolytes is hindered by the concurrent H2 evolution reaction (HER), which takes place at similar potentials. While the influence of cations on this process has been extensively studied, the influence of anions remains largely unexplored. In this work, we study how eCO2RR selectivity and activity on a gold catalyst are affected by a wide range of inorganic and carboxylate anions. We utilize in situ differential electrochemical mass spectrometry (DEMS) for real-time product monitoring coupled with molecular dynamics (MD) simulations. We show that anions significantly impact eCO2RR kinetics and eCO2RR selectivity. MD simulations reveal a new descriptor─free energy of anion physisorption─where weakly adsorbing anions enable favorable CO2 reduction kinetics, despite the negative charge carried by the electrode surface. By leveraging these fundamental insights, we identify propionate as the most promising anion, achieving nearly 100% Faradaic efficiency while showing high CO production rates that are comparable to those in bicarbonate. These insights underscore the vital role of anion selection in achieving a highly efficient eCO2RR in aqueous electrolytes.

Accounting for the Quantum Capacitance of Graphite in Constant Potential Molecular Dynamics Simulations.

Molecular dynamics (MD) simulations at a constant electric potential are an essential tool to study electrochemical processes, providing microscopic information on the structural, thermodynamic, and dynamical properties. Despite the numerous advances in the simulation of electrodes, they fail to accurately represent the electronic structure of materials such as graphite. In this work, a simple parameterization method that allows to tune the metallicity of the electrode based on a quantum chemistry calculation of the density of states (DOS) is introduced. As a first illustration, the interface between graphite electrodes and two different liquid electrolytes, an aqueous solution of NaCl and a pure ionic liquid, at different applied potentials are studied. It is shown that the simulations reproduce qualitatively the experimentally-measured capacitance; in particular, they yield a minimum of capacitance at the point of zero charge (PZC), which is due to the quantum capacitance (QC) contribution. An analysis of the structure of the adsorbed liquids allows to understand why the ionic liquid displays a lower capacitance despite its large ionic concentration. In addition to its relevance for the important class of carbonaceous electrodes, this method can be applied to any electrode materials (e.g. 2D materials, conducting polymers, etc), thus enabling molecular simulation studies of complex electrochemical devices in the future.

Speciation of the proton in water-in-salt electrolytes.

Water-in-salt (WiS) electrolytes are promising systems for a variety of energy storage devices. Indeed, they represent a great alternative to conventional organic electrolytes thanks to their environmental friendliness, non-flammability, and good electrochemical stability. Understanding the behaviour of such systems and their local organisation is a key direction for their rational design and successful implementation at the industrial scale. In the present paper, we focus our investigation on the 21 m bis(trifluoromethanesulfonyl)imide (LiTFSI) WiS electrolyte, recently reported to have acidic pH values. We explore the speciation of an excess proton in this system and its dependence on the initial local environment using ab initio molecular dynamics simulations. In particular, we observe the formation of HTFSI acid in the WiS system, known to act as a superacid in water. This acid is stabilised in the WiS solution for several picoseconds thanks to the formation of a complex with water molecules and a neighboring TFSI- anion. We further investigate how the excess proton affects the microstructure of WiS, in particular, the recently observed oligomerisation of lithium cations, and we report possible notable perturbations of the lithium nanochain organisation. These two phenomena are particularly important when considering WiS as electrolytes in batteries and supercapacitors, and our results contribute to the comprehension of these systems at the molecular level.

Accelerating QM/MM simulations of electrochemical interfaces through machine learning of electronic charge densities.

