Alessandro Lodi
Impact in
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- Graphene research and applications
- Luminescence and Fluorescent Materials
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- Synthesis and Properties of Aromatic Compounds
- Fullerene Chemistry and Applications
Papers in
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- Molecular Junctions and Nanostructures 2
- Advanced Memory and Neural Computing 2
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- Graphene research and applications 3
- 2D Materials and Applications 1
- ZnO doping and properties 1
- Carbon Nanotubes in Composites 1
- Co-authors
- Lapo Bogani (5 shared papers)Kläus Müllen (3 shared papers)Akimitsu Narita (3 shared papers)Ji Ma (2 shared papers)Junzhi Liu (2 shared papers)Xinliang Feng (2 shared papers)William K. Myers (1 shared paper)Michael Slota (1 shared paper)
- Journals
- Advanced Science (2 papers)Science (1 paper)Nature Materials (1 paper)Nature Chemistry (1 paper)Surfaces (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Alessandro Lodi
6 papers receiving 308 citations
Peers
Comparison fields: 5 of 26
- Materials Chemistry 200
- Organic Chemistry 87
- Electrical and Electronic Engineering 155
- Biophysics 13
- Atomic and Molecular Physics, and Optics 67
Countries citing papers authored by Alessandro Lodi
This map shows the geographic impact of Alessandro Lodi'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 Alessandro Lodi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alessandro Lodi more than expected).
Fields of papers citing papers by Alessandro Lodi
This network shows the impact of papers produced by Alessandro Lodi. 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 Alessandro Lodi. The network helps show where Alessandro Lodi may publish in the future.
Co-authors
The 25 scholars most cited alongside Alessandro Lodi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 158 | |
| 2 | 2023 | 55 | |
| 3 | 2024 | 54 | |
| 4 | 2022 | 45 | |
| 5 | 2025 | 1 | |
| 6 | 2022 | 1 |
About Alessandro Lodi
Alessandro Lodi is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Artificial Intelligence, Cellular and Molecular Neuroscience and Atomic and Molecular Physics, and Optics, having authored 6 papers that have together received 314 indexed citations. Recurring topics across this work include Graphene research and applications (3 papers), Molecular Junctions and Nanostructures (2 papers), Neural Networks and Reservoir Computing (2 papers), Advanced Memory and Neural Computing (2 papers), Ga2O3 and related materials (1 paper), 2D Materials and Applications (1 paper), ZnO doping and properties (1 paper) and Carbon Nanotubes in Composites (1 paper). The work is most often cited by research in Materials Chemistry (200 citations), Organic Chemistry (87 citations), Electrical and Electronic Engineering (155 citations), Biophysics (13 citations) and Atomic and Molecular Physics, and Optics (67 citations). Alessandro Lodi has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Lapo Bogani, Kläus Müllen, Akimitsu Narita, Ji Ma, Junzhi Liu, Xinliang Feng, William K. Myers, Michael Slota, Alex Gee and C. David Wright. Their work appears in journals such as Advanced Science, Science, Nature Materials, Nature Chemistry and Surfaces.
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.