Nathaniel Feldberg

431 citations
10 papers · 372 · h-index 8

Impact in

    • Machine Learning in Materials Science
    • MXene and MAX Phase Materials
    • ZnO doping and properties
    • Electronic and Structural Properties of Oxides
    • Boron and Carbon Nanomaterials Research
    • Metal and Thin Film Mechanics

Papers in

    • Machine Learning in Materials Science 7
    • Boron and Carbon Nanomaterials Research 2
    • Graphene research and applications 2
    • ZnO doping and properties 1
    • Metal and Thin Film Mechanics 6

Nathaniel Feldberg

10 papers receiving 369 citations

Peers

Nathaniel Feldberg
Comparison fields: 5 of 18
  • Materials Chemistry 355
  • Mechanics of Materials 164
  • Inorganic Chemistry 75
  • Condensed Matter Physics 38
  • Electrical and Electronic Engineering 111
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Citations per year

Countries citing papers authored by Nathaniel Feldberg

Since Specialization
Citations

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

Fields of papers citing papers by Nathaniel Feldberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 2013104
2 2015101
3 201639
4 201937
5 201430
6 201220
7 201715
8 201914
9 20206
10 20196

About Nathaniel Feldberg

Nathaniel Feldberg is a scholar working on Materials Chemistry, Mechanics of Materials, Condensed Matter Physics, Electronic, Optical and Magnetic Materials and Inorganic Chemistry, having authored 10 papers that have together received 372 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (7 papers), Metal and Thin Film Mechanics (6 papers), Ga2O3 and related materials (3 papers), GaN-based semiconductor devices and materials (3 papers), Inorganic Chemistry and Materials (3 papers), Boron and Carbon Nanomaterials Research (2 papers), Graphene research and applications (2 papers) and ZnO doping and properties (1 paper). The work is most often cited by research in Materials Chemistry (355 citations), Mechanics of Materials (164 citations), Inorganic Chemistry (75 citations), Condensed Matter Physics (38 citations) and Electrical and Electronic Engineering (111 citations). Nathaniel Feldberg has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include S. M. Durbin, T. D. Veal, David O. Scanlon, W. M. Linhart, P. A. Stampe, R. J. Kennedy, Louis F. J. Piper, Nicholas F. Quackenbush, Roy Clarke and Laurie J. Phillips. Their work appears in journals such as Nanotechnology, Journal of Electronic Materials, Advanced Energy Materials, Applied Physics Letters and AIP Advances.

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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