A crucial aspect in the simulation of electrochemical interfaces consists in treating the distribution of electronic charge of electrode materials that are put in contact with an electrolyte solution. Recently, it has been shown how a machine-learning method that specifically targets the electronic charge density, also known as SALTED, can be used to predict the long-range response of metal electrodes in model electrochemical cells. In this work, we provide a full integration of SALTED with MetalWalls, a program for performing classical simulations of electrochemical systems. We do so by deriving a spherical harmonics extension of the Ewald summation method, which allows us to efficiently compute the electric field originated by the predicted electrode charge distribution. We show how to use this method to drive the molecular dynamics of an aqueous electrolyte solution under the quantum electric field of a gold electrode, which is matched to the accuracy of density-functional theory. Notably, we find that the resulting atomic forces present a small error of the order of 1 meV/Å, demonstrating the great effectiveness of adopting an electron-density path in predicting the electrostatics of the system. Upon running the data-driven dynamics over about 3 ns, we observe qualitative differences in the interfacial distribution of the electrolyte with respect to the results of a classical simulation. By greatly accelerating quantum-mechanics/molecular-mechanics approaches applied to electrochemical systems, our method opens the door to nanosecond timescales in the accurate atomistic description of the electrical double layer.

Cluster analysis as a tool for quantifying structure-transport properties in simulations of superconcentrated electrolyte.

Using molecular dynamics simulations and graph-theory-based cluster analysis, we investigate the structure-transport properties of typical water-in-salt electrolytes. We demonstrate that ions exhibit distinct dynamics across different ionic clusters-namely, solvent-separated ion pairs (SSIPs), contact ion pairs (CIPs), and aggregates (AGGs). We assess the average proportions of various ionic species and their lifetimes. Our method reveals a dynamic decoupling of ion kinetics, with each species independently contributing to the overall molecular motion. This is evidenced by the fact that the total velocity autocorrelation function (VACF) and power spectrum can be expressed as a weighted sum of independent functions for each species. The experimental data on the ionic conductivity of the studied LiTFSI electrolytes align well with our theoretical predictions at various concentrations, based on the proportions and diffusion coefficients of free ions derived from our analysis. The insights gained into the solvation structures and dynamics of different ionic species enable us to elucidate the physical mechanisms driving ion transport in such superconcentrated electrolytes, providing a comprehensive framework for the future design and optimization of electrolytes.

Modeling of Nanomaterials for Supercapacitors: Beyond Carbon Electrodes.

Capacitive storage devices allow for fast charge and discharge cycles, making them the perfect complements to batteries for high power applications. Many materials display interesting capacitive properties when they are put in contact with ionic solutions despite their very different structures and (surface) reactivity. Among them, nanocarbons are the most important for practical applications, but many nanomaterials have recently emerged, such as conductive metal-organic frameworks, 2D materials, and a wide variety of metal oxides. These heterogeneous and complex electrode materials are difficult to model with conventional approaches. However, the development of computational methods, the incorporation of machine learning techniques, and the increasing power in high performance computing now allow us to tackle these types of systems. In this Review, we summarize the current efforts in this direction. We show that depending on the nature of the materials and of the charging mechanisms, different methods, or combinations of them, can provide desirable atomic-scale insight on the interactions at play. We mainly focus on two important aspects: (i) the study of ion adsorption in complex nanoporous materials, which require the extension of constant potential molecular dynamics to multicomponent systems, and (ii) the characterization of Faradaic processes in pseudocapacitors, that involves the use of electronic structure-based methods. We also discuss how recently developed simulation methods will allow bridges to be made between double-layer capacitors and pseudocapacitors for future high power electricity storage devices.

Correlated Anion Disorder in Heteroanionic Cubic TiOF2.

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO3-type) TiOF2 using X-ray pair distribution function (PDF), 19F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF2, characterized by predominant cis-[O2F4] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF4. We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

Correlating Substrate Reactivity at Electrified Interfaces with the Electrolyte Structure in Synthetically Relevant Organic Solvent/Water Mixtures.

