Kristin A. Persson

63.7k citations
365 papers · 48.2k indexed · 31 hit papers · h-index 100
Topics
Machine Learning in Materials Science (122 papers)Advancements in Battery Materials (112 papers)Advanced Battery Materials and Technologies (100 papers)

In The Last Decade

Kristin A. Persson

354 papers receiving 47.4k citations

Hit Papers

Commentary: The Materials Project: A materials genome app...2010202620152020201320122020201120172.5k5.0k7.5k

Peers

Kristin A. Persson
Comparison fields: 5 of 202
  • Materials Chemistry 27.4k
  • Electrical and Electronic Engineering 25.0k
  • Electronic, Optical and Magnetic Materials 5.7k
  • Automotive Engineering 5.3k
  • Renewable Energy, Sustainability and the Environment 5.1k
Replace Shyue Ping Ong with:
Shyue Ping Ong United States
Ju Li United States
Geoffroy Hautier United States
Anubhav Jain United States
Ying Chen China
Gerbrand Ceder United States
Graeme Henkelman United States
Qing Jiang China
Nigel D. Browning United States
Chris Wolverton United States
Kristin A. Persson relative to Shyue Ping Ong United States Shyue Ping Ong's profile →
Citations per field
00.5×1.5×1.8×
Shyue Ping Ong · 1×
Citations per year

Countries citing papers authored by Kristin A. Persson

Since Specialization
Citations

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

Fields of papers citing papers by Kristin A. Persson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kristin A. Persson

This figure shows the co-authorship network connecting the top 25 collaborators of Kristin A. Persson. A scholar is included among the top collaborators of Kristin A. Persson 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 Kristin A. Persson. Kristin A. Persson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
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4 4
5 12
6 6
7 14
8 30
9 68
10 43
11 14
12 95
13 11
14 36
15 105
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17 297
18 25
19 222
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About Kristin A. Persson

Kristin A. Persson is a scholar working on Materials Chemistry, Catalysis and Inorganic Chemistry, having authored 365 papers that have together received 48.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (122 papers), Advancements in Battery Materials (112 papers) and Advanced Battery Materials and Technologies (100 papers). The work is most often cited by research in Materials Chemistry (27.4k citations), Automotive Engineering (5.3k citations) and Electrical and Electronic Engineering (25.0k citations). Kristin A. Persson has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Gerbrand Ceder, Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, Dan Gunter, William D. Richards, Shreyas Cholia, Stephen Dacek and David Skinner. Their work appears in journals such as Nature, Chemical Reviews and Proceedings of the National Academy of Sciences.

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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