John J. Molina

112 total papers · 1.0k total citations
55 papers, 757 citations indexed

About

John J. Molina is a scholar working on Condensed Matter Physics, Biomedical Engineering and Mechanical Engineering. According to data from OpenAlex, John J. Molina has authored 55 papers receiving a total of 757 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Condensed Matter Physics, 19 papers in Biomedical Engineering and 11 papers in Mechanical Engineering. Recurrent topics in John J. Molina's work include Micro and Nano Robotics (21 papers), Microfluidic and Bio-sensing Technologies (16 papers) and Modular Robots and Swarm Intelligence (8 papers). John J. Molina is often cited by papers focused on Micro and Nano Robotics (21 papers), Microfluidic and Bio-sensing Technologies (16 papers) and Modular Robots and Swarm Intelligence (8 papers). John J. Molina collaborates with scholars based in Japan, France and United Kingdom. John J. Molina's co-authors include Ryōichi Yamamoto, Jean‐François Dufrêche, Yasuya Nakayama, Pierre Turq, Mathieu Salanne, Bertrand Siboulet, Masaki Sano, Olivier Bernard, Magali Duvail and Philippe Guilbaud and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Chemical Physics.

In The Last Decade

John J. Molina

53 papers receiving 746 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
John J. Molina	260	246	170	153	134	55	757
William Strieder	85 0.3×	143 0.6×	203 1.2×	214 1.4×	61 0.5×	76	798
Eugenia Corvera Poiré	180 0.7×	262 1.1×	231 1.4×	196 1.3×	72 0.5×	47	877
Jesper Schmidt Hansen	55 0.2×	347 1.4×	98 0.6×	248 1.6×	136 1.0×	36	752
Ludwig C. Nitsche	48 0.2×	222 0.9×	200 1.2×	243 1.6×	41 0.3×	39	776
Sergey Shklyaev	285 1.1×	347 1.4×	425 2.5×	247 1.6×	35 0.3×	46	886
Mikhail Stukan	89 0.3×	153 0.6×	41 0.2×	310 2.0×	71 0.5×	41	773
Ignacio Zúñiga	88 0.3×	226 0.9×	243 1.4×	457 3.0×	80 0.6×	32	808
Ulrich M. Scheven	260 1.0×	98 0.4×	86 0.5×	92 0.6×	92 0.7×	45	872
P. Hébraud	83 0.3×	99 0.4×	117 0.7×	447 2.9×	75 0.6×	24	806
Tomoyuki Kinjo	38 0.1×	194 0.8×	189 1.1×	252 1.6×	81 0.6×	37	719

Countries citing papers authored by John J. Molina

Since Specialization

Citations

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

Fields of papers citing papers by John J. Molina

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John J. Molina. 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 John J. Molina. The network helps show where John J. Molina may publish in the future.

Co-authorship network of co-authors of John J. Molina

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

All Works

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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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