Steven B. Torrisi

941 total citations
21 papers, 619 citations indexed

About

Steven B. Torrisi is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Steven B. Torrisi has authored 21 papers receiving a total of 619 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Materials Chemistry, 7 papers in Electrical and Electronic Engineering and 3 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Steven B. Torrisi's work include Machine Learning in Materials Science (12 papers), Electronic and Structural Properties of Oxides (6 papers) and Electrocatalysts for Energy Conversion (3 papers). Steven B. Torrisi is often cited by papers focused on Machine Learning in Materials Science (12 papers), Electronic and Structural Properties of Oxides (6 papers) and Electrocatalysts for Energy Conversion (3 papers). Steven B. Torrisi collaborates with scholars based in United States, Switzerland and Iran. Steven B. Torrisi's co-authors include Efthimios Kaxiras, Paul Cazeaux, Mitchell Luskin, Stephen Carr, Daniel Massatt, Joseph H. Montoya, Santosh K. Suram, Linda Hung, Matthew R. Carbone and Yang Ha and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and Energy & Environmental Science.

In The Last Decade

Steven B. Torrisi

21 papers receiving 602 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Steven B. Torrisi United States 12 463 171 119 92 61 21 619
Miriam Brafman United States 3 605 1.3× 322 1.9× 49 0.4× 80 0.9× 69 1.1× 3 910
Sebastiaan P. Huber Switzerland 10 411 0.9× 117 0.7× 64 0.5× 34 0.4× 63 1.0× 16 543
Matthew R. Carbone United States 12 381 0.8× 108 0.6× 60 0.5× 43 0.5× 95 1.6× 39 617
Daniel Schwalbe‐Koda United States 15 743 1.6× 163 1.0× 83 0.7× 80 0.9× 71 1.2× 31 900
Martin Uhrin Switzerland 6 574 1.2× 218 1.3× 70 0.6× 75 0.8× 80 1.3× 7 726
Casper Welzel Andersen Denmark 7 488 1.1× 124 0.7× 45 0.4× 54 0.6× 65 1.1× 11 623
Nina Andrejevic United States 8 253 0.5× 143 0.8× 86 0.7× 121 1.3× 26 0.4× 14 423
Mathias Jørgensen Denmark 16 595 1.3× 175 1.0× 65 0.5× 33 0.4× 37 0.6× 22 728
Yashasvi S. Ranawat Finland 5 538 1.2× 121 0.7× 71 0.6× 55 0.6× 50 0.8× 7 637
Alexander Lindmaa Sweden 5 606 1.3× 116 0.7× 61 0.5× 33 0.4× 50 0.8× 6 683

Countries citing papers authored by Steven B. Torrisi

Since Specialization
Citations

This map shows the geographic impact of Steven B. Torrisi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Steven B. Torrisi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven B. Torrisi more than expected).

Fields of papers citing papers by Steven B. Torrisi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven B. Torrisi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Steven B. Torrisi. The network helps show where Steven B. Torrisi may publish in the future.

