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RSC Advances|May 9, 2022
Materials with the CrVO<sub>4</sub> structure type as candidate superprotonic conductorsPandu Wisesa, Chenyang Li, Chuhong Wang, et al.
The Journal of Chemical Physics|February 10, 2020
Machine learning for interatomic potential modelsTim Mueller, Alberto Hernandez, Chuhong Wang
The Journal of Physical Chemistry Letters|December 18, 2024
Overcoming Inaccuracies in Machine Learning Interatomic Potential Implementation for Ionic Vacancy SimulationsPandu Wisesa, Wissam A Saidi
ACS Applied Materials & Interfaces|December 1, 2020
Ionic Conduction through Reaction Products at the Electrolyte-Electrode Interface in All-Solid-State Li<sup>+</sup> BatteriesChuhong Wang, Koutarou Aoyagi, Muratahan Aykol, et al.
Journal of Chemical Information and Modeling|September 19, 2018
The Use of Cluster Expansions To Predict the Structures and Properties of Surfaces and Nanostructured MaterialsLiang Cao, Chenyang Li, Tim Mueller
The Journal of Physical Chemistry Letters|September 22, 2023
Machine-Learning Accelerated First-Principles Accurate Modeling of the Solid-Liquid Phase Transition in MgO under Mantle ConditionsPandu Wisesa, Christopher M Andolina, Wissam A Saidi
The Journal of Physical Chemistry Letters|January 9, 2023
Development and Validation of Versatile Deep Atomistic Potentials for Metal OxidesPandu Wisesa, Christopher M Andolina, Wissam A Saidi
Physical Chemistry Chemical Physics : PCCP|November 6, 2019
Mechanisms for hydrogen evolution on transition metal phosphide catalysts and a comparison to Pt(111)Chenyang Li, Hao Gao, Wan Wan, et al.
ACS Nano|August 31, 2019
Ordered Intermetallic Pd<sub>3</sub>Bi Prepared by an Electrochemically Induced Phase Transformation for Oxygen Reduction ElectrocatalysisDu Sun, Yunfei Wang, Kenneth J T Livi, et al.
Nano Letters|January 14, 2025
Cu-Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and <i>in Situ</i> TEM StudyPandu Wisesa, Meng Li, Matthew T Curnan, et al.
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