25 citations · 57 across the 8 of their papers we have counts for
8 papers
Stability and Structure of Binary Metal Hydrides under Pressure, Electrochemical Potential and Combined Pressure-Electrochemistry
Mgcini Keith Phuthi, Pin-Wen Guan, Russell J. Hemley +1
Metal hydrides can be tuned to have a diverse range of properties and find applications in hydrogen storage and superconductivity. Finding methods to control the synthesis of hydri…
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…
Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials
Mgcini Keith Phuthi, Archie Mingze Yao, Simon Batzner +4
The properties of lithium metal are key parameters in the design of lithium ion and lithium metal batteries. They are difficult to probe experimentally due to the high reactivity a…
Differentiable thermodynamic modeling
Pin-Wen Guan
A new framework of thermodynamic modeling is proposed by introducing the concept of differentiable programming, where all the thermodynamic observables including both thermochemica…
MeltNet: Predicting alloy melting temperature by machine learning
Pin-Wen Guan, Venkatasubramanian Viswanathan
Thermodynamics is fundamental for understanding and synthesizing multi-component materials, while efficient and accurate prediction of it still remain urgent and challenging. As a…
: Combining pressure and electrochemistry to synthesize superhydrides
Pin-Wen Guan, Russell J. Hemley, Venkatasubramanian Viswanathan
Recently, superhydrides have been computationally identified and subsequently synthesized with a variety of metals at very high pressures. In this work, we evaluate the possibility…
Uncertainty Quantification of First Principles Computational Phase Diagram Predictions of Li-Si System Via Bayesian Sampling
Ying Yuan, Gregory Houchins, Pin-Wen Guan +1
In this work, an assessment of the CALPHAD method trained on only density functional theory (DFT) data is performed for the Li-Si binary system, as a case study. Using a parameter…
Uncertainty Quantification of DFT-predicted Finite Temperature Thermodynamic Properties within the Debye Model
Pinwen Guan, Gregory Houchins, Venkatasubramanian Viswanathan
Finite-temperature effects can be included by calculating the vibrations properties and this can greatly improve the fidelity of computational screening. An important challenge for…