Massimo Rovere

51 total papers · 2.1k total citations
39 papers, 1.6k citations indexed

About

Massimo Rovere is a scholar working on Materials Chemistry, Mechanical Engineering and Polymers and Plastics. According to data from OpenAlex, Massimo Rovere has authored 39 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Materials Chemistry, 13 papers in Mechanical Engineering and 10 papers in Polymers and Plastics. Recurrent topics in Massimo Rovere's work include Fiber-reinforced polymer composites (10 papers), Carbon Nanotubes in Composites (9 papers) and Graphene research and applications (8 papers). Massimo Rovere is often cited by papers focused on Fiber-reinforced polymer composites (10 papers), Carbon Nanotubes in Composites (9 papers) and Graphene research and applications (8 papers). Massimo Rovere collaborates with scholars based in Italy, Canada and United States. Massimo Rovere's co-authors include Alberto Tagliaferro, Mattia Bartoli, Mauro Giorcelli, Pravin Jagdale, Carlo Rosso, Andrea Orlando, Filippo Franceschini, Aamer Khan, Elisa Padovano and Micaela Castellino and has published in prestigious journals such as Scientific Reports, Carbon and The Journal of Physical Chemistry C.

In The Last Decade

Massimo Rovere

39 papers receiving 1.5k citations

Hit Papers

A Comprehensive Review on... 2021 2026 2022 2024 2021 50 100 150 200

Author Peers

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

Author Last Decade Papers Cites
Massimo Rovere 693 358 286 253 244 39 1.6k
M. Ferhat Yardim 389 0.6× 405 1.1× 163 0.6× 232 0.9× 384 1.6× 32 1.5k
Dawei Li 573 0.8× 728 2.0× 294 1.0× 188 0.7× 272 1.1× 66 1.9k
Benny K. George 969 1.4× 312 0.9× 186 0.7× 215 0.8× 147 0.6× 56 1.7k
Xiangyu Bi 686 1.0× 403 1.1× 200 0.7× 102 0.4× 328 1.3× 33 1.5k
Shi-Jie Gao 632 0.9× 643 1.8× 213 0.7× 206 0.8× 131 0.5× 44 1.9k
Jia Lei 647 0.9× 247 0.7× 246 0.9× 257 1.0× 241 1.0× 54 1.7k
Houssam El‐Rassy 1.0k 1.5× 425 1.2× 148 0.5× 138 0.5× 272 1.1× 42 2.2k
Dan Chang 787 1.1× 596 1.7× 230 0.8× 287 1.1× 200 0.8× 62 2.0k
Mojammel A. Khan 534 0.8× 461 1.3× 396 1.4× 565 2.2× 144 0.6× 33 1.6k
Mohammad Ilyas Khan 869 1.3× 288 0.8× 225 0.8× 85 0.3× 149 0.6× 55 1.7k

Countries citing papers authored by Massimo Rovere

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Rovere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Rovere

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

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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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