Jonathan Schmidt

4.5k citations
33 papers · 3.1k indexed · 1 hit paper · h-index 18

Jonathan Schmidt

32 papers receiving 3.1k citations

Hit Papers

Recent advances and applications of machine learning in s...1.7k201920262021202350010001.5k

Peers

Jonathan Schmidt
Comparison fields: 5 of 161
  • Materials Chemistry 2.0k
  • Computational Theory and Mathematics 334
  • Metals and Alloys 53
  • Structural Biology 29
  • Catalysis 142
Replace Kamal Choudhary with:
Kamal Choudhary United States
Nongnuch Artrith United States
Francesca Tavazza United States
Rohit Batra United States
Yunxing Zuo China
Daniel W. Davies United Kingdom
Chiho Kim United States
Amir Barati Farimani United States
Hugh Cartwright United Kingdom
Luca M. Ghiringhelli Germany
Jonathan Schmidt relative to Kamal Choudhary United States Kamal Choudhary's profile →
Citations per field
00.5×1.6×
Kamal Choudhary · 1×
Citations per year

Countries citing papers authored by Jonathan Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Jonathan Schmidt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Schmidt Line = papers co-authored together Jonathan Schmidt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202449
3 20241
4 20243
5 202314
6 20236
7 202314
8 202313
9 202228
10 202211
11 202122
12 2020247
13 201973
14 20192
15 201919
16
Recent advances and applications of machine learning in solid-state materials sciencebreakdown →
20191698
17 20172
18 2017258
19 2012180
20 19943

About Jonathan Schmidt

Jonathan Schmidt is a scholar working on Physical and Theoretical Chemistry, Catalysis, Materials Chemistry, Inorganic Chemistry and Condensed Matter Physics, having authored 33 papers that have together received 3.1k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (17 papers), X-ray Diffraction in Crystallography (8 papers), Spectroscopy and Quantum Chemical Studies (5 papers), Computational Drug Discovery Methods (4 papers), Inorganic Chemistry and Materials (4 papers), Catalysis and Oxidation Reactions (3 papers), Perovskite Materials and Applications (3 papers) and Photochemistry and Electron Transfer Studies (3 papers). The work is most often cited by research in Materials Chemistry (2.0k citations), Computational Theory and Mathematics (334 citations), Metals and Alloys (53 citations), Structural Biology (29 citations) and Catalysis (142 citations). Jonathan Schmidt has collaborated with scholars based in Germany, United States and Portugal. Frequent co-authors include Miguel A. L. Marques, Silvana Botti, Mário R. G. Marques, Pedro Borlido, John C. Tully, Priya V. Parandekar, Liming Chen, Jingming Shi, Ahmad W. Huran and Fabien Tran. Their work appears in journals such as npj Computational Materials, The Journal of Chemical Physics, Physical review. B., Physical Review A and Chemistry of Materials.

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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