304 citations · 398 across the 14 of their papers we have counts for
15 papers
Synthesizing like a chemist: an iterative, feedback-driven loop for materials discovery
Fang Sheng, Steven B. Torrisi, Amanda Volk +4
Most computationally predicted materials are never synthesized because conventional synthesis optimization is slow, expertise-dependent, and iterative. Here we present a closed-loo…
Spectra-Scope : A toolkit for automated and interpretable characterization of material properties from spectral data
Amalya C. Johnson, Chris Fajardo, Leena Sansguiri +2
Spectroscopy is a central pillar of materials characterization, providing useful information on properties like structure, composition, or excited state dynamics of a system. Howev…
Short-Range Order and LiTM Probability Maps for Disordered Rocksalt Cathodes
Tzu-chen Liu, Steven B. Torrisi, Chris Wolverton
Short-range order (SRO) in the cation-disordered state is a controlling factor influencing the probability of finding Li tetrahedron clusters in disordered rocksalt (DRX) cat…
Tailored ordering enables high-capacity cathode materials
Tzu-chen Liu, Adolfo Salgado-Casanova, So Yubuchi +7
Newly designed Li-ion battery cathode materials with high capacity and greater flexibility in chemical composition will be critical for the growing electric vehicles market. Cathod…
Anomalous Reversal of Stability in Mo-containing Oxides: A Difficult Case Exhibiting Sensitivity to DFT+U and Distortion
Tzu-chen Liu, Dale Gaines, Hyungjun Kim +3
Accurate predictions of the properties of transition metal oxides using density functional theory (DFT) calculations are essential for the computational design of energy materials.…
Interpretable Multimodal Machine Learning Analysis of X-ray Absorption Near-Edge Spectra and Pair Distribution Functions
Tanaporn Na Narong, Zoe N. Zachko, Steven B. Torrisi +1
We used interpretable machine learning to combine information from multiple heterogeneous spectra: X-ray absorption near-edge spectra (XANES) and atomic pair distribution functions…
Oxygen Vacancy Formation Energy in Metal Oxides: High Throughput Computational Studies and Machine Learning Predictions
Bianca Baldassarri, Jiangang He, Abhijith Gopakumar +5
The oxygen vacancy formation energy () governs defect dynamics and is a useful metric to perform materials selection for a variety of applications. However, density functi…
Complexity of Many-Body Interactions in Transition Metals via Machine-Learned Force Fields from the TM23 Data Set
Cameron J. Owen, Steven B. Torrisi, Yu Xie +6
This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we co…
High-Throughput Design of Atomic Interfaces using InterMatch
Eli Gerber, Steven B. Torrisi, Sara Shabani +6
Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput appro…
Effects of Structural Distortions on the Electronic Structure of T-type Transition Metal Dichalcogenides
Daniel T. Larson, Wei Chen, Steven B. Torrisi +3
Single-layer transition metal dichalcogenides (TMDCs) can adopt two distinct structures corresponding to different coordination of the metal atoms. TMDCs adopting the T-type struct…
Electronic structure calculations of twisted multi-layer graphene superlattices
Georgios A. Tritsaris, Stephen Carr, Ziyan Zhu +6
Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and few-l…
Two-Dimensional Forms of Robust CO Reduction Photocatalysts
Steven B. Torrisi, Arunima K. Singh, Joseph H. Montoya +2
Novel photoelectrocatalysts that use sunlight to power the CO reduction reaction will be crucial for carbon-neutral power and energy-efficient industrial processes. Scalable ph…
On-the-Fly Active Learning of Interpretable Bayesian Force Fields for Atomistic Rare Events
Jonathan Vandermause, Steven B. Torrisi, Simon Batzner +4
Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training effic…
Relaxation and Domain Formation in Incommensurate 2D Heterostructures
Stephen Carr, Daniel Massatt, Steven B. Torrisi +3
We introduce configuration space as a natural representation for calculating the mechanical relaxation patterns of incommensurate two-dimensional (2D) bilayers, bypassing supercell…
Perpendicular laser cooling with a rotating wall potential in a Penning trap
Steven B. Torrisi, Joseph W. Britton, Justin G. Bohnet +1
We investigate the impact of a rotating wall potential on perpendicular laser cooling in a Penning ion trap. By including energy exchange with the rotating wall, we extend previous…