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A classical coulombic correlation functional in one-loop (1L) and local-density-approximation (LDA) is derived for electrolyte solutions, starting from a first-principles many-body partition function. The 1L-LDA functional captures correlations between electrolyte ions and solvent dipoles, such as screening and solvation, that are ignored by conventional mean-field theories. This 1L-LDA functional introduces two parameters that can be tuned to the experimental dielectric permittivity and activity coefficients in the bulk electrolyte solution. The capabilities of the 1L-LDA functional for the description of metal-electrolyte interfaces are demonstrated by embedding the functional into a combined quantum-classical model. Here, the 1L-LDA functional leads to a more pronounced double-peak structure of the interfacial capacitance with higher peaks and shorter peak-to-peak distance, significantly improving the agreement with experimental data and showing that electrolyte correlation effects exert a vital impact on the capacitive response.

Most of the novel energy materials contain multiple elements occupying a single site in their lattice. The exceedingly large configurational space of these materials imposes challenges in determining their ground-state structures. Coulomb energies of possible configurations generally show a satisfactory correlation to computed energies at higher levels of theory and thus allow to screen for minimum-energy structures. Employing a second-order cluster expansion, we obtain an efficient Coulomb energy optimizer using Monte Carlo and Genetic Algorithms. The presented optimization package, GOAC (Global Optimization of Atomistic Configurations by Coulomb), can achieve a speed up of several orders of magnitude compared to existing software. Our code is able to find low-energy configurations of complex systems involving up to $10^{920}$ structural configurations. The GOAC package thus provides an efficient method for constructing ground-state atomistic models for multi-element materials with gigantic configurational spaces.

Molecular dynamics 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, we introduce a simple parameterization method that allows to tune the metallicity of the electrode based on a quantum chemistry calculation of the density of states. As a first illustration, we study the interface between graphite electrodes and two different liquid electrolytes, an aqueous solution of NaCl and a pure ionic liquid, at different applied potentials. We show that the simulations reproduce qualitatively the experimentally-measured capacitance; in particular, they yield a minimum of capacitance at the point of zero charge, which is due to the quantum capacitance 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.

Energy materials with disorder in site occupation are challenging for computational studies due to an exponential scaling of the configuration space. We herein present a grand-canonical optimization method that enables the use of quantum annealing (QA) for sampling the ionic ground state. The method relies on a Legendre transformation of the Coulomb energy cost function that strongly reduces the effective coupling strengths of the fully connected problem, which is essential for effectiveness of QA. The approach is expected to be applicable to a variety of materials optimization problems.

The differential capacitance comprises the most relevant thermodynamic information about an electrochemical system. Classical approaches to describe electrochemical capacitance have difficulties to combine the treatment of the ionic contribution of the electrolyte with the electronic contribution of the electrode. Moreover, different approaches are typically required for the description of the double-layer capacitance, on the one hand, and the pseudocapacitive contribution due to adsorption or intercalation of reactive species, on the other. In the present work, a new approach to describe electrochemical capacitance from first principles is developed. The treatment of a general electrochemical system at the level of multicomponent density-functional theory (MCDFT) yields an exact analytical expression for the total capacitance of the system, which corresponds to a formal series-circuit partitioning into "quantum" capacitance contributions of the density of states of electrons and ions, the (mean-field) electrostatic capacitance, as well as capacitance contributions of exchange and correlation among all active species. It is shown that the classical expression of the double-layer capacitance involving the interfacial Galvani potential is obtained in the limit of extended electrode and electrolyte regions. Importantly, the present formalism also describes systems with confined electrode and electrolyte phases, where the definition of the (classical) inner potentials of the electrode and electrolyte domains becomes problematic. Moreover, the new approach unifies the treatment of double-layer capacitance and pseudocapacitance resulting from reactive processes.

Computational studies of electrochemical interfaces based on density-functional theory (DFT) play an increasingly important role in present research on electrochemical processes for energy conversion and storage. The homogeneous background method (HBM) offers a straightforward approach to charge the electrochemical system within DFT simulations, but it typically requires the specification of the "active" fraction of excess electrons based on a certain choice of the electrode-electrolyte boundary location, which can be difficult in presence of electrode-surface adsorbates or explicit solvent molecules. In this work, we present a methodological advancement of the HBM, both facilitating and extending its applicability. The advanced version neither requires energy corrections nor the specification of the "active" fraction of excess electrons, providing a versatile and readily available method for the simulation of charged interfaces also when adsorbates or explicit solvent molecules are present. Our computational DFT results for Pt(111), Au(111) and Li(100) metal electrodes in high-dielectric-constant solvents demonstrate an excellent agreement in the interfacial charging characteristics obtained from simulations with the advanced HBM in comparison with the (linearized) Poisson-Boltzmann model (PBM).

