David Gao

1.9k citations
35 papers · 1.5k indexed · 1 hit paper · h-index 16

David Gao

32 papers receiving 1.5k citations

Hit Papers

DScribe: Library of descriptors for machine learning in m...5702019202620212023100200300400500

Peers

David Gao
Comparison fields: 5 of 94
  • Materials Chemistry 857
  • Electrical and Electronic Engineering 759
  • Structural Biology 16
  • Computational Theory and Mathematics 148
  • Atomic and Molecular Physics, and Optics 275
Replace Troy D. Loeffler with:
Troy D. Loeffler United States
Nicola Molinari United States
Sherif Abdulkader Tawfik Australia
Pankaj Rajak United States
Christian J. Long United States
Venkatesh Botu United States
Roman V. Chepulskii United States
Filippo Federici Canova Japan
Yasunobu Ando Japan
Kentaro Kinoshita Japan
David Gao relative to Troy D. Loeffler United States Troy D. Loeffler's profile →
Citations per field
00.5×7.7×
Troy D. Loeffler · 1×
Citations per year

Countries citing papers authored by David Gao

Since Specialization
Citations

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

Fields of papers citing papers by David Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20226
3 20222
4 20211
5 202030
6 20201
7
DScribe: Library of descriptors for machine learning in materials sciencebreakdown →
2019570
8 201850
9 201872
10 201761
11 20171
12 201781
13 20170
14 2017100
15 201655
16 201611
17 201622
18 201210
19 201214
20
18F-RGD-K5: A cyclic triazole-bearing RGD peptide for imaging integrin αvβ3 expression in vivo
20096

About David Gao

David Gao is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Polymers and Plastics and Biomedical Engineering, having authored 35 papers that have together received 1.5k indexed citations. Recurring topics across this work include Molecular Junctions and Nanostructures (7 papers), Semiconductor materials and devices (7 papers), Advanced Memory and Neural Computing (6 papers), Surface Chemistry and Catalysis (6 papers), Electronic and Structural Properties of Oxides (5 papers), Force Microscopy Techniques and Applications (4 papers), Graphene research and applications (4 papers) and Carbon Nanotubes in Composites (4 papers). The work is most often cited by research in Materials Chemistry (857 citations), Electrical and Electronic Engineering (759 citations), Structural Biology (16 citations), Computational Theory and Mathematics (148 citations) and Atomic and Molecular Physics, and Optics (275 citations). David Gao has collaborated with scholars based in United Kingdom, Japan and United States. Frequent co-authors include Alexander L. Shluger, Filippo Federici Canova, Adam S. Foster, Lauri Himanen, Yashasvi S. Ranawat, Patrick Rinke, Eiaki V. Morooka, Manveer Singh Munde, Al-Moatasem El-Sayed and Matthew B. Watkins. Their work appears in journals such as The Journal of Physical Chemistry C, Advanced Materials, Nature Materials, Computer Physics Communications and Journal of Physics Condensed Matter.

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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2026