Brian DeCost

5.2k citations
48 papers · 3.1k · 2 hit papers · h-index 21

Impact in

Papers in

    • Machine Learning in Materials Science 32
    • X-ray Diffraction in Crystallography 11
    • Electronic and Structural Properties of Oxides 6
    • Corrosion Behavior and Inhibition 3
    • High Entropy Alloys Studies 5
    • Mineral Processing and Grinding 3

Brian DeCost

47 papers receiving 3.0k citations

Brian DeCost's Hit Papers

Recent advances and applications of deep learning methods in materials science 2022 · 701 citations
7010+1+3Years since publication200400600

Peers

Brian DeCost
Comparison fields: 5 of 143
  • Metals and Alloys 129
  • Structural Biology 61
  • Materials Chemistry 2.0k
  • Computational Theory and Mathematics 353
  • Surfaces, Coatings and Films 136
Replace Kamal Choudhary with:
Kamal Choudhary United States
Prasanna V. Balachandran United States
Francesca Tavazza United States
Rohit Batra United States
Logan Ward United States
Chiho Kim United States
Jonathan Schmidt Germany
Jason Hattrick‐Simpers United States
Arun Mannodi‐Kanakkithodi United States
Daniel W. Davies United Kingdom
Brian DeCost relative to Kamal Choudhary United States Kamal Choudhary's profile →
Citations per field
00.5×1.5×
Kamal Choudhary · 1×
Citations per year

Countries citing papers authored by Brian DeCost

Since Specialization
Citations

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

Fields of papers citing papers by Brian DeCost

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Recent advances and applications of deep learning methods in materials science
Hit paper breakdown →
2022701
2
Atomistic Line Graph Neural Network for improved materials property predictions
Hit paper breakdown →
2021454
3 2019260
4 2019246
5 2015218
6 2017165
7 2018122
8 2016102
9 202376
10 202375
11 202365
12 201764
13 201762
14 202453
15 201647
16 202233
17 201628
18 201726
19 202325
20 202425

About Brian DeCost

Brian DeCost is a scholar working on Materials Chemistry, Mechanical Engineering, Computational Theory and Mathematics, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 3.1k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (32 papers), X-ray Diffraction in Crystallography (11 papers), Computational Drug Discovery Methods (10 papers), Electronic and Structural Properties of Oxides (6 papers), High Entropy Alloys Studies (5 papers), High-Temperature Coating Behaviors (3 papers), Mineral Processing and Grinding (3 papers) and Corrosion Behavior and Inhibition (3 papers). The work is most often cited by research in Metals and Alloys (129 citations), Structural Biology (61 citations), Materials Chemistry (2.0k citations), Computational Theory and Mathematics (353 citations) and Surfaces, Coatings and Films (136 citations). Brian DeCost has collaborated with scholars based in United States, Canada and Egypt. Frequent co-authors include Kamal Choudhary, Elizabeth A. Holm, Francesca Tavazza, Toby Francis, Ankit Agrawal, Alok Choudhary, Shyue Ping Ong, Simon J. L. Billinge, Ryan Cohn and Anubhav Jain. Their work appears in journals such as npj Computational Materials, Matter, Communications Materials, Computational Materials Science and JOM.

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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