Optimizing electrosynthetic reactions requires fine tuning of a vast chemical space, including charge transfer at electrocatalyst/electrode surfaces, engineering of mass transport limitations, and complex interactions of reactants and products with their environment. Hybrid electrolytes, in which supporting salt ions and substrates are dissolved in a binary mixture of organic solvent and water, represent a new piece of this complex puzzle as they offer a unique opportunity to harness water as the oxygen or proton source in electrosynthesis. In this work, we demonstrate that modulating water-organic solvent interactions drastically impacts the solvation properties of hybrid electrolytes. Combining various spectroscopies with synchrotron small-angle X-ray scattering (SAXS) and force field-based molecular dynamics (MD) simulations, we show that the size and composition of aqueous domains forming in hybrid electrolytes can be controlled. We demonstrate that water is more reactive for the hydrogen evolution reaction (HER) in aqueous domains than when strongly interacting with solvent molecules, which originates from a change in reaction kinetics rather than a thermodynamic effect. We exemplify novel opportunities arising from this new knowledge for optimizing electrosynthetic reactions in hybrid electrolytes. For reactions proceeding first via the activation of water, fine tuning of aqueous domains impacts the kinetics and potentially the selectivity of the reaction. Instead, for organic substrates reacting prior to water, aqueous domains have no impact on the reaction kinetics, while selectivity may be affected. We believe that such a fine comprehension of solvation properties of hybrid electrolytes can be transposed to numerous electrosynthetic reactions.

Dynamics and Energetics of Ion Adsorption at the Interface between a Pure Ionic Liquid and Carbon Electrodes.

Molecular dynamics simulations have been used extensively to determine equilibrium properties of the electrode-electrolyte interface in supercapacitors held at various potentials. While such studies are essential to understand and optimize the performance of such energy storage systems, investigation of the dynamics of adsorption during the charge of the supercapacitors is also necessary. Dynamical properties are especially important to get an insight into the power density of supercapacitors, one of their main assets. In this work, we propose a new method to coarse-grain simulations of all-atom systems and compute effective Lennard-Jones and Coulomb parameters, allowing subsequently to analyze the trajectories of adsorbing ions. We focus on pure 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide in contact with planar carbon electrodes. We characterize the evolution of the ion orientation and ion-electrode distance during adsorption and show that ions reorientate as they adsorb. We then determine the forces experienced by the adsorbing ions and demonstrate that Coulomb forces are dominant at a long range while van der Waals forces are dominant at a short range. We also show that there is an almost equal contribution from the two forces at an intermediate distance, explaining the peak of ion density close to the electrode surface.

Data-Driven Path Collective Variables.

Identifying optimal collective variables to model transformations using atomic-scale simulations is a long-standing challenge. We propose a new method for the generation, optimization, and comparison of collective variables that can be thought of as a data-driven generalization of the path collective variable concept. It consists of a kernel ridge regression of the committor probability, which encodes a transformation's progress. The resulting collective variable is one-dimensional, interpretable, and differentiable, making it appropriate for enhanced sampling simulations requiring biasing. We demonstrate the validity of the method on two different applications: a precipitation model and the association of Li+ and F- in water. For the former, we show that global descriptors such as the permutation invariant vector allow reaching an accuracy far from the one achieved via simpler, more intuitive variables. For the latter, we show that information correlated with the transformation mechanism is contained in the first solvation shell only and that inertial effects prevent the derivation of optimal collective variables from the atomic positions only.

Tuning MXene Properties through Cu Intercalation: Coupled Guest/Host Redox and Pseudocapacitance.

