Daniel Elkington

583 citations
25 papers · 472 · h-index 13

Impact in

Papers in

Daniel Elkington

25 papers receiving 468 citations

Peers

Daniel Elkington
Comparison fields: 5 of 53
  • Polymers and Plastics 271
  • Bioengineering 68
  • Electrical and Electronic Engineering 360
  • Biomedical Engineering 151
  • Materials Chemistry 108
Replace Oscar Larsson with:
Oscar Larsson Sweden
Nathan A. Cooling Australia
Marcin Kielar Australia
Garrett LeCroy United States
P. Anjaneyulu India
Wen-Fang Chou United States
Matteo Parmeggiani Italy
Tom P. A. van der Pol Netherlands
Yuanyuan Zhu China
Jae Gyu Jang South Korea
Daniel Elkington relative to Oscar Larsson Sweden Oscar Larsson's profile →
Citations per field
00.5×3.5×
Oscar Larsson · 1×
Citations per year

Countries citing papers authored by Daniel Elkington

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Elkington

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201490
2 201352
3 201440
4 201538
5 201538
6 201928
7 201626
8 201322
9 201919
10 201917
11 201413
12 202112
13 201612
14 201111
15 201510
16 20149
17 20219
18 20148
19 20117
20 20183

About Daniel Elkington

Daniel Elkington is a scholar working on Electrical and Electronic Engineering, Polymers and Plastics, Biomedical Engineering, Bioengineering and Cellular and Molecular Neuroscience, having authored 25 papers that have together received 472 indexed citations. Recurring topics across this work include Conducting polymers and applications (18 papers), Organic Electronics and Photovoltaics (17 papers), Thin-Film Transistor Technologies (10 papers), Advanced Sensor and Energy Harvesting Materials (6 papers), Analytical Chemistry and Sensors (4 papers), Neuroscience and Neural Engineering (3 papers), Luminescence and Fluorescent Materials (2 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Polymers and Plastics (271 citations), Bioengineering (68 citations), Electrical and Electronic Engineering (360 citations), Biomedical Engineering (151 citations) and Materials Chemistry (108 citations). Daniel Elkington has collaborated with scholars based in Australia, Indonesia and United Kingdom. Frequent co-authors include Paul C. Dastoor, Warwick J. Belcher, Xiaojing Zhou, Nathan A. Cooling, Matthew J. Griffith, Glenn Bryant, Natalie P. Holmes, A. L. D. Kilcoyne, Thomas R. Andersen and Krishna Feron. Their work appears in journals such as Applied Physics Letters, Journal of Colloid and Interface Science, Solar Energy Materials and Solar Cells, IEEE Journal of Selected Topics in Quantum Electronics and Carbon.

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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