324 citations · 649 across the 6 of their papers we have counts for
6 papers
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts
Richard Tran, Janice Lan, Muhammed Shuaibi +14
The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials. One class of materials…
Proton distribution visualization in perovskite nickelate devices utilizing nanofocused X-rays
Ivan A. Zaluzhnyy, Peter O. Sprau, Richard Tran +17
We use a 30-nm x-ray beam to study the spatially resolved properties of a SmNiO-based nanodevice that is doped with protons. The x-ray absorption spectra supported by density-f…
The Breakdown of Mott Physics at VO Surfaces
Matthew J. Wahila, Nicholas F. Quackenbush, Jerzy T. Sadowski +12
Transition metal oxides such as vanadium dioxide (VO), niobium dioxide (NbO), and titanium sesquioxide (TiO) are known to undergo a temperature-dependent metal-insu…
Grain Boundary Properties of Elemental Metals
Hui Zheng, Xiang-Guo Li, Richard Tran +5
The structure and energy of grain boundaries (GBs) are essential for predicting the properties of polycrystalline materials. In this work, we use high-throughput density functional…
Anisotropic work function of elemental crystals
Richard Tran, Xiang-Guo Li, Joseph Montoya +3
The work function is a fundamental electronic property of a solid that varies with the facets of a crystalline surface. It is a crucial parameter in spectroscopy as well as materia…
Accurate Force Field for Molybdenum by Machine Learning Large Materials Data
Chi Chen, Zhi Deng, Richard Tran +3
In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning tech…