MXenes are 2D transition metal carbides, nitrides, and/or carbonitrides that can be intercalated with cations through chemical or electrochemical pathways. While the insertion of alkali and alkaline earth cations into Ti3C2Tx MXenes is well studied, understanding of the intercalation of redox-active transition metal ions into MXenes and its impact on their electronic and electrochemical properties is lacking. In this work, we investigate the intercalation of Cu ions into Ti3C2Tx MXene and its effect on its electronic and electrochemical properties. Using X-ray absorption spectroscopy (XAS) and ab initio molecular dynamics (AIMD), we observe an unusual phenomenon whereby Cu2+ ions undergo partial reduction upon intercalation from the solution into the MXene. Furthermore, using in situ XAS, we reveal changes in the oxidation states of intercalated Cu ions and Ti atoms during charging. We show that the pseudocapacitive response of Cu-MXene originates from the redox of both the Cu intercalant and Ti3C2Tx host. Despite highly reducing potentials, Cu ions inside the MXene show an excellent stability against full reduction upon charging. Our findings demonstrate how electronic coupling between Cu ions and Ti3C2Tx modifies electrochemical and electronic properties of the latter, providing the framework for the rational design and utilization of transition metal intercalants for tuning the properties of MXenes for various electrochemical systems.

Formation of Polymer-like Nanochains with Short Lithium-Lithium Distances in a Water-in-Salt Electrolyte.

Water-in-salts (WiSs) have recently emerged as promising electrolytes for energy storage applications ranging from aqueous batteries to supercapacitors. Here, ab initio molecular dynamics is used to study the structure of a 21 m LiTFSI WiS. The simulation reveals a new feature, in which the lithium ions form polymer-like nanochains that involve up to 10 ions. Despite the strong Coulombic interaction between them, the ions in the chains are found at a distance of 2.5 Å. They show a drastically different solvation shell compared to that of the isolated ions, in which they share on average two water molecules. The nanochains have a highly transient character due to the low free energy barrier for forming/breaking them. Providing new insights into the nanostructure of WiS electrolytes, our work calls for reevaluating our current knowledge of highly concentrated electrolytes and the impact of the modification of the solvation of active species on their electrochemical performances.

Solvation-Tuned Photoacid as a Stable Light-Driven pH Switch for CO2 Capture and Release.

Photoacids are organic molecules that release protons under illumination, providing spatiotemporal control of the pH. Such light-driven pH switches offer the ability to cyclically alter the pH of the medium and are highly attractive for a wide variety of applications, including CO2 capture. Although photoacids such as protonated merocyanine can enable fully reversible pH cycling in water, they have a limited chemical stability against hydrolysis (<24 h). Moreover, these photoacids have low solubility, which limits the pH-switching ability in a buffered solution such as dissolved CO2. In this work, we introduce a simple pathway to dramatically increase stability and solubility of photoacids by tuning their solvation environment in binary solvent mixtures. We show that a preferential solvation of merocyanine by aprotic solvent molecules results in a 60% increase in pH modulation magnitude when compared to the behavior in pure water and can withstand stable cycling for >350 h. Our results suggest that a very high stability of merocyanine photoacids can be achieved in the right solvent mixtures, offering a way to bypass complex structural modifications of photoacid molecules and serving as the key milestone toward their application in a photodriven CO2 capture process.

Ions Adsorbed at Amorphous Solid/Solution Interfaces Form Wigner Crystal-like Structures.

When a surface is immersed in a solution, it usually acquires a charge, which attracts counterions and repels co-ions to form an electrical double layer. The ions directly adsorbed to the surface are referred to as the Stern layer. The structure of the Stern layer normal to the interface was described decades ago, but the lateral organization within the Stern layer has received scant attention. This is because instrumental limitations have prevented visualization of the ion arrangements except for atypical, model, crystalline surfaces. Here, we use high-resolution amplitude modulated atomic force microscopy (AFM) to visualize in situ the lateral structure of Stern layer ions adsorbed to polycrystalline gold, and amorphous silica and gallium nitride (GaN). For all three substrates, when the density of ions in the layer exceeds a system-dependent threshold, correlation effects induce the formation of close packed structures akin to Wigner crystals. Depending on the surface and the ions, the Wigner crystal-like structure can be hexagonally close packed, cubic, or worm-like. The influence of the electrolyte concentration, species, and valence, as well as the surface type and charge, on the Stern layer structures is described. When the system parameters are changed to reduce the Stern layer ion surface excess below the threshold value, Wigner crystal-like structures do not form and the Stern layer is unstructured. For gold surfaces, molecular dynamics (MD) simulations reveal that when sufficient potential is applied to the surface, ion clusters form with dimensions similar to the Wigner crystal-like structures in the AFM images. The lateral Stern layer structures presented, and in particular the Wigner crystal-like structures, will influence diverse applications in chemistry, energy storage, environmental science, nanotechnology, biology, and medicine.

