Scott Broderick

1.8k total citations
84 papers, 1.4k citations indexed

About

Scott Broderick is a scholar working on Materials Chemistry, Biomedical Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Scott Broderick has authored 84 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Materials Chemistry, 28 papers in Biomedical Engineering and 13 papers in Computational Theory and Mathematics. Recurrent topics in Scott Broderick's work include Machine Learning in Materials Science (28 papers), Advanced Materials Characterization Techniques (26 papers) and Computational Drug Discovery Methods (10 papers). Scott Broderick is often cited by papers focused on Machine Learning in Materials Science (28 papers), Advanced Materials Characterization Techniques (26 papers) and Computational Drug Discovery Methods (10 papers). Scott Broderick collaborates with scholars based in United States, Chile and Algeria. Scott Broderick's co-authors include Krishna Rajan, Krishna Rajan, Balaji Narasimhan, H. Aourag, Michael J. Wannemuehler, Amanda E. Ramer‐Tait, Latrisha K. Petersen, Susan B. Sinnott, Somnath Datta and Mahendra K. Sunkara and has published in prestigious journals such as Nature Communications, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.

In The Last Decade

Scott Broderick

83 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Scott Broderick United States 22 790 260 228 227 211 84 1.4k
Stefan Rühl United States 30 1.4k 1.8× 245 0.9× 719 3.2× 424 1.9× 382 1.8× 85 3.9k
Y. Rosenberg Israel 13 459 0.6× 111 0.4× 926 4.1× 495 2.2× 77 0.4× 17 2.0k
Steven Johnson United Kingdom 23 225 0.3× 462 1.8× 455 2.0× 857 3.8× 140 0.7× 125 2.0k
Pascal Lenormand France 27 593 0.8× 212 0.8× 797 3.5× 335 1.5× 183 0.9× 78 2.4k
Trevor Hinkley United Kingdom 13 277 0.4× 362 1.4× 371 1.6× 81 0.4× 25 0.1× 16 1.3k
Yuan‐Chih Chang Taiwan 34 599 0.8× 833 3.2× 996 4.4× 573 2.5× 148 0.7× 99 3.3k
Liancheng Wang China 35 1.2k 1.6× 352 1.4× 64 0.3× 746 3.3× 114 0.5× 115 3.5k
Mohammed Shahabuddin Saudi Arabia 30 504 0.6× 207 0.8× 788 3.5× 662 2.9× 881 4.2× 100 3.2k
Yufeng Cai China 19 202 0.3× 591 2.3× 222 1.0× 429 1.9× 33 0.2× 37 1.8k
Tomohiro Koyama Japan 28 600 0.8× 133 0.5× 236 1.0× 534 2.4× 134 0.6× 133 2.5k

Countries citing papers authored by Scott Broderick

Since Specialization
Citations

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

Fields of papers citing papers by Scott Broderick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott Broderick. 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 Scott Broderick. The network helps show where Scott Broderick may publish in the future.

