213 citations · 417 across the 6 of their papers we have counts for
6 papers
Excess Density as a Descriptor for Electrolyte Solvent Design
Celia Kelly, Emil Annevelink, Adarsh Dave +1
Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes…
Differentiable Modeling and Optimization of Battery Electrolyte Mixtures Using Geometric Deep Learning
Shang Zhu, Bharath Ramsundar, Emil Annevelink +5
Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyt…
Autonomous optimization of nonaqueous battery electrolytes via robotic experimentation and machine learning
Adarsh Dave, Jared Mitchell, Sven Burke +3
In this work, we introduce a novel workflow that couples robotics to machine-learning for efficient optimization of a non-aqueous battery electrolyte. A custom-built automated expe…
AutoMat: Accelerated Computational Electrochemical systems Discovery
Emil Annevelink, Rachel Kurchin, Eric Muckley +17
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and…
Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning
Adarsh Dave, Jared Mitchell, Kirthevasan Kandasamy +5
Innovations in batteries take years to formulate and commercialize, requiring extensive experimentation during the design and optimization phases. We approached the design and sele…
Benchmarking conductivity predictions of the Advanced Electrolyte Model (AEM) for aqueous systems
Adarsh Dave, Kevin L. Gering, Jared M. Mitchell +2
High-concentration aqueous electrolytes have shown promise as candidates for a safer, lower-cost battery system. Ionic conductivity is a key property required in high performing el…