Disclosing the Interfacial Electrolyte Structure of Na-Insertion Electrode Materials: Origins of the Desolvation Phenomenon.

Among a variety of promising cathode materials for Na-ion batteries, polyanionic Na-insertion compounds are among the preferred choices due to known fast sodium transfer through the ion channels along their framework structures. The most interesting representatives are Na3V2(PO4)3 (NVP) and Na3V2(PO4)2F3 (NVPF), which display large Na+ diffusion coefficients (up to 10-9 m2 s-1 in NVP) and high voltage plateaux (up to 4.2 V for NVPF). While the diffusion in the solid material is well-known to be the rate-limiting step during charging, already being thoroughly discussed in the literature, interfacial transport of sodium ions from the liquid electrolyte toward the electrode was recently shown to be important due to complex ion desolvation effects at the surface. In order to fill the blanks in the description of the electrode/electrolyte interface in Na-ion batteries, we performed a molecular dynamics study of the local nanostructure of a series of carbonate-based sodium electrolytes at the NVP and the NVPF interfaces along with careful examination of the desolvation phenomenon. We show that the tightness of solvent packing at the electrode surface is a major factor determining the height of the free energy barrier associated with desolvation, which explains the differences between the NVP and the NVPF structures. To rationalize and emphasize the remarkable properties of this family of cathode materials, a complementary comparative analysis of the same electrolyte system at the carbon electrode interface was also performed.

Capturing the interactions in the BaSnF4 ionic conductor: Comparison between a machine-learning potential and a polarizable force field.

BaSnF4 is a prospective solid state electrolyte for fluoride ion batteries. However, the diffusion mechanism of the fluoride ions remains difficult to study, both in experiments and in simulations. In principle, ab initio molecular dynamics could allow to fill this gap, but this method remains very costly from the computational point of view. Using machine learning potentials is a promising method that can potentially address the accuracy issues of classical empirical potentials while maintaining high efficiency. In this work, we fitted a dipole polarizable ion model and trained machine learning potential for BaSnF4 and made comprehensive comparisons on the ease of training, accuracy and efficiency. We also compared the results with the case of a simpler ionic system (NaF). We show that contrarily to the latter, for BaSnF4 the machine learning potential offers much higher versatility. The current work lays foundations for the investigation of fluoride ion mobility in BaSnF4 and provides insight on the choice of methods for atomistic simulations.

Electrochemical Properties and Local Structure of the TEMPO/TEMPO+ Redox Pair in Ionic Liquids.

Redox-active organic species play an important role in catalysis, energy storage, and biotechnology. One of the representatives is the 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) radical, used as a mediator in organic synthesis and considered a safe alternative to heavy metals. In order to develop a TEMPO-based system with well-controlled electrochemical and catalytic properties, a reaction medium should be carefully chosen. Being highly conductive, stable, and low flammability fluids, ionic liquids (ILs) seem to be promising solvents with easily adjustable physical and solvation properties. In this work, we give an insight into the local structure of ILs around TEMPO and its oxidized form, TEMPO+, underlining striking differences in the solvation of these two species. The analysis is coupled with a study of thermodynamics and kinetics of oxidation in the frame of Marcus theory. Our systematic investigation includes imidazolium, pyrrolydinium, and phosphonium families combined with anions of different size, polarity, and flexibility, opting to provide a clear and comprehensive picture of the impact of the nature of IL ions on the behavior of radical/cation redox pairs. The obtained results will help to explain experimentally observed effects and to rationalize the design of TEMPO/IL systems.