Loı̈c M. Roch

3.2k total citations · 1 hit paper
36 papers, 2.2k citations indexed

About

Loı̈c M. Roch is a scholar working on Materials Chemistry, Organic Chemistry and Biomedical Engineering. According to data from OpenAlex, Loı̈c M. Roch has authored 36 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Materials Chemistry, 9 papers in Organic Chemistry and 8 papers in Biomedical Engineering. Recurrent topics in Loı̈c M. Roch's work include Machine Learning in Materials Science (15 papers), Synthesis and Properties of Aromatic Compounds (8 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (7 papers). Loı̈c M. Roch is often cited by papers focused on Machine Learning in Materials Science (15 papers), Synthesis and Properties of Aromatic Compounds (8 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (7 papers). Loı̈c M. Roch collaborates with scholars based in Switzerland, United States and Canada. Loı̈c M. Roch's co-authors include Alán Aspuru‐Guzik, Florian Häse, Christoph Kreisbeck, Christoph J. Brabec, Hermann Tribukait, Lars P. E. Yunker, Jason E. Hein, Kim K. Baldridge, Semion K. Saikin and Daniel P. Tabor and has published in prestigious journals such as Advanced Materials, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Loı̈c M. Roch

34 papers receiving 2.1k 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.

Accelerating the discovery of materials for clean energy in the era of smart automation

2018 572 citations Daniel P. Tabor, Loı̈c M. Roch et al. Nature Reviews Materials profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Loı̈c M. Roch Switzerland	19	1.3k	490	482	385	258	36	2.2k
Katherine C. Elbert United States	10	1.2k 0.9×	609 1.2×	233 0.5×	199 0.5×	195 0.8×	16	1.9k
Carlos Amador‐Bedolla Mexico	20	1.2k 0.9×	719 1.5×	352 0.7×	261 0.7×	139 0.5×	98	2.6k
Robert Pollice Canada	18	791 0.6×	368 0.8×	199 0.4×	335 0.9×	332 1.3×	39	1.7k
Ben M. Alston United Kingdom	15	1.1k 0.9×	300 0.6×	368 0.8×	152 0.4×	355 1.4×	15	1.9k
Edward O. Pyzer‐Knapp United Kingdom	19	947 0.7×	248 0.5×	195 0.4×	354 0.9×	216 0.8×	44	1.6k
Arun Mannodi‐Kanakkithodi United States	23	2.4k 1.8×	934 1.9×	593 1.2×	545 1.4×	113 0.4×	63	3.1k
Zhonglin Cao United States	19	798 0.6×	247 0.5×	656 1.4×	346 0.9×	86 0.3×	32	1.7k
Jarosław M. Granda Poland	13	850 0.7×	152 0.3×	552 1.1×	378 1.0×	225 0.9×	23	1.6k
Florian Häse Canada	20	1.6k 1.2×	318 0.6×	551 1.1×	869 2.3×	97 0.4×	25	2.7k
Milad Abolhasani United States	33	1.6k 1.2×	1.1k 2.1×	1.7k 3.5×	141 0.4×	305 1.2×	118	3.4k

Countries citing papers authored by Loı̈c M. Roch

Since Specialization

Citations

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

Fields of papers citing papers by Loı̈c M. Roch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Loı̈c M. Roch

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

All Works

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20 of 20 papers shown

Wu, EX, L. Brey, Hermann Tribukait, et al.. (2025). Bridging Innovation and Efficiency: The Promises and Challenges of Self-Driving Labs as Sustainable Drivers for Chemistry. CHIMIA International Journal for Chemistry. 79(9). 600–605.

Luterbacher, Jeremy S., et al.. (2025). Best practices for multi-fidelity Bayesian optimization in materials and molecular research. Nature Computational Science. 5(7). 572–581. 5 indexed citations

Schilter, Oliver, Alessandro Castrogiovanni, Alberto García-Durán, et al.. (2024). Combining Bayesian optimization and automation to simultaneously optimize reaction conditions and routes. Chemical Science. 15(20). 7732–7741. 13 indexed citations

Tribukait, Hermann, et al.. (2023). How to Accelerate R&D and Optimize Experiment Planning with Machine Learning and Data Science. CHIMIA International Journal for Chemistry. 77(1/2). 7–7. 9 indexed citations

