Gary Tom

1.3k citations
18 papers · 576 · 1 hit paper · h-index 11

Impact in

Papers in

Gary Tom

16 papers receiving 569 citations

Gary Tom's Hit Papers

Self-Driving Laboratories for Chemistry and Materials Science 2024 · 269 citations
2690+1Years since publication50100150200250

Peers

Gary Tom
Comparison fields: 5 of 79
  • Materials Chemistry 299
  • Computational Theory and Mathematics 78
  • Information Systems and Management 22
  • Biomedical Engineering 104
  • Atomic and Molecular Physics, and Optics 73
Replace Cyrille Lavigne with:
Cyrille Lavigne Canada
Cher Tian Ser Canada
Ganesh Sivaraman United States
Steven B. Torrisi United States
Max C. Gallant United States
Andrés Aguilar‐Granda Mexico
Luca Torresi Germany
Bernardus Rendy United States
Jiechun Liang China
Jenya Vestfrid Canada
Gary Tom relative to Cyrille Lavigne Canada Cyrille Lavigne's profile →
Citations per field
00.5×1.5×2.5×
Cyrille Lavigne · 1×
Citations per year

Countries citing papers authored by Gary Tom

Since Specialization
Citations

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

Fields of papers citing papers by Gary Tom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gary Tom, 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 Gary Tom Line = papers co-authored together Gary Tom links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1
Self-Driving Laboratories for Chemistry and Materials Science
Hit paper breakdown →
2024269
2 201975
3 202447
4 202138
5 202327
6 202225
7 202517
8 202514
9 202414
10 201813
11 202410
12 20229
13 20248
14 20257
15 20251
16 20031
17 20251
18 20250

About Gary Tom

Gary Tom is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Biomedical Engineering, Electrical and Electronic Engineering and Molecular Biology, having authored 18 papers that have together received 576 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (6 papers), Molecular Junctions and Nanostructures (3 papers), Organic Electronics and Photovoltaics (2 papers), Luminescence and Fluorescent Materials (2 papers), Various Chemistry Research Topics (2 papers), Analytical Chemistry and Chromatography (2 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (2 papers). The work is most often cited by research in Materials Chemistry (299 citations), Computational Theory and Mathematics (78 citations), Information Systems and Management (22 citations), Biomedical Engineering (104 citations) and Atomic and Molecular Physics, and Optics (73 citations). Gary Tom has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Alán Aspuru‐Guzik, Sergio Pablo‐García, Ella Miray Rajaonson, Han Hao, Stanley Lo, Yang Cao, Gun Deniz Akkoc, Felix Strieth‐Kalthoff, Sterling G. Baird and Kourosh Darvish. Their work appears in journals such as Advanced Materials, Chemical Reviews, Journal of Materials Chemistry A, Journal of the American Chemical Society and The Journal of Physical Chemistry C.

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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