Co-authorship network of co-authors of Steven B. Torrisi

This figure shows the co-authorship network connecting the top 25 collaborators of Steven B. Torrisi. A scholar is included among the top collaborators of Steven B. Torrisi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Steven B. Torrisi. Steven B. Torrisi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huang, Jin, Zhe Wang, Jiashun Liang, et al.. (2025). Accelerating the Pace of Oxygen Evolution Reaction Catalyst Discovery through Megalibraries. Journal of the American Chemical Society. 147(34). 30956–30966. 2 indexed citations
2.
Kim, Hyungjun, et al.. (2025). Anomalous reversal of stability in Mo-containing oxides: A difficult case exhibiting sensitivity to DFT+U and distortion. Physical Review Materials. 9(5). 2 indexed citations
3.
Torrisi, Steven B., et al.. (2025). Interpretable multimodal machine learning analysis of X-ray absorption near-edge spectra and pair distribution functions. npj Computational Materials. 11(1). 3 indexed citations
4.
Torrisi, Steven B., et al.. (2024). History-agnostic battery degradation inference. Journal of Energy Storage. 81. 110279–110279. 3 indexed citations
5.
Kang, Stephen Dongmin, Sunny Wang, Huada Lian, et al.. (2024). Data-driven analysis of battery formation reveals the role of electrode utilization in extending cycle life. Joule. 8(11). 3072–3087. 18 indexed citations
6.
Owen, Cameron J., Steven B. Torrisi, Yu Xie, et al.. (2024). Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set. npj Computational Materials. 10(1). 23 indexed citations
7.
Torrisi, Steven B.. (2024). Two-dimensional forms of robust CO2 reduction photocatalysts. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 5 indexed citations
8.
Montoya, Joseph H., Muratahan Aykol, Colin Ophus, et al.. (2024). How the AI-assisted discovery and synthesis of a ternary oxide highlights capability gaps in materials science. Chemical Science. 15(15). 5660–5673. 12 indexed citations
9.
He, Jiangang, et al.. (2023). Oxygen Vacancy Formation Energy in Metal Oxides: High-Throughput Computational Studies and Machine-Learning Predictions. Chemistry of Materials. 35(24). 10619–10634. 25 indexed citations
10.
11.
Torrisi, Steven B., Sara Shabani, Jennifer E. Hoffman, et al.. (2023). High-throughput ab initio design of atomic interfaces using InterMatch. Nature Communications. 14(1). 7921–7921. 8 indexed citations
12.
Stevens, Michaela Burke, Megha Anand, Melissa E. Kreider, et al.. (2022). New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research. Energy & Environmental Science. 15(9). 3775–3794. 31 indexed citations
13.
Marcella, Nicholas, Jin Soo Lim, Anna M. Płonka, et al.. (2022). Decoding reactive structures in dilute alloy catalysts. Nature Communications. 13(1). 832–832. 68 indexed citations
14.
Palizhati, Aini, Steven B. Torrisi, Muratahan Aykol, et al.. (2022). Agents for sequential learning using multiple-fidelity data. Scientific Reports. 12(1). 4694–4694. 21 indexed citations
15.
Montoya, Joseph H., Muratahan Aykol, Abraham Anapolsky, et al.. (2022). Toward autonomous materials research: Recent progress and future challenges. Applied Physics Reviews. 9(1). 30 indexed citations
16.
Torrisi, Steven B., Matthew R. Carbone, Brian A. Rohr, et al.. (2020). Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships. npj Computational Materials. 6(1). 133 indexed citations
17.
Larson, Daniel T., Wei Chen, Steven B. Torrisi, et al.. (2020). Effects of structural distortions on the electronic structure of T-type transition metal dichalcogenides. Physical review. B.. 102(4). 5 indexed citations
18.
Vandermause, Jonathan, Steven B. Torrisi, Simon Batzner, Alexie M. Kolpak, & Boris Kozinsky. (2019). Accelerating atomistic modelling with active learning. Bulletin of the American Physical Society. 2019. 1 indexed citations
19.
Carr, Stephen, Daniel Massatt, Steven B. Torrisi, et al.. (2018). Relaxation and domain formation in incommensurate two-dimensional heterostructures. Physical review. B.. 98(22). 193 indexed citations
20.
Torrisi, Steven B., J. Britton, Justin Bohnet, & J. J. Bollinger. (2016). Perpendicular laser cooling with a rotating-wall potential in a Penning trap. Physical review. A. 93(4). 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Miriam Brafman Breakdown of academic impact, for papers by Sebastiaan P. Huber Breakdown of academic impact, for papers by Matthew R. Carbone Breakdown of academic impact, for papers by Daniel Schwalbe‐Koda Breakdown of academic impact, for papers by Martin Uhrin Breakdown of academic impact, for papers by Casper Welzel Andersen Breakdown of academic impact, for papers by Nina Andrejevic Breakdown of academic impact, for papers by Mathias Jørgensen Breakdown of academic impact, for papers by Yashasvi S. Ranawat Breakdown of academic impact, for papers by Alexander Lindmaa
Rankless by CCL
2026