Hickman, Riley J., et al.. (2023). Equipping data-driven experiment planning for Self-driving Laboratories with semantic memory: case studies of transfer learning in chemical reaction optimization. Reaction Chemistry & Engineering. 8(9). 2284–2296. 12 indexed citations

Christensen, Melodie, Lars P. E. Yunker, Florian Häse, et al.. (2021). Data-science driven autonomous process optimization. Communications Chemistry. 4(1). 112–112. 143 indexed citations

Friederich, Pascal, Salvador León, José Darío Perea, Loı̈c M. Roch, & Alán Aspuru‐Guzik. (2020). The influence of sorbitol doping on aggregation and electronic properties of PEDOT:PSS: a theoretical study. Machine Learning Science and Technology. 2(1). 01LT01–01LT01. 11 indexed citations

Roch, Loı̈c M., Florian Häse, Christoph Kreisbeck, et al.. (2020). ChemOS: An orchestration software to democratize autonomous discovery. PLoS ONE. 15(4). e0229862–e0229862. 95 indexed citations

Häse, Florian, Loı̈c M. Roch, Pascal Friederich, & Alán Aspuru‐Guzik. (2020). Designing and understanding light-harvesting devices with machine learning. Nature Communications. 11(1). 85 indexed citations

10.

Sánchez-Lengeling, Benjamín, Loı̈c M. Roch, José Darío Perea, et al.. (2018). A Bayesian Approach to Predict Solubility Parameters. Advanced Theory and Simulations. 2(1). 76 indexed citations

11.

Tabor, Daniel P., Loı̈c M. Roch, Semion K. Saikin, et al.. (2018). Accelerating the discovery of materials for clean energy in the era of smart automation. Nature Reviews Materials. 3(5). 5–20. 572 indexed citations breakdown →

12.

Wang, Zhenzhen, Hui Cui, Zhimin Sun, et al.. (2018). Melatonin-directed micellization: a case for tryptophan metabolites and their classical bioisosteres as templates for the self-assembly of bipyridinium-based supramolecular amphiphiles in water. Soft Matter. 14(15). 2893–2905. 8 indexed citations

13.

Liu, Shi, Loı̈c M. Roch, Oliver Allemann, et al.. (2018). 1,2,3- versus 1,2-Indeno Ring Fusions Influence Structure Property and Chirality of Corannulene Bowls. The Journal of Organic Chemistry. 83(7). 3979–3986. 12 indexed citations

14.

Roch, Loı̈c M. & Kim K. Baldridge. (2017). General optimization procedure towards the design of a new family of minimal parameter spin-component-scaled double-hybrid density functional theory. Physical Chemistry Chemical Physics. 19(38). 26191–26200. 27 indexed citations

15.

Roch, Loı̈c M. & Kim K. Baldridge. (2017). Dispersion-Corrected Spin-Component-Scaled Double-Hybrid Density Functional Theory: Implementation and Performance for Non-covalent Interactions. Journal of Chemical Theory and Computation. 13(6). 2650–2666. 9 indexed citations

16.

Roch, Loı̈c M., Amit Kumar Dutta, Yujia Wang, et al.. (2016). Pentaindenocorannulene: Properties, Assemblies, and C₆₀ Complex. Angewandte Chemie International Edition. 55(47). 14648–14652. 59 indexed citations

17.

Marchioro, Arianna, Julien Andrès, Loı̈c M. Roch, et al.. (2014). Kinetics of the Regeneration by Iodide of Dye Sensitizers Adsorbed on Mesoporous Titania. The Journal of Physical Chemistry C. 118(30). 17108–17115. 26 indexed citations

18.

Gonthier, Jérôme F., Stephan N. Steinmann, Loı̈c M. Roch, et al.. (2012). π-Depletion as a criterion to predict π-stacking ability. Chemical Communications. 48(74). 9239–9239. 82 indexed citations

19.

Roch, Loı̈c M., et al.. (2011). Many worlds interpretation of quantum theory. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2 indexed citations

20.

Roch, Loı̈c M., et al.. (1967). Visual Changes Associated With Clomiphene Citrate Therapy. Archives of Ophthalmology. 77(1). 14–17. 18 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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