Christopher M. Collins

868 total citations
38 papers, 609 citations indexed

About

Christopher M. Collins is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Christopher M. Collins has authored 38 papers receiving a total of 609 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Materials Chemistry, 10 papers in Electrical and Electronic Engineering and 8 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Christopher M. Collins's work include Machine Learning in Materials Science (11 papers), Catalysis and Oxidation Reactions (7 papers) and Electronic and Structural Properties of Oxides (6 papers). Christopher M. Collins is often cited by papers focused on Machine Learning in Materials Science (11 papers), Catalysis and Oxidation Reactions (7 papers) and Electronic and Structural Properties of Oxides (6 papers). Christopher M. Collins collaborates with scholars based in United Kingdom, United States and France. Christopher M. Collins's co-authors include Matthew J. Rosseinsky, Matthew S. Dyer, George R. Darling, John B. Claridge, Laurence J. Hardwick, Filipe Braga, V.R. Dhanak, Chi‐Chang Hu, Michael J. Pitcher and David Hesp and has published in prestigious journals such as Nature, Science and Journal of the American Chemical Society.

In The Last Decade

Christopher M. Collins

30 papers receiving 590 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher M. Collins United Kingdom 13 266 229 172 49 48 38 609
S. Pandiarajan India 12 311 1.2× 136 0.6× 108 0.6× 48 1.0× 65 1.4× 71 586
Alexandre Garreau France 14 182 0.7× 276 1.2× 66 0.4× 34 0.7× 49 1.0× 43 560
Jun Geng China 14 608 2.3× 334 1.5× 77 0.4× 41 0.8× 103 2.1× 34 851
L. J. Brown Australia 12 133 0.5× 121 0.5× 67 0.4× 24 0.5× 47 1.0× 25 431
Junjie Li China 16 356 1.3× 319 1.4× 470 2.7× 19 0.4× 32 0.7× 32 786
Alexandre Rocha Paschoal Brazil 15 436 1.6× 83 0.4× 84 0.5× 18 0.4× 96 2.0× 41 614
Imran Khan China 12 568 2.1× 272 1.2× 29 0.2× 34 0.7× 40 0.8× 38 712
Haruyuki Ishii Japan 17 348 1.3× 63 0.3× 102 0.6× 40 0.8× 230 4.8× 63 985
В. В. Соколов Russia 14 439 1.7× 125 0.5× 164 1.0× 6 0.1× 88 1.8× 55 626

Countries citing papers authored by Christopher M. Collins

Since Specialization
Citations

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

Fields of papers citing papers by Christopher M. Collins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher M. Collins. 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 Christopher M. Collins. The network helps show where Christopher M. Collins may publish in the future.

