Max C. Gallant
Impact in
-
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Electronic and Structural Properties of Oxides
-
- Scientific Computing and Data Management
Papers in
-
- Machine Learning in Materials Science 6
- X-ray Diffraction in Crystallography 4
- Electronic and Structural Properties of Oxides 3
-
- Catalysis and Oxidation Reactions 2
- Co-authors
- Kristin A. Persson (7 shared papers)Matthew J. McDermott (5 shared papers)Anubhav Jain (2 shared papers)Gerbrand Ceder (2 shared papers)Christopher J. Bartel (2 shared papers)Ekin D. Cubuk (1 shared paper)Nathan J. Szymanski (1 shared paper)Haegyeom Kim (1 shared paper)
- Journals
- Nature (2 papers)Advanced Functional Materials (1 paper)ACS Central Science (1 paper)Chemistry of Materials (1 paper)npj Computational Materials (1 paper)
- Partner nations
- United StatesDenmarkSouth Korea
In The Last Decade
Max C. Gallant
8 papers receiving 572 citations
Max C. Gallant's Hit Papers
Peers
Comparison fields: 5 of 81
- Materials Chemistry 347
- Information Systems and Management 37
- Catalysis 29
- Health Informatics 4
- Computational Theory and Mathematics 49
Countries citing papers authored by Max C. Gallant
This map shows the geographic impact of Max C. Gallant'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 Max C. Gallant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Max C. Gallant more than expected).
Fields of papers citing papers by Max C. Gallant
This network shows the impact of papers produced by Max C. Gallant. 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 Max C. Gallant. The network helps show where Max C. Gallant may publish in the future.
Co-authors
The 25 scholars most cited alongside Max C. Gallant, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | An autonomous laboratory for the accelerated synthesis of inorganic materials Hit paper breakdown → | 2023 | 524 |
| 2 | 2024 | 25 | |
| 3 | 2023 | 20 | |
| 4 | 2024 | 9 | |
| 5 | 2025 | 8 | |
| 6 | 2022 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 1 |
About Max C. Gallant
Max C. Gallant is a scholar working on Materials Chemistry, Catalysis, Information Systems and Management, Ocean Engineering and Aerospace Engineering, having authored 8 papers that have together received 593 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (6 papers), X-ray Diffraction in Crystallography (4 papers), Electronic and Structural Properties of Oxides (3 papers), Catalysis and Oxidation Reactions (2 papers), Perovskite Materials and Applications (1 paper), Scientific Computing and Data Management (1 paper), Reservoir Engineering and Simulation Methods (1 paper) and High-Temperature Coating Behaviors (1 paper). The work is most often cited by research in Materials Chemistry (347 citations), Information Systems and Management (37 citations), Catalysis (29 citations), Health Informatics (4 citations) and Computational Theory and Mathematics (49 citations). Max C. Gallant has collaborated with scholars based in United States, Denmark and South Korea. Frequent co-authors include Kristin A. Persson, Matthew J. McDermott, Anubhav Jain, Gerbrand Ceder, Christopher J. Bartel, Ekin D. Cubuk, Nathan J. Szymanski, Haegyeom Kim, Tanjin He and Bernardus Rendy. Their work appears in journals such as Nature, Advanced Functional Materials, ACS Central Science, Chemistry of Materials and npj Computational Materials.
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.