A. Miguel

2.0k citations
44 papers · 1.4k · h-index 20

Impact in

    • Machine Learning in Materials Science
    • X-ray Diffraction in Crystallography
    • Diamond and Carbon-based Materials Research
    • Graphene research and applications
    • Electrochemical Analysis and Applications

Papers in

A. Miguel

42 papers receiving 1.4k citations

Peers

A. Miguel
Comparison fields: 5 of 82
  • Materials Chemistry 1.0k
  • Electrochemistry 100
  • Structural Biology 20
  • Catalysis 78
  • Surfaces, Coatings and Films 71
Replace Filippo Federici Canova with:
Filippo Federici Canova Japan
Hsin-Yu Ko United States
Min Feng China
David Gao United Kingdom
Nicholas D. M. Hine United Kingdom
Giacomo Miceli Switzerland
Andrew J. Morris United Kingdom
Sébastien Gauthier France
Itai Leven United States
Ferenc Karsai Austria
A. Miguel relative to Filippo Federici Canova Japan Filippo Federici Canova's profile →
Citations per field
00.5×2.6×
Filippo Federici Canova · 1×
Citations per year

Countries citing papers authored by A. Miguel

Since Specialization
Citations

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

Fields of papers citing papers by A. Miguel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside A. Miguel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with A. Miguel Line = papers co-authored together A. Miguel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017144
2 2020112
3 2019111
4 201988
5 201485
6 201884
7 201874
8 202265
9 202063
10 202360
11 201957
12 202054
13 201652
14 202149
15 202246
16 202343
17 202231
18 202327
19 201725
20 202321

About A. Miguel

A. Miguel is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Surfaces, Coatings and Films and Computational Theory and Mathematics, having authored 44 papers that have together received 1.4k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (25 papers), Advanced Chemical Physics Studies (7 papers), Diamond and Carbon-based Materials Research (6 papers), Electron and X-Ray Spectroscopy Techniques (5 papers), X-ray Diffraction in Crystallography (4 papers), Computational Drug Discovery Methods (4 papers), Catalytic Processes in Materials Science (3 papers) and X-ray Spectroscopy and Fluorescence Analysis (3 papers). The work is most often cited by research in Materials Chemistry (1.0k citations), Electrochemistry (100 citations), Structural Biology (20 citations), Catalysis (78 citations) and Surfaces, Coatings and Films (71 citations). A. Miguel has collaborated with scholars based in Finland, United Kingdom and United States. Frequent co-authors include Tomi Laurila, Volker L. Deringer, Gábor Cśanyi, Sami Sainio, Anja Aarva, Olga Lopez‐Acevedo, Tapio Ala-Nissilä, Yanzhou Wang, Zheyong Fan and Ping Qian. Their work appears in journals such as Chemistry of Materials, Physical review. B., The Journal of Chemical Physics, The Journal of Physical Chemistry C and ACS Catalysis.

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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