Co-authorship network of co-authors of Christopher M. Collins

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher M. Collins. A scholar is included among the top collaborators of Christopher M. Collins 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 Christopher M. Collins. Christopher M. Collins 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
1.
2.
Antypov, Dmytro, Andrij Vasylenko, Christopher M. Collins, et al.. (2025). Discovery of Crystalline Inorganic Solids in the Digital Age. Accounts of Chemical Research. 58(9). 1355–1365.
3.
4.
Collins, Christopher M., Katie Atkinson, Matthew S. Dyer, et al.. (2024). Exploration of Chemical Space Through Automated Reasoning. Angewandte Chemie International Edition. 64(6). e202417657–e202417657. 2 indexed citations
5.
Carluccio, Giuseppe, et al.. (2024). Comparison of Methods to Improve the Transmit Efficiency for MRgFUS Systems. 134–136.
6.
Han, Guopeng, Luke M. Daniels, Andrij Vasylenko, et al.. (2024). Enhancement of Low Temperature Superionic Conductivity by Suppression of Li Site Ordering in Li7Si2–xGexS7I. Angewandte Chemie International Edition. 63(37). e202409372–e202409372. 4 indexed citations
7.
Zanella, Marco, Craig M. Robertson, Hongjun Niu, et al.. (2024). Navigation through high-dimensional chemical space: discovery of Ba 5 Y 13 [SiO 4 ] 8 O 8.5 and Ba 3 Y 2 [Si 2 O 7 ] 2. Chemical Science. 15(40). 16503–16518.
8.
Collins, Christopher M., Katie Atkinson, Matthew S. Dyer, et al.. (2024). Exploration of Chemical Space Through Automated Reasoning. Angewandte Chemie. 137(6).
9.
Antypov, Dmytro, Christopher M. Collins, Andrij Vasylenko, et al.. (2024). Statistically Derived Proxy Potentials Accelerate Geometry Optimization of Crystal Structures. ChemPhysChem. 25(12). e202400254–e202400254. 2 indexed citations
10.
Collins, Christopher M., et al.. (2024). Integration of generative machine learning with the heuristic crystal structure prediction code FUSE. Faraday Discussions. 256(0). 85–103. 2 indexed citations
11.
Vasylenko, Andrij, Christopher M. Collins, Michael W. Gaultois, et al.. (2024). Inferring energy–composition relationships with Bayesian optimization enhances exploration of inorganic materials. The Journal of Chemical Physics. 160(5). 4 indexed citations
12.
Collins, Christopher M., Dmytro Antypov, Vladimir V. Gusev, et al.. (2023). Reinforcement learning in crystal structure prediction. Digital Discovery. 2(6). 1831–1840. 4 indexed citations
13.
Gusev, Vladimir V., Argyrios Deligkas, Dmytro Antypov, et al.. (2023). Optimality guarantees for crystal structure prediction. Nature. 619(7968). 68–72. 33 indexed citations
14.
Brizi, Danilo, et al.. (2023). A Passive and Conformal Magnetic Metasurface for 3T MRI Birdcage Coil. CINECA IRIS Institutial research information system (University of Pisa). 222–224.
15.
Fayon, Franck, Emmanuel Véron, Cécile Genevois, et al.. (2023). A computationally-guided non-equilibrium synthesis approach to materials discovery in the SrO–Al2O3–SiO2 phase field. Chemical Communications. 59(70). 10544–10547. 3 indexed citations
16.
Collins, Christopher M., Luke M. Daniels, Ruiyong Chen, et al.. (2022). Cation Disorder and Large Tetragonal Supercell Ordering in the Li-Rich Argyrodite Li7Zn0.5SiS6. Chemistry of Materials. 34(9). 4073–4087. 7 indexed citations
17.
Collins, Christopher M., Luke M. Daniels, Quinn Gibson, et al.. (2021). Discovery of a Low Thermal Conductivity Oxide Guided by Probe Structure Prediction and Machine Learning. Angewandte Chemie International Edition. 60(30). 16457–16465. 21 indexed citations
18.
Perez, Arnaud J., José Antonio Coca Clemente, Filipe Braga, et al.. (2019). Stabilization of O–O Bonds by d0 Cations in Li4+xNi1–xWO6 (0 ≤ x ≤ 0.25) Rock Salt Oxides as the Origin of Large Voltage Hysteresis. Journal of the American Chemical Society. 141(18). 7333–7346. 74 indexed citations
19.
Dyer, Matthew S., Christopher M. Collins, Philip A. Chater, et al.. (2013). Computationally Assisted Identification of Functional Inorganic Materials. Science. 340(6134). 847–852. 57 indexed citations
20.
Wang, Dorothy Y., et al.. (2013). Engine test for wavelength-multiplexed fiber Bragg grating temperature sensor. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8722. 872209–872209. 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by S. Pandiarajan Breakdown of academic impact, for papers by Alexandre Garreau Breakdown of academic impact, for papers by Jun Geng Breakdown of academic impact, for papers by L. J. Brown Breakdown of academic impact, for papers by Junjie Li Breakdown of academic impact, for papers by Alexandre Rocha Paschoal Breakdown of academic impact, for papers by Imran Khan Breakdown of academic impact, for papers by Haruyuki Ishii Breakdown of academic impact, for papers by В. В. Соколов
Rankless by CCL
2026