Chiara Panosetti

526 citations
18 papers · 373 indexed · h-index 10
Topics
Machine Learning in Materials Science (7 papers)Advanced Chemical Physics Studies (6 papers)Advancements in Battery Materials (4 papers)
Journals
The Journal of Chemical PhysicsSHILAP Revista de lepidopterologíaNano Letters

In The Last Decade

Chiara Panosetti

17 papers receiving 367 citations

Peers

Chiara Panosetti
Comparison fields: 5 of 62
  • Materials Chemistry 246
  • Electrical and Electronic Engineering 109
  • Atomic and Molecular Physics, and Optics 93
  • Catalysis 65
  • Renewable Energy, Sustainability and the Environment 33
Replace Anand Narayanan Krishnamoorthy with:
Anand Narayanan Krishnamoorthy Germany
Alexander Lindmaa Sweden
Yashasvi S. Ranawat Finland
Tsz Wai Ko United States
Samare Rostami Iran
Jaehoon Kim South Korea
Chiheb Ben Mahmoud Switzerland
Kyle Michel United States
Camilo E. Calderón United States
Fernando Gargiulo Switzerland
Chiara Panosetti relative to Anand Narayanan Krishnamoorthy Germany Anand Narayanan Krishnamoorthy's profile →
Citations per field
00.5×
Anand Narayanan Krishnamoorthy · 1×
Citations per year

Countries citing papers authored by Chiara Panosetti

Since Specialization
Citations

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

Fields of papers citing papers by Chiara Panosetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chiara Panosetti

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 0
2 6
3 4
4 2
5 18
6 8
7 9
8 17
9 33
10 200
11 1
12 12
13 12
14 15
15 12
16 5
17 7
18 12

About Chiara Panosetti

Chiara Panosetti is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Automotive Engineering, having authored 18 papers that have together received 373 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (7 papers), Advanced Chemical Physics Studies (6 papers) and Advancements in Battery Materials (4 papers). The work is most often cited by research in Catalysis (65 citations), Materials Chemistry (246 citations) and Atomic and Molecular Physics, and Optics (93 citations). Chiara Panosetti has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Karsten Reuter, Mie Andersen, Christoph Scheurer, Lydia Nemec, Johannes T. Margraf, Werner A. Hofer, Reinhard J. Maurer, Yonghyuk Lee, Dennis Palagin and Stefan Seidlmayer. Their work appears in journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and Nano Letters.

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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