Amil Merchant

1.8k total citations · 2 hit papers
5 papers, 1.1k citations indexed

About

Amil Merchant is a scholar working on Materials Chemistry, Industrial and Manufacturing Engineering and Artificial Intelligence. According to data from OpenAlex, Amil Merchant has authored 5 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Materials Chemistry, 1 paper in Industrial and Manufacturing Engineering and 1 paper in Artificial Intelligence. Recurrent topics in Amil Merchant's work include Machine Learning in Materials Science (4 papers), X-ray Diffraction in Crystallography (2 papers) and Fuel Cells and Related Materials (1 paper). Amil Merchant is often cited by papers focused on Machine Learning in Materials Science (4 papers), X-ray Diffraction in Crystallography (2 papers) and Fuel Cells and Related Materials (1 paper). Amil Merchant collaborates with scholars based in United States, United Kingdom and Japan. Amil Merchant's co-authors include Ekin D. Cubuk, Muratahan Aykol, Simon Batzner, Samuel S. Schoenholz, Gowoon Cheon, Tanjin He, Christopher J. Bartel, Bernardus Rendy, Gerbrand Ceder and Matthew J. McDermott and has published in prestigious journals such as Nature, Journal of the American Chemical Society and Nature Computational Science.

In The Last Decade

Amil Merchant

5 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Scaling deep learning for materials discovery

2023 667 citations Amil Merchant, Simon Batzner et al. Nature profile →
An autonomous laboratory for the accelerated synthesis of inorganic materials

2023 451 citations Nathan J. Szymanski, Bernardus Rendy et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Amil Merchant United States	4	740	249	149	120	106	5	1.1k
Nathan J. Szymanski United States	18	807 1.1×	380 1.5×	140 0.9×	68 0.6×	129 1.2×	35	1.2k
Gowoon Cheon United States	9	921 1.2×	432 1.7×	110 0.7×	104 0.9×	89 0.8×	11	1.3k
Hermann Tribukait Switzerland	5	461 0.6×	223 0.9×	137 0.9×	90 0.8×	63 0.6×	6	715
Paul Raccuglia United States	2	872 1.2×	245 1.0×	183 1.2×	198 1.6×	217 2.0×	2	1.3k
Steven K. Kauwe United States	11	743 1.0×	156 0.6×	107 0.7×	185 1.5×	153 1.4×	15	970
Nicola Rankin United Kingdom	5	594 0.8×	183 0.7×	309 2.1×	141 1.2×	108 1.0×	5	1.1k
Philip Adler United Kingdom	5	888 1.2×	253 1.0×	185 1.2×	200 1.7×	217 2.0×	9	1.3k
Vladimir V. Gusev United Kingdom	6	636 0.9×	203 0.8×	279 1.9×	182 1.5×	99 0.9×	25	1.1k
Aurelio Mollo United States	6	876 1.2×	245 1.0×	192 1.3×	198 1.6×	217 2.0×	7	1.4k

Countries citing papers authored by Amil Merchant

Since Specialization

Citations

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

Fields of papers citing papers by Amil Merchant

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amil Merchant

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

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Aykol, Muratahan, Amil Merchant, Simon Batzner, Jennifer N. Wei, & Ekin D. Cubuk. (2024). Predicting emergence of crystals from amorphous precursors with deep learning potentials. Nature Computational Science. 5(2). 105–111. 4 indexed citations

2.

Miura, Akira, Muratahan Aykol, S Kozaki, et al.. (2024). Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico Predictions. Journal of the American Chemical Society. 146(43). 29637–29644. 2 indexed citations

3.

Szymanski, Nathan J., Bernardus Rendy, Rishi E. Kumar, et al.. (2023). An autonomous laboratory for the accelerated synthesis of inorganic materials. Nature. 624(7990). 86–91. 451 indexed citations breakdown →

4.

Merchant, Amil, Simon Batzner, Samuel S. Schoenholz, et al.. (2023). Scaling deep learning for materials discovery. Nature. 624(7990). 80–85. 667 indexed citations breakdown →

5.

Lin, Alexander, et al.. (2019). Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models. Knowledge Discovery and Data Mining. 50–58. 4 indexed citations

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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