T. Pearson

4.7k total citations · 2 hit papers
9 papers, 517 citations indexed

About

T. Pearson is a scholar working on Electronic, Optical and Magnetic Materials, Materials Chemistry and Condensed Matter Physics. According to data from OpenAlex, T. Pearson has authored 9 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Electronic, Optical and Magnetic Materials, 5 papers in Materials Chemistry and 3 papers in Condensed Matter Physics. Recurrent topics in T. Pearson's work include Magnetism in coordination complexes (5 papers), Lanthanide and Transition Metal Complexes (3 papers) and Advanced NMR Techniques and Applications (2 papers). T. Pearson is often cited by papers focused on Magnetism in coordination complexes (5 papers), Lanthanide and Transition Metal Complexes (3 papers) and Advanced NMR Techniques and Applications (2 papers). T. Pearson collaborates with scholars based in United States, Russia and Saudi Arabia. T. Pearson's co-authors include Danna E. Freedman, Samuel I. Stupp, Balu D. Dherange, Mark D. Levin, Nicholas A. Sather, Mónica Olvera de la Cruz, Víctor López‐Domínguez, Pedram Khalili Amiri, Shuangping Liu and Hang Yuan and has published in prestigious journals such as Science, Journal of the American Chemical Society and Chemistry of Materials.

In The Last Decade

T. Pearson

9 papers receiving 516 citations

Hit Papers

Fast and programmable locomotion of hydrogel-metal hybrid... 2020 2026 2022 2024 2020 2023 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. Pearson United States 7 180 177 170 135 115 9 517
Yajun Su China 14 69 0.4× 32 0.2× 208 1.2× 137 1.0× 182 1.6× 22 482
Jenna A. Bilbrey United States 11 52 0.3× 218 1.2× 102 0.6× 8 0.1× 118 1.0× 21 535
Mengfei Wang Japan 11 84 0.5× 191 1.1× 60 0.4× 14 0.1× 418 3.6× 38 646
Odile Gavat France 9 34 0.2× 164 0.9× 71 0.4× 19 0.1× 184 1.6× 14 385
Mario Palacios‐Corella Spain 13 55 0.3× 30 0.2× 117 0.7× 112 0.8× 229 2.0× 26 436
Rika Matsumoto Japan 12 100 0.6× 160 0.9× 59 0.3× 8 0.1× 384 3.3× 45 551
Jolanta Konieczkowska Poland 15 123 0.7× 104 0.6× 71 0.4× 9 0.1× 338 2.9× 40 543
Tianyi Yao United States 9 49 0.3× 30 0.2× 45 0.3× 51 0.4× 136 1.2× 11 507
Georges J. M. Formon France 8 40 0.2× 245 1.4× 43 0.3× 28 0.2× 109 0.9× 18 481
Kim Kuntze Finland 12 39 0.2× 115 0.6× 69 0.4× 7 0.1× 256 2.2× 18 389

Countries citing papers authored by T. Pearson

Since Specialization
Citations

This map shows the geographic impact of T. Pearson'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 T. Pearson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Pearson more than expected).

Fields of papers citing papers by T. Pearson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Pearson

This figure shows the co-authorship network connecting the top 25 collaborators of T. Pearson. A scholar is included among the top collaborators of T. Pearson 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 T. Pearson. T. Pearson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Pearson, T., et al.. (2023). Aromatic nitrogen scanning by ipso -selective nitrene internalization. Science. 381(6665). 1474–1479. 137 indexed citations breakdown →
2.
Ziebel, Michael E., Lei Sun, T. Pearson, et al.. (2021). Strong Magnetocrystalline Anisotropy Arising from Metal–Ligand Covalency in a Metal–Organic Candidate for 2D Magnetic Order. Chemistry of Materials. 33(22). 8712–8721. 9 indexed citations
3.
Li, Chuang, Hang Yuan, Víctor López‐Domínguez, et al.. (2020). Fast and programmable locomotion of hydrogel-metal hybrids under light and magnetic fields. Science Robotics. 5(49). 244 indexed citations breakdown →
4.
Coste, Scott C., T. Pearson, Alison B. Altman, et al.. (2020). Orbital energy mismatch engenders high-spin ground states in heterobimetallic complexes. Chemical Science. 11(36). 9971–9977. 4 indexed citations
5.
Coste, Scott C., T. Pearson, & Danna E. Freedman. (2019). Magnetic Anisotropy in Heterobimetallic Complexes. Inorganic Chemistry. 58(18). 11893–11902. 25 indexed citations
6.
Beldjoudi, Yassine, Ashwin Narayanan, Indranil Roy, et al.. (2019). Supramolecular Tessellations by a Rigid Naphthalene Diimide Triangle. Journal of the American Chemical Society. 141(44). 17783–17795. 74 indexed citations
7.
Pearson, T. & Danna E. Freedman. (2018). Size Determines Efficacy of Nanoparticle Magnetoresistance. ACS Central Science. 4(9). 1092–1094. 1 indexed citations
8.
Pearson, T., Daniel W. Laorenza, Matthew D. Krzyaniak, Michael R. Wasielewski, & Danna E. Freedman. (2018). Octacyanometallate qubit candidates. Dalton Transactions. 47(34). 11744–11748. 9 indexed citations
9.
Pearson, T., Majed S. Fataftah, & Danna E. Freedman. (2016). Enhancement of magnetic anisotropy in a Mn–Bi heterobimetallic complex. Chemical Communications. 52(76). 11394–11397. 14 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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