Corey S. O’Hern

9.4k total citations · 3 hit papers
158 papers, 7.0k citations indexed

About

Corey S. O’Hern is a scholar working on Materials Chemistry, Computational Mechanics and Molecular Biology. According to data from OpenAlex, Corey S. O’Hern has authored 158 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Materials Chemistry, 42 papers in Computational Mechanics and 41 papers in Molecular Biology. Recurrent topics in Corey S. O’Hern's work include Material Dynamics and Properties (66 papers), Granular flow and fluidized beds (40 papers) and Protein Structure and Dynamics (25 papers). Corey S. O’Hern is often cited by papers focused on Material Dynamics and Properties (66 papers), Granular flow and fluidized beds (40 papers) and Protein Structure and Dynamics (25 papers). Corey S. O’Hern collaborates with scholars based in United States, China and United Kingdom. Corey S. O’Hern's co-authors include Andrea J. Liu, Sidney R. Nagel, Leonardo E. Silbert, Mark D. Shattuck, Stephen A. Langer, Carl F. Schreck, Eric R. Dufresne, Robert Behringer, Ning Xu and Jerzy Bławzdziewicz and has published in prestigious journals such as Cell, Physical Review Letters and Advanced Materials.

In The Last Decade

Corey S. O’Hern

152 papers receiving 6.9k citations

Hit Papers

Jamming at zero temperatu... 2002 2026 2010 2018 2003 2013 2002 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Corey S. O’Hern 3.9k 1.8k 1.3k 1.2k 1.1k 158 7.0k
Andrea J. Liu 8.0k 2.1× 2.3k 1.3× 3.2k 2.5× 2.8k 2.4× 1.7k 1.6× 193 13.7k
Eric R. Weeks 5.5k 1.4× 966 0.5× 1.6k 1.3× 2.3k 2.0× 1.2k 1.1× 107 9.5k
Matthieu Wyart 3.2k 0.8× 1.1k 0.6× 1.5k 1.1× 741 0.6× 549 0.5× 100 5.1k
Klaus Mecke 2.5k 0.7× 1.7k 0.9× 766 0.6× 1.6k 1.4× 1.2k 1.1× 137 7.1k
Igor S. Aranson 2.2k 0.6× 2.1k 1.1× 5.8k 4.6× 3.2k 2.8× 1.6k 1.5× 243 11.7k
Wim van Saarloos 1.8k 0.5× 1.6k 0.9× 1.6k 1.2× 766 0.7× 1.6k 1.5× 151 6.5k
Stephan Herminghaus 3.6k 0.9× 4.7k 2.6× 1.7k 1.4× 4.8k 4.1× 1.6k 1.5× 223 13.9k
Ralf Seemann 1.8k 0.5× 2.5k 1.4× 685 0.5× 2.6k 2.2× 424 0.4× 117 6.4k
Dov Levine 3.7k 0.9× 1.5k 0.8× 1.0k 0.8× 437 0.4× 747 0.7× 64 6.3k
Wolfgang Losert 1.1k 0.3× 1.4k 0.8× 496 0.4× 1.3k 1.1× 507 0.5× 243 5.8k

Countries citing papers authored by Corey S. O’Hern

Since Specialization
Citations

This map shows the geographic impact of Corey S. O’Hern'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 Corey S. O’Hern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Corey S. O’Hern more than expected).

Fields of papers citing papers by Corey S. O’Hern

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Corey S. O’Hern. 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 Corey S. O’Hern. The network helps show where Corey S. O’Hern may publish in the future.

