Salt-concentrated electrolytes offer properties beyond conventional dilute electrolytes yet suffer from high cost and viscosity which hinder their practical applications. Introducing a secondary solvent as a diluent could reduce the salt content while maintaining the local solution structure of salt-concentrated electrolytes, giving rise to localized high-concentration electrolytes (LHCEs). Through a comprehensive investigation involving over 500 samples, we find that the dielectric constant of solvent, a widely used parameter for electrolyte design, does not serve as a useful screening criterion for diluents; instead, donor number (DN) is an effective design parameter to achieve LHCE structure�i.e., the primary solvent must have DN > 10 and the diluent must have DN ≤ 10. Based on this simple rule, a new LHCE using lowcost m-fluorotoluene diluent is formulated, enabling high-voltage (>4.6 V) and wide-temperature (−40−100 °C) operation of lithium batteries.
Computational
design of high-quality catalysts targeting specific
operation conditions is a challenging task due to the mechanistic,
structural, and environmental complexities across multiple length
and time scales. A multiscale method of a catalyst design linking ab initio calculations, microkinetics, and multiphysics
modeling was proposed to address this challenge. The chemistry-based
analytical model derived from a microkinetic model assisted by first-principles-based
deep neural networks efficiently bridged zero Kelvin ab initio microscopic descriptors and multiphysics modeling. We applied the
multiscale method to the design of carbon-resistant steam methane
reforming catalysts, successfully identifying a few cost-efficient
bimetallic alloys for CH4 internal reforming solid oxide
fuel cells. The multiphysics modeling demonstrates that catalysts
of relatively low activity such as NiZn are actually beneficial for
fuel efficiency, highlighting the importance of the multiphysics model
for a multiscale computational catalyst design.
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