No abstract

All-solid-state batteries promise significant safety and energy density advantages over liquid-electrolyte batteries. The interface between the cathode and the solid electrolyte is an important contributor to charge transfer resistance. Strong bonding of solid oxide electrolytes and cathodes requires sintering at elevated temperatures. Knowledge of the temperature dependence of the composition and charge transfer properties of this interface is important for determining the ideal sintering conditions. To understand the interfacial decomposition processes and their onset temperatures, model systems of LiCoO2 (LCO) thin films deposited on cubic Al-doped Li7La3Zr2O12 (LLZO) pellets were studied as a function of temperature using interface-sensitive techniques. X-ray photoelectron spectroscopy (XPS), secondary ion mass spectroscopy (SIMS), and energy-dispersive X-ray spectroscopy (EDS) data indicated significant cation interdiffusion and structural changes starting at temperatures as low as 300⁰C. La2Zr2O7 and Li2CO3 were identified as 2 decomposition products after annealing at 500°C by synchrotron X-ray diffraction (XRD). X-ray absorption spectroscopy (XAS) results indicate the presence of also LaCoO3, in addition to La2Zr2O7 and Li2CO3. Based on electrochemical impedance spectroscopy, and depth profiling of the Li distribution upon potentiostatic hold experiments on symmetric LCO|LLZO|LCO cells, the interfaces exhibited significantly increased impedance, up to 8 times that of the as-deposited samples after annealing at 500 o C. Our results indicate that lower-temperature processing conditions, shorter annealing time scales, and CO2-free environments are desirable for obtaining ceramic cathode-electrolyte interfaces that enable fast Li transfer and high capacity.

The results of kinetic tests and ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) show the important role played by a ZnO-copper interface in the generation of CO and the synthesis of methanol from CO hydrogenation. The deposition of nanoparticles of ZnO on Cu(100) and Cu(111), θ < 0.3 monolayer, produces highly active catalysts. The catalytic activity of these systems increases in the sequence: Cu(111) < Cu(100) < ZnO/Cu(111) < ZnO/Cu(100). The structure of the copper substrate influences the catalytic performance of a ZnO-copper interface. Furthermore, size and metal-oxide interactions affect the chemical and catalytic properties of the oxide making the supported nanoparticles different from bulk ZnO. The formation of a ZnO-copper interface favors the binding and conversion of CO into a formate intermediate that is stable on the catalyst surface up to temperatures above 500 K. Alloys of Zn with Cu(111) and Cu(100) were not stable at the elevated temperatures (500-600 K) used for the CO hydrogenation reaction. Reaction with CO oxidized the zinc, enhancing its stability over the copper substrates.

No abstract

Physical neural networks made of analog resistive switching processors are promising platforms for analog computing. State-of-the-art resistive switches rely on either conductive filament formation or phase change. These processes suffer from poor reproducibility or high energy consumption, respectively. Herein, we demonstrate the behavior of an alternative synapse design that relies on a deterministic charge-controlled mechanism, modulated electrochemically in solid-state. The device operates by shuffling the smallest cation, the proton, in a threeterminal configuration. It has a channel of active material, WO 3. A solid proton reservoir layer, PdH x , also serves as the gate terminal. A proton conducting solid electrolyte separates the channel and the reservoir. By protonation/deprotonation, we modulate the electronic conductivity of the channel over seven orders of magnitude, obtaining a continuum of resistance states. Proton intercalation increases the electronic conductivity of WO 3 by increasing both the carrier density and mobility. This switching mechanism offers low energy dissipation, good reversibility, and high symmetry in programming.