Co-authorship network of co-authors of Scott Broderick

This figure shows the co-authorship network connecting the top 25 collaborators of Scott Broderick. A scholar is included among the top collaborators of Scott Broderick 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 Scott Broderick. Scott Broderick 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.
Islam, Md Tohidul, et al.. (2025). Enhanced modeling of electronic structure – Mechanical property relationships in high-entropy alloys through data driven analysis. Materials Today Communications. 47. 113112–113112. 1 indexed citations
2.
Forrester, Michael, et al.. (2025). Data-Driven Modeling and Design of Sustainable High Tg Polymers. International Journal of Molecular Sciences. 26(6). 2743–2743. 4 indexed citations
3.
Islam, Md Tohidul, et al.. (2024). Machine Learning Accelerated Design of High-Temperature Ternary and Quaternary Nitride Superconductors. Applied Sciences. 14(20). 9196–9196. 3 indexed citations
4.
Islam, Md Tohidul, et al.. (2023). Data-driven design for enhanced efficiency of Sn-based perovskite solar cells using machine learning. SHILAP Revista de lepidopterología. 1(4). 10 indexed citations
5.
Mullis, Brian, et al.. (2023). Midshaft clavicle fractures: is anterior plating an acceptable alternative to superior plating?. European Journal of Orthopaedic Surgery & Traumatology. 33(8). 3373–3377. 5 indexed citations
6.
Broderick, Scott, et al.. (2023). Immunization with a mucosal, post-fusion F/G protein-based polyanhydride nanovaccine protects neonatal calves against BRSV infection. Frontiers in Immunology. 14. 1186184–1186184. 3 indexed citations
7.
Mullis, Adam S., et al.. (2022). Data analytics-guided rational design of antimicrobial nanomedicines against opportunistic, resistant pathogens. Nanomedicine Nanotechnology Biology and Medicine. 48. 102647–102647. 2 indexed citations
8.
Hu, Yong, Scott Broderick, Zipeng Guo, et al.. (2021). Proton switching molecular magnetoelectricity. Nature Communications. 12(1). 4602–4602. 15 indexed citations
9.
Broderick, Scott, et al.. (2021). Exploring the shape of data for discovering patterns in crystal chemistry. MRS Communications. 11(6). 811–817. 1 indexed citations
10.
Broderick, Scott, et al.. (2019). Probabilistic Assessment of Glass Forming Ability Rules for Metallic Glasses Aided by Automated Analysis of Phase Diagrams. Scientific Reports. 9(1). 357–357. 21 indexed citations
11.
Seko, Atsuto, Kazuaki Toyoura, Shunsuke Muto, Teruyasu Mizoguchi, & Scott Broderick. (2018). Progress in nanoinformatics and informational materials science. MRS Bulletin. 43(9). 690–695. 6 indexed citations
12.
Ashton, Michael, Richard G. Hennig, Scott Broderick, Krishna Rajan, & Susan B. Sinnott. (2016). Computational discovery of stableM2AXphases. Physical review. B.. 94(5). 83 indexed citations
13.
Srinivasan, Srikant, et al.. (2015). Automated voxelization of 3D atom probe data through kernel density estimation. Ultramicroscopy. 159. 381–386. 7 indexed citations
14.
Phanse, Yashdeep, Brenda Carrillo‐Conde, Amanda E. Ramer‐Tait, et al.. (2014). A systems approach to designing next generation vaccines: combining α-galactose modified antigens with nanoparticle platforms. Scientific Reports. 4(1). 3775–3775. 25 indexed citations
15.
Narasimhan, Balaji, Kathleen A. Ross, Wuwei Wu, et al.. (2014). Hemagglutinin-based polyanhydride nanovaccines against H5N1 influenza elicit protective virus neutralizing titers and cell-mediated immunity. International Journal of Nanomedicine. 10. 229–229. 42 indexed citations
16.
Broderick, Scott, et al.. (2013). Mapping energetics of atom probe evaporation events through first principles calculations. Ultramicroscopy. 132. 143–151. 21 indexed citations
17.
Ulery, Bret D., Latrisha K. Petersen, Yashdeep Phanse, et al.. (2011). Rational Design of Pathogen-Mimicking Amphiphilic Materials as Nanoadjuvants. Scientific Reports. 1(1). 198–198. 64 indexed citations
18.
Petersen, Latrisha K., Amanda E. Ramer‐Tait, Scott Broderick, et al.. (2011). Activation of innate immune responses in a pathogen-mimicking manner by amphiphilic polyanhydride nanoparticle adjuvants. Biomaterials. 32(28). 6815–6822. 115 indexed citations
19.
Broderick, Scott & Krishna Rajan. (2011). Eigenvalue decomposition of spectral features in density of states curves. Europhysics Letters (EPL). 95(5). 57005–57005. 29 indexed citations
20.
Broderick, Scott, et al.. (2009). Tracking Chemical Processing Pathways in Combinatorial Polymer Libraries via Data Mining. Journal of Combinatorial Chemistry. 12(2). 270–277. 20 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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