Tailoring Electrode-Electrolyte Interfaces in Lithium-Ion Batteries Using Molecularly Engineered Functional Polymers.

Electrode-electrolyte interfaces (EEIs) affect the rate capability, cycling stability, and thermal safety of lithium-ion batteries (LIBs). Designing stable EEIs with fast Li+ transport is crucial for developing advanced LIBs. Here, we study Li+ kinetics at EEIs tailored by three nanoscale polymer thin films via chemical vapor deposition (CVD) polymerization. Small binding energy with Li+ and the presence of sufficient binding sites for Li+ allow poly(3,4-ethylenedioxythiophene) (PEDOT) based artificial coatings to enable fast charging of LiCoO2. Operando synchrotron X-ray diffraction experiments suggest that the superior Li+ transport property in PEDOT further improves current homogeneity in the LiCoO2 electrode during cycling. PEDOT also forms chemical bonds with LiCoO2, which reduces Co dissolution and inhibits electrolyte decomposition. As a result, the LiCoO2 4.5 V cycle life tested at C/2 increases over 1700% after PEDOT coating. In comparison, the other two polymer coatings show undesirable effects on LiCoO2 performance. These insights provide us with rules for selecting/designing polymers to engineer EEIs in advanced LIBs.

Resolving the Geometry/Charge Puzzle of the c(2 × 2)-Cl Cu(100) Electrode.

Potential-induced changes in charge and surface structure are significant drivers of the reactivity of electrochemical interfaces but are frequently difficult to decouple from the effects of surface solvation. Here, we consider the Cu(100) surface with a c(2 × 2)-Cl adlayer, a model surface with multiple geometry measurements under both ultrahigh vacuum and electrochemical conditions. Under aqueous electrochemical conditions, the measured Cu-Cl interplanar separation (dCu-Cl) increases by at least 0.3 Å relative to that under ultrahigh vacuum conditions. This large geometry change is unexpected for a hydrophobic surface, and it requires invoking a negative charge on the Cl-covered surface which is much greater than expected from the work function and our capacitance measurements. To resolve this inconsistency we employ ab initio calculations and find that the Cu-Cl separation increases with charging at a rate of 0.7 Å/e- per Cl atom. The larger Cu-Cl bond distance increases the surface dipole and, therefore, the work function of the interface, contributing to the negative charge under fixed potential electrochemical conditions. Interactions with water are not needed to explain either the large charge or large Cu-Cl interplanar spacing of this surface under electrochemical conditions.

Halide-induced Step Faceting and Dissolution Energetics from Atomistic Machine Learned Potentials on Cu(100).

Adsorbates impact the surface stability and reactivity of metallic electrodes, affecting the corrosion, dissolution, and deposition behavior. Here, we use density functional theory (DFT) and DFT-based Behler-Parrinello neural networks (BPNN) to investigate the geometries, surface formation energies, and atom removal energies of stepped and kinked surfaces vicinal to Cu(100) with a c(2×2) Cl adlayer. DFT calculations indicate that the stable structures for the adsorbate-free vicinal surfaces favor steps with <110> orientation, while the addition of the c(2×2) Cl adlayer leads to <100> step facets, in agreement with scanning tunneling microscopy (STM) observations. The BPNN calculations produce energies in good agreement with DFT results (root mean square error of 1.3 meV/atom for a randomly chosen set of structures excluded from the training set). We draw three conclusions from the BPNN calculations. First, Cl on the upper <100> step edges occupies the three fold hollow sites (as opposed to the four-fold sites on the terraces), congruent with deviations of the STM height profile for the adsorbate at the upper step edge. Second, disruptions in the continuity of the halide overlayer at the steps result in significant long-range step-step interactions. Third, anisotropic metal dissolution and deposition energetics arise from phase shifts of the c(2×2) adlayer at orthogonal <100> steps. This DFT-BPNN approach offers an effective strategy for tackling large-scale surface structure challenges with atomic-level accuracy.

Machine Learning-Guided Approach for Studying Solvation Environments.

