Daniel S. Green

1.0k citations
29 papers · 793 · h-index 14

Impact in

Papers in

Daniel S. Green

28 papers receiving 778 citations

Peers

Daniel S. Green
Comparison fields: 5 of 91
  • Condensed Matter Physics 302
  • Immunology 272
  • Immunology and Allergy 45
  • Electronic, Optical and Magnetic Materials 133
  • Electrical and Electronic Engineering 251
Replace Masahiro Kitano with:
Masahiro Kitano Japan
Zhen Xiong China
Takaki Yamamoto Japan
Naiyin Wang Australia
Catherine A. Cox United States
Shuhei Hashimoto Japan
M. Ikebe Japan
Isabelle Meunier France
James M. Gordon United States
Yan‐Jun Liu China
Daniel S. Green relative to Masahiro Kitano Japan Masahiro Kitano's profile →
Citations per field
00.5×3.2×
Masahiro Kitano · 1×
Citations per year

Countries citing papers authored by Daniel S. Green

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. Green

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel S. Green. 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 Daniel S. Green. The network helps show where Daniel S. Green may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003157
2 2017131
3 2007108
4 200380
5 201747
6 200839
7 200825
8 201624
9 201823
10 201919
11 201917
12 201217
13 200916
14 201315
15 200413
16 20149
17 20159
18 20028
19 20198
20 20147

About Daniel S. Green

Daniel S. Green is a scholar working on Immunology, Condensed Matter Physics, Electrical and Electronic Engineering, Reproductive Medicine and Electronic, Optical and Magnetic Materials, having authored 29 papers that have together received 793 indexed citations. Recurring topics across this work include GaN-based semiconductor devices and materials (8 papers), Immune Cell Function and Interaction (8 papers), Immune cells in cancer (6 papers), Radio Frequency Integrated Circuit Design (4 papers), Ga2O3 and related materials (3 papers), 3D IC and TSV technologies (3 papers), Ovarian cancer diagnosis and treatment (3 papers) and Semiconductor materials and devices (3 papers). The work is most often cited by research in Condensed Matter Physics (302 citations), Immunology (272 citations), Immunology and Allergy (45 citations), Electronic, Optical and Magnetic Materials (133 citations) and Electrical and Electronic Engineering (251 citations). Daniel S. Green has collaborated with scholars based in United States, Czechia and Australia. Frequent co-authors include Howard A. Young, Julio C. Valencia, Steven P. DenBaars, S. Keller, Umesh K. Mishra, William W. Cruikshank, Hardy Kornfeld, P. Kozodoy, Haijiang Yu and Huili Grace Xing. Their work appears in journals such as The Journal of Immunology, Journal of Interferon & Cytokine Research, Journal of Translational Medicine, Cytokine and Japanese Journal of Applied Physics.

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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