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Size-Dependent Chemomechanical Failure of Sulfide Solid Electrolyte Particles during Electrochemical Reaction with Lithium
The very high ionic conductivity of Li 10 GeP 2 S 12 (LGPS) solid electrolyte (SE) makes it a promising candidate SE for solid-state batteries in electrical vehicles. However, chemomechanical failure, whose mechanism remains unclear, has plagued its widespread applications. Here, we report in situ imaging lithiation-induced failure of LGPS SE. In this work, we revealed a strong size effect in the chemomechanical failure of LGPS particles: namely, when the particle size is greater than 3 μm, fracture/pulverization occurred; when the particle size is between 1 and 3 μm, microcracks emerged; when the particle size is less than 1 μm, no chemomechanical failure was observed. This strong size effect is interpreted by the interplay between elastic energy storage and dissipation. Our finding has important implications for the design of high-performance LGPS SE, for example, by reducing the particle size to less than 1 μm the chemomechanical failure of LGPS SE can be mitigated.
Approach to Evaluating Reorganization Energies of Interfacial Electrochemical Reactions
Reaction rate coefficients for electron-transfer processes at the electrode–electrolyte interface are commonly estimated by using the Butler–Volmer equation, but their values are inaccurate beyond a few tenths of volts of overpotential. The Marcus–Hush–Chidsey (MHC) formalism yields correct asymptotic behavior of the rate coefficients vs applied overpotential but has complex dependencies on the redox system’s intrinsic parameters, which can be difficult to model or measure. In this work, we bridge the two kinetics formalisms to estimate the reorganization energy, one of the important parameters for the MHC formalism, and investigate its dependence on other intrinsic parameters such as activation barriers, electronic coupling strength, and the density of states of the electrode surface. We examine the sensitivity of the reorganization energy to these parameters, establish some general relationships for accurately predicting rate coefficients using the MHC formalism over a wide range of applied overpotentials, and compare this approach to calculating MHC rate constants with other empirical approaches for the mechanisms of CO 2 reduction on different metal electrode surfaces.
On the Temperature Sensitivity of Electrochemical Reaction Thermodynamics
Not Available
Electrical decoupling of microbial electrochemical reactions enables spontaneous H 2 evolution
The uphill reaction of H 2 evolution was made possible by harvesting wastewater energy using electrical circuiting.
Predictive stochastic analysis of massive filter-based electrochemical reaction networks
New methods for chemical reaction network construction and analysis enable the discovery of novel products and mechanisms in battery electrochemistry.
Machine learning for design principles for single atom catalysts towards electrochemical reactions
Machine learning (ML) integrated density functional theory (DFT) calculations have recently been used to accelerate the design and discovery of heterogeneous catalysts such as single atom catalysts (SACs) through the establishment of deep structure–activity relationships. Here, this review provides recent progress in the ML-aided rational design of heterogeneous catalysts with the focus on SACs in terms of structure–activity relationships, feature importance analysis, high-throughput screening, stability, and metal–support interactions for electrochemistry. Support vector machine (SVM), random forest regression (RFR), and deep neural networks (DNN) along with atomic properties are mainly used for the design of SACs. The ML results have shown that the number of electrons in the d orbital, oxide formation enthalpy, ionization energy, Bader charge, d-band center, and enthalpy of vaporization are mainly the most important parameters for the defining of the structure–activity relationships for electrochemistry. However, the black-box nature of ML techniques occasionally makes a physical interpretation of descriptors, such as the Bader charge, d-band center, and enthalpy of vaporization, non-trivial. At the current stage, ML application is limited by the lack of a large and high-quality database. Future prospects for the development of a large database and a generalized ML algorithm for SAC design are discussed to give insights for further studies in this field.
