Benjamin A. Helfrecht

607 citations
14 papers · 160 indexed · h-index 8
Topics
Machine Learning in Materials Science (4 papers)Computational Drug Discovery Methods (4 papers)Graphene research and applications (2 papers)
Journals
Nature MaterialsSHILAP Revista de lepidopterologíaJournal of Applied Physics

In The Last Decade

Benjamin A. Helfrecht

12 papers receiving 153 citations

Peers

Benjamin A. Helfrecht
Comparison fields: 5 of 38
  • Electrical and Electronic Engineering 90
  • Materials Chemistry 84
  • Electronic, Optical and Magnetic Materials 33
  • Atomic and Molecular Physics, and Optics 21
  • Polymers and Plastics 13
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Chidozie Onwudinanti Netherlands
Kalyan Jyoti Sarkar India
Jiajie Qi China
Jimin Shang China
Fangqi Liu China
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Ruiwen Xue China
Jure Strle Slovenia
Luis Barroso-Luque United States
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Citations per field
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Citations per year

Countries citing papers authored by Benjamin A. Helfrecht

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin A. Helfrecht

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin A. Helfrecht. 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 Benjamin A. Helfrecht. The network helps show where Benjamin A. Helfrecht may publish in the future.

Co-authorship network of co-authors of Benjamin A. Helfrecht

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin A. Helfrecht. A scholar is included among the top collaborators of Benjamin A. Helfrecht based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Benjamin A. Helfrecht. Benjamin A. Helfrecht is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 0
2 7
3 9
4 4
5 3
6 7
7 0
8 61
9 1
10 33
11 6
12 9
13 8
14 12

About Benjamin A. Helfrecht

Benjamin A. Helfrecht is a scholar working on Computational Theory and Mathematics, Molecular Medicine and Materials Chemistry, having authored 14 papers that have together received 160 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (4 papers) and Graphene research and applications (2 papers). The work is most often cited by research in Materials Chemistry (84 citations), Electronic, Optical and Magnetic Materials (33 citations) and Electrical and Electronic Engineering (90 citations). Benjamin A. Helfrecht has collaborated with scholars based in United States, Switzerland and Hong Kong. Frequent co-authors include Alejandro Strachan, Nicolas Onofrio, Mahalingam Balasubramanian, Zhihong Chen, Shengjiao Zhang, Dana Weinstein, Chun‐Li Lo, Yanbo He, Ernesto E. Marinero and Michele Ceriotti. Their work appears in journals such as Nature Materials, SHILAP Revista de lepidopterología and 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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