Molecular-level understanding and characterization of solvation environments are often needed across chemistry, biology, and engineering. Toward practical modeling of local solvation effects of any solute in any solvent, we report a static and all-quantum mechanics-based cluster-continuum approach for calculating single-ion solvation free energies. This approach uses a global optimization procedure to identify low-energy molecular clusters with different numbers of explicit solvent molecules and then employs the smooth overlap for atomic positions learning kernel to quantify the similarity between different low-energy solute environments. From these data, we use sketch maps, a nonlinear dimensionality reduction algorithm, to obtain a two-dimensional visual representation of the similarity between solute environments in differently sized microsolvated clusters. After testing this approach on different ions having charges 2+, 1+, 1-, and 2-, we find that the solvation environment around each ion can be seen to usually become more similar in hand with its calculated single-ion solvation free energy. Without needing either dynamics simulations or an a priori knowledge of local solvation structure of the ions, this approach can be used to calculate solvation free energies within 5% of experimental measurements for most cases, and it should be transferable for the study of other systems where dynamics simulations are not easily carried out.

Quantum Chemical Analyses of BH4- and BH3 OH- Hydride Transfers to CO2 in Aqueous Solution with Potentials of Mean Force.

Biomimetic hydride transfer catalysts are a promising route to efficiently convert CO2 into more useful products, but a lack of understanding about their atomic-scale reaction mechanisms slows their development. To this end, we report a computational quantum chemistry study of how aqueous solvation influences CO2 reduction reactions facilitated by sodium borohydride (NaBH4 ) and a partially oxidized derivative (NaBH3 OH). This work compares 0 K reaction barriers from nudged elastic band calculations to free-energy barriers obtained at 300 K using potentials of mean force from umbrella sampling simulations. We show that explicitly treating free energies from reaction pathway sampling has anywhere from a small to a large effect on the reaction-energy profiles for aqueous-phase hydride transfers to CO2 . Sampling along predefined reaction coordinates is thus recommended when it is computationally feasible.

Explicitly Unraveling the Roles of Counterions, Solvent Molecules, and Electron Correlation in Solution Phase Reaction Pathways.

Studies utilizing continuum solvation methods can sometimes omit critically important solute-solvent interactions, while explicitly sampling full solution phase mechanisms accurately with Born-Oppenheimer molecular dynamics (BOMD) is computationally costly. In this work, we benchmark components for an alternative IRCMax-like procedure for refined analyses of electronic energies along reaction pathways. The procedure involves obtaining molecular clusters from nudged elastic band calculations for use in mixed explicit-continuum models. The reaction energetics from these models correspond well to energetics obtained from explicit models using periodic boundary conditions, and the clusters obtained are more amenable to treatments with high levels of quantum chemistry theory. We demonstrate this approach using CO2 reduction by NaBH4 and NaBH3OH in aqueous solution as test cases. We show that the local solvation environment containing explicit solvent molecules and a counterion within the entire first solvation shell significantly influences reaction energies. For the hydride transfers reported herein, the level of quantum chemistry theory used beyond that treated by standard GGA exchange correlation functionals normally plays a less significant role.

Structural and Substituent Group Effects on Multielectron Standard Reduction Potentials of Aromatic N-Heterocycles.

Aromatic N-heterocycles have been used in electrochemical CO2 reduction, but their precise role is not yet fully understood. We used first-principles quantum chemistry to determine how the molecular sizes and substituent groups of these molecules affect their standard redox potentials involving various proton and electron transfers. We then use that data to generate molecular Pourbaix diagrams to find the electrochemical conditions at which the aromatic N-heterocycle molecules could participate in multiproton and electron shuttling in accordance with the Sabatier principle. While one-electron standard redox potentials for aromatic N-heterocycles can vary significantly with molecule size and the presence of substituent groups, the two-electron and two-proton standard redox potentials depend much less on structural modifications and substituent groups. This indicates that a wide variety of aromatic N-heterocycles can participate in proton, electron, and/or hydride shuttling under suitable electrochemical conditions.