The ab initio simulation of charged interfaces in the framework of density functional theory (DFT) is heavily employed for the study of electrochemical energy conversion processes. The capacitance is the primary descriptor for the response of the electrochemical interface. It is essentially equal to the inverse of the energy curvature as a function of electron number, and as such there appears a conflict with the fundamental principle of piecewise linearity in DFT that requires the energy curvature to be zero at fractional electron numbers, i.e. almost everywhere. To resolve this conflict, we derive an exact expression between the energy curvature and the Kohn-Sham density of states, the local density of states, and the Fukui potential. We find that the piecewise linearity requirement does not hold for the volume- or area-specific energy of extended systems and surfaces. Applied to the joint density functional theory of an electrode-electrolyte interface, including the ionic and dielectric response of the electrolyte, the same expression represents a rigorous basis for the partitioning of the total interfacial capacitance into contributions of the quantum capacitance, space-charge capacitance, and electrochemical double-layer capacitance. It provides insight into the influence of the electrode material, thickness, and temperature on the charging characteristics, as demonstrated by results for a bulk gold electrode, a single-layer gold electrode, and a single-layer graphene electrode.

We study the oxo-hexametallate Li$_7$TaO$_6$ with first-principles and classical molecular dynamics simulations, obtaining a low activation barrier for diffusion of $\sim$0.29 eV and a high ionic conductivity of $5.7 \times 10^{-4}$ S cm$^{-1}$ at room temperature (300 K). We find evidence for a wide electrochemical stability window from both calculations and experiments, suggesting its viable use as a solid-state electrolyte in next-generation solid-state Li-ion batteries. To assess its applicability in an electrochemical energy storage system, we performed electrochemical impedance spectroscopy measurements on multicrystalline pellets, finding substantial ionic conductivity, if below the values predicted from simulation. We further elucidate the relationship between synthesis conditions and the observed ionic conductivity using X-ray diffraction, inductively coupled plasma optical emission spectrometry, and X-ray photoelectron spectroscopy, and study the effects of Zr and Mo doping.

The recently published DeePMD model (https://github.com/deepmodeling/deepmd-kit), based on a deep neural network architecture, brings the hope of solving the time-scale issue which often prevents the application of first principle molecular dynamics to physical systems. With this contribution we assess the performance of the DeePMD potential on a real-life application and model diffusion of ions in solid-state electrolytes. We consider as test cases the well known Li10GeP2S12, Li7La3Zr2O12 and Na3Zr2Si2PO12. We develop and test a training protocol suitable for the computation of diffusion coefficients, which is one of the key properties to be optimized for battery applications, and we find good agreement with previous computations. Our results show that the DeePMD model may be a successful component of a framework to identify novel solid-state electrolytes.

Superior stability and safety are key promises attributed to all-solid-state batteries (ASSBs) containing solid-state electrolyte (SSE) compared to their conventional counterparts utilizing liquid electrolyte. To unleash the full potential of ASSBs, SSE materials that are stable when in contact with the low and high potential electrodes are required. The electrochemical stability window is conveniently used to assess the SSE-electrode interface stability. In the present work, we review the most important methods to compute the SSE stability window. Our analysis reveals that the stoichiometry stability method represents a bridge between HOMO-LUMO method and phase stability method (grand canonical phase diagram). Moreover, we provide computational implementations of these methods for SSE material screening. We compare their results for the relevant Li- and Na-SSE materials LGPS, LIPON, LLZO, LLTO, LATP, LISICON, and NASICON, and we discuss their relation to published experimental stability windows.

We outline the non-perturbative theory of multiple scattering of resonant, intense laser light off a dilute cloud of cold atoms. A combination of master equation and diagrammatic techniques allows, for the first time, a quantitative description of nonlinear diffusive transport as well as of coherent backscattering of the injected electromagnetic field, notwithstanding the exponential growth of Hilbert space with the number of atomic scatterers. As an exemplary application, we monitor the laser light's intensity profile within the medium, the spectrum of the backscattered light and the coherent backscattering peak's height with increasing pump intensity. Our theory establishes a general, microscopic, scalable approach to nonlinear transport phenomena in complex quantum materials., Comment: 33 pages, 21 figures