Massimo Poletto

3.7k citations
129 papers · 3.1k · h-index 34

Impact in

Papers in

Massimo Poletto

124 papers receiving 3.0k citations

Peers

Massimo Poletto
Comparison fields: 5 of 127
  • Computational Mechanics 1.3k
  • Ocean Engineering 503
  • Fluid Flow and Transfer Processes 191
  • Automotive Engineering 370
  • Mechanical Engineering 995
Replace Diego Barletta with:
Diego Barletta Italy
Satoru Watano Japan
Rahmat Sotudeh‐Gharebagh Iran
Benjamin J. Glasser United States
Masoud Rahimi Iran
Ville Alopaeus Finland
Vivek Vinayak Ranade India
Ali Lohi Canada
Madalena M. Dias Portugal
Sudipto Chakraborty India
Massimo Poletto relative to Diego Barletta Italy Diego Barletta's profile →
Citations per field
00.5×1.6×
Diego Barletta · 1×
Citations per year

Countries citing papers authored by Massimo Poletto

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Poletto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Massimo Poletto, 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 Massimo Poletto Line = papers co-authored together Massimo Poletto links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 129 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994135
2 1998124
3 1997115
4 201288
5 199987
6 201279
7 202177
8 201061
9 202057
10 201755
11 201853
12 200753
13 199552
14 201550
15 200649
16 201748
17 201848
18 201748
19 201046
20 201546

About Massimo Poletto

Massimo Poletto is a scholar working on Computational Mechanics, Ocean Engineering, Mechanical Engineering, Automotive Engineering and Fluid Flow and Transfer Processes, having authored 129 papers that have together received 3.1k indexed citations. Recurring topics across this work include Granular flow and fluidized beds (69 papers), Particle Dynamics in Fluid Flows (29 papers), Cyclone Separators and Fluid Dynamics (18 papers), Mineral Processing and Grinding (17 papers), Fluid Dynamics and Heat Transfer (16 papers), Additive Manufacturing and 3D Printing Technologies (13 papers), Biofuel production and bioconversion (12 papers) and Injection Molding Process and Properties (11 papers). The work is most often cited by research in Computational Mechanics (1.3k citations), Ocean Engineering (503 citations), Fluid Flow and Transfer Processes (191 citations), Automotive Engineering (370 citations) and Mechanical Engineering (995 citations). Massimo Poletto has collaborated with scholars based in Italy, United Kingdom and China. Frequent co-authors include Diego Barletta, Ernesto Reverchon, Daniele Sofia, Giovanna Ferrari, Aristide Giuliano, Paola Lettieri, Giorgio Donsı̀, Hamid Salehi Kahrizsangi, Paola F. Russo and D. D. Joseph. Their work appears in journals such as Powder Technology, Chemical Engineering Science, Industrial & Engineering Chemistry Research, Particuology and Process Safety and Environmental Protection.

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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