most citedDiscovering Melting Temperature Prediction Models of Inorganic Solids by Combining Supervised and Unsupervised Learning

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci20241 cited

Discovering Melting Temperature Prediction Models of Inorganic Solids by Combining Supervised and Unsupervised Learning

Vahe Gharakhanyan, Luke J. Wirth, Jose A. Garrido Torres +5

The melting temperature is important for materials design because of its relationship with thermal stability, synthesis, and processing conditions. Current empirical and computatio…

cond-mat.mtrl-sci2024

Layered-to-Spinel Phase Transformation in LiNiO from First Principles

Cem Komurcuoglu, Alan C. West, Alexander Urban

The phase transition layered LiNiO to spinel Li(NiO) is a potential degradation pathway in LiNiO-based lithium-ion battery cathodes. We investigated the mec…

cond-mat.mtrl-sci20241 cited

Understanding how off-stoichiometry promotes cation mixing in LiNiO

Cem Komurcuoglu, Yunhao Xiao, Xinhao Li +4

Although LiNiO is chemically similar to LiCoO and offers a nearly identical theoretical capacity, LiNiO and related Co-free Ni-rich cathode materials suffer from degrad…

cond-mat.mtrl-sci2023

Constructing and Compressing Global Moment Descriptors from Local Atomic Environments

Vahe Gharakhanyan, Max Aalto, Aminah Alsoulah +2

Local atomic environment descriptors (LAEDs) are used in the materials science and chemistry communities, for example, for the development of machine learning interatomic potential…

cond-mat.mtrl-sci2023

Atomic Insights into the Oxidative Degradation Mechanisms of Sulfide Solid Electrolytes

Chuntian Cao, Matthew R. Carbone, Cem Komurcuoglu +15

Electrochemical degradation of solid electrolytes is a major roadblock in the development of solid-state batteries, and the formed solid-solid interphase (SSI) plays a key role in…