Co-authorship network of co-authors of Corey S. O’Hern

This figure shows the co-authorship network connecting the top 25 collaborators of Corey S. O’Hern. A scholar is included among the top collaborators of Corey S. O’Hern 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 Corey S. O’Hern. Corey S. O’Hern 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.
Wang, Dong, Nidhi Pashine, Mark D. Shattuck, et al.. (2025). Evolution of adaptive force chains in reconfigurable granular metamaterials. Soft Matter. 21(30). 6088–6099.
2.
Anda, Jaime de, Sherry L. Kuchma, Shanice S. Webster, et al.. (2024). How P. aeruginosa cells with diverse stator composition collectively swarm. mBio. 15(4). 1 indexed citations
3.
O’Hern, Corey S., et al.. (2024). Modeling the Effects of Varying the Ti Concentration on the Mechanical Properties of Cu–Ti Alloys. ACS Omega. 9(9). 10286–10298. 7 indexed citations
4.
Shattuck, Mark D., et al.. (2024). Mechanical plasticity of cell membranes enhances epithelial wound closure. Physical Review Research. 6(1). 3 indexed citations
5.
Meer, D., et al.. (2024). Flow and clogging of capillary droplets. Soft Matter. 20(40). 8036–8051.
6.
Pashine, Nidhi, et al.. (2023). Universal Mechanical Polycomputation in Granular Matter. Proceedings of the Genetic and Evolutionary Computation Conference. 193–201. 1 indexed citations
7.
Wang, Philip, et al.. (2021). Shear response of granular packings compressed above jamming onset. Physical review. E. 103(2). 22902–22902. 11 indexed citations
8.
O’Hern, Corey S., et al.. (2020). Using an Engineering Design Center to Infuse Design Experience into a Mechanical Engineering Program. Papers on Engineering Education Repository (American Society for Engineering Education). 24.1320.1–24.1320.14. 2 indexed citations
9.
Levine, Zachary A., et al.. (2020). Analyses of protein cores reveal fundamental differences between solution and crystal structures. Proteins Structure Function and Bioinformatics. 88(9). 1154–1161. 16 indexed citations
10.
Xie, Yujun, Sungwoo Sohn, Minglei Wang, et al.. (2019). Supercluster-coupled crystal growth in metallic glass forming liquids. Nature Communications. 10(1). 915–915. 43 indexed citations
11.
Jülich, Dörthe, Emilie Guillon, Andrew K. Lawton, et al.. (2019). Organization of Embryonic Morphogenesis via Mechanical Information. Developmental Cell. 49(6). 829–839.e5. 26 indexed citations
12.
Regan, Lynne, et al.. (2018). Comparing side chain packing in soluble proteins, protein‐protein interfaces, and transmembrane proteins. Proteins Structure Function and Bioinformatics. 86(5). 581–591. 7 indexed citations
13.
Williams, Peter, et al.. (2018). Computational models of the role of pectins in plant cell wall structure. Bulletin of the American Physical Society. 2018. 1 indexed citations
14.
Bosenberg, Marcus, et al.. (2016). Modeling the Spatiotemporal Evolution of the Melanoma Tumor Microenvironment. Bulletin of the American Physical Society. 2016. 1 indexed citations
15.
Bosenberg, Marcus, et al.. (2015). Computational modeling of the spatiotemporal dynamics of cancer stem cells. Bulletin of the American Physical Society. 2015. 1 indexed citations
16.
Parry, Bradley R., Ivan V. Surovtsev, Matthew T. Cabeen, et al.. (2014). Cellular Metabolism Fluidizes the Glassy Bacterial Cytoplasm. Biophysical Journal. 106(2). 313a–313a.
17.
O’Hern, Corey S., et al.. (2013). The power of hard-sphere models for proteins: Understanding side-chain conformations and predicting thermodynamic stability. Bulletin of the American Physical Society. 2013. 1 indexed citations
18.
O’Hern, Corey S., et al.. (2012). The Power of Hard-Sphere Models: Explaining Side-Chain Dihedral Angle Distributions of Thr and Val. Biophysical Journal. 102(10). 2345–2352. 27 indexed citations
19.
Lois, Gregg, Jerzy Bławzdziewicz, & Corey S. O’Hern. (2009). The Free Energy Reaction Path Theory of Reliable Protein Folding. Biophysical Journal. 96(3). 589a–590a. 1 indexed citations
20.
Lois, Gregg, Jerzy Bławzdziewicz, & Corey S. O’Hern. (2008). Reliable Protein Folding on Complex Energy Landscapes: The Free Energy Reaction Path. Biophysical Journal. 95(6). 2692–2701. 3 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.

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