Electrochemical Reactions – Fundamentals Mapped from the Atomic to the Macroscopic Scale
Electrochemistry more important than ever Electrocatalysis great prospects Enhanced selective vs thermocatalysis More benign conditions New chemical processes needed for, e.g., sustainability Demand for tailor-made catalysts Atomic scale modeling useful guide Surge to develop methods that can capture realistic systems
Reactor with advanced architecture for the electrochemical reaction of CO2, CO, and other chemical compounds
A platform technology that uses a novel membrane electrode assembly including a cathode layer comprising a reduction catalyst and a first anion-and-cation-conducting polymer, an anode layer comprising an oxidation catalyst and a cation-conducting polymer, a membrane layer comprising a cation-conducting polymer, the membrane layer arranged between the cathode layer and the anode layer and conductively connecting the cathode layer and the anode layer, in a COx reduction reactor has been developed. The reactor can be used to synthesize a broad range of carbon-based compounds from carbon dioxide.
Reactor with advanced architecture for the electrochemical reaction of CO2, CO and other chemical compounds
A platform technology that uses a novel membrane electrode assembly, including a cathode layer, an anode layer, a membrane layer arranged between the cathode layer and the anode layer, the membrane conductively connecting the cathode layer and the anode layer, in a COx reduction reactor has been developed. The reactor can be used to synthesize a broad range of carbon-based compounds from carbon dioxide and other gases containing carbon.
Investigating Electrochemical Reactions of MnO2 and Mn Ions in Acidic Electrolyte.
Abstract not provided.
Reactor with advanced architecture for the electrochemical reaction of CO2, CO, and other chemical compounds
A platform technology that uses a novel membrane electrode assembly including a cathode layer comprising a reduction catalyst and a first anion-and-cation-conducting polymer, an anode layer comprising an oxidation catalyst and a cation-conducting polymer, a membrane layer comprising a cation-conducting polymer, the membrane layer arranged between the cathode layer and the anode layer and conductively connecting the cathode layer and the anode layer, in a COx reduction reactor has been developed. The reactor can be used to synthesize a broad range of carbon-based compounds from carbon dioxide.
Boosting electrochemical reaction and suppressing phase transition with a high-entropy O3-type layered oxide for sodium-ion batteries
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Reactor with advanced architecture for the electrochemical reaction of CO2, CO and other chemical compounds
A platform technology that uses a novel membrane electrode assembly, including a cathode layer, an anode layer, a membrane layer arranged between the cathode layer and the anode layer, the membrane conductively connecting the cathode layer and the anode layer, in a CO x reduction reactor has been developed. The reactor can be used to synthesize a broad range of carbon-based compounds from carbon dioxide and other gases containing carbon.
Electrochemical kinetics of parallel reactions
Electrochemical oxidation of molecular parallel reactions
Surrogate Model Development of Spent Fuel Degradation for Repository Performance Assessment
In model simulations of deep geologic repositories, UO 2 fuel matrix degradation typically begins as soon as the waste package breaches and groundwater contacts the fuel surface. The initial degradation rate depends on the timing of these events, burnup of the fuel, temperature, and concentrations of dissolved reactants. Estimating the initial rate of degradation is fairly straightforward, but as UO 2 corrosion products precipitate on the fuel surface and the movement of dissolved species between the fuel surface and environment is impeded by the precipitated solids, the rate is more difficult to quantify. At that point, calculating the degradation rate becomes a reactive-transport problem in which a large number of equations must be solved by iteration for a large number of grid cells at each time step. The consequence is that repository simulations, which are already expensive, become much more expensive, especially when hundreds or thousands of waste packages breach. The Fuel Matrix Degradation (FMD) model is the process model of the Spent Fuel and Waste Science and Technology (SFWST) campaign of the US Department of Energy (DOE). It calculates spent fuel degradation rates as a function of radiolysis, redox reactions, electrochemical reactions, alteration layer growth, and diffusion of reactants through the alteration layer. Like other similar fuel degradation process models, it is a complicated model requiring a large number of calculations and iterations at each time step.