Nicodemo Di Pasquale
- Materials Chemistry
- Molecular Biology
- Biomedical Engineering
- Atomic and Molecular Physics, and Optics
- Computational Theory and Mathematics top 10%
- Co-authors
- Paola CarboneDaniele MarchisioPaul L. A. PopelierAntonello BarresiRuslan L. DavidchackPeter I. MaxwellMatteo IcardiRichard Gowers
- Topics
- Machine Learning in Materials Science (8 papers)Computational Drug Discovery Methods (6 papers)Protein Structure and Dynamics (5 papers)
- Partner nations
- United KingdomItalyUnited States
In The Last Decade
Nicodemo Di Pasquale
30 papers receiving 381 citations
Peers
Comparison fields: 5 of 64
- Materials Chemistry 196
- Molecular Biology 84
- Biomedical Engineering 70
- Atomic and Molecular Physics, and Optics 61
- Computational Theory and Mathematics 59
Countries citing papers authored by Nicodemo Di Pasquale
This map shows the geographic impact of Nicodemo Di Pasquale'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 Nicodemo Di Pasquale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicodemo Di Pasquale more than expected).
Fields of papers citing papers by Nicodemo Di Pasquale
This network shows the impact of papers produced by Nicodemo Di Pasquale. 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 Nicodemo Di Pasquale. The network helps show where Nicodemo Di Pasquale may publish in the future.
Co-authorship network of co-authors of Nicodemo Di Pasquale
This figure shows the co-authorship network connecting the top 25 collaborators of Nicodemo Di Pasquale. A scholar is included among the top collaborators of Nicodemo Di Pasquale 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 Nicodemo Di Pasquale. Nicodemo Di Pasquale is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 12 | |
| 7 | 5 | |
| 8 | 6 | |
| 9 | 11 | |
| 10 | 12 | |
| 11 | 3 | |
| 12 | 7 | |
| 13 | 11 | |
| 14 | 23 | |
| 15 | 8 | |
| 16 | 22 | |
| 17 | 17 | |
| 18 | 2 | |
| 19 | 30 | |
| 20 | 21 |
About Nicodemo Di Pasquale
Nicodemo Di Pasquale is a scholar working on Fluid Flow and Transfer Processes, Computational Theory and Mathematics and Condensed Matter Physics, having authored 30 papers that have together received 387 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (8 papers), Computational Drug Discovery Methods (6 papers) and Protein Structure and Dynamics (5 papers). The work is most often cited by research in Physical and Theoretical Chemistry (44 citations), Materials Chemistry (196 citations) and Surfaces, Coatings and Films (28 citations). Nicodemo Di Pasquale has collaborated with scholars based in United Kingdom, Italy and United States. Frequent co-authors include Paola Carbone, Daniele Marchisio, Paul L. A. Popelier, Antonello Barresi, Ruslan L. Davidchack, Peter I. Maxwell, Matteo Icardi, Richard Gowers, Michael Bane and Joshua D. Elliott. Their work appears in journals such as Chemical Reviews, The Journal of Chemical Physics and The Journal of Physical Chemistry B.
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.