Ivan Maliyov
- Materials Chemistry
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Molecular Biology
- Co-authors
- Marco BernardiJinsoo ParkJin-Jian ZhouI-Te LuXiao TongFabien BrunevalJean-Paul CrocombetteMykhailo Girych
- Topics
- Machine Learning in Materials Science (4 papers)Semiconductor materials and devices (4 papers)Molecular Junctions and Nanostructures (3 papers)
- Journals
- Journal of Chemical Theory and ComputationComputer Physics CommunicationsPhysical review. B.
- Partner nations
- United StatesFranceUkraine
In The Last Decade
Ivan Maliyov
10 papers receiving 333 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Materials Chemistry 173
- Atomic and Molecular Physics, and Optics 145
- Electrical and Electronic Engineering 114
- Electronic, Optical and Magnetic Materials 29
- Molecular Biology 23
Countries citing papers authored by Ivan Maliyov
This map shows the geographic impact of Ivan Maliyov'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 Ivan Maliyov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Maliyov more than expected).
Fields of papers citing papers by Ivan Maliyov
This network shows the impact of papers produced by Ivan Maliyov. 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 Ivan Maliyov. The network helps show where Ivan Maliyov may publish in the future.
Co-authorship network of co-authors of Ivan Maliyov
This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Maliyov. A scholar is included among the top collaborators of Ivan Maliyov 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 Ivan Maliyov. Ivan Maliyov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | Perturbo: A software package for ab initio electron–phonon interactions, charge transport and ultrafast dynamicsbreakdown → | 186 |
| 7 | 14 | |
| 8 | 11 | |
| 9 | 17 | |
| 10 | 31 | |
| 11 | 24 | |
| 12 | 42 |
About Ivan Maliyov
Ivan Maliyov is a scholar working on Atomic and Molecular Physics, and Optics, Clinical Biochemistry and Computational Theory and Mathematics, having authored 12 papers that have together received 336 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Semiconductor materials and devices (4 papers) and Molecular Junctions and Nanostructures (3 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (145 citations), Materials Chemistry (173 citations) and Structural Biology (3 citations). Ivan Maliyov has collaborated with scholars based in United States, France and Ukraine. Frequent co-authors include Marco Bernardi, Jinsoo Park, Jin-Jian Zhou, I-Te Lu, Xiao Tong, Fabien Bruneval, Jean-Paul Crocombette, Mykhailo Girych, Valeriya Trusova and Galyna Gorbenko. Their work appears in journals such as Journal of Chemical Theory and Computation, Computer Physics Communications and Physical review. 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.