Mario Lanza
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- Advanced Memory and Neural Computing 108
- Ferroelectric and Negative Capacitance Devices 76
- Semiconductor materials and devices 60
- Materials Chemistry top 1%
- Graphene research and applications 42
- 2D Materials and Applications 29
- Electronic and Structural Properties of Oxides 23
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- Neuroscience and Neural Engineering 29
- Polymers and Plastics top 1%
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- Force Microscopy Techniques and Applications 24
Mario Lanza
212 papers receiving 8.6k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Electrical and Electronic Engineering 6.4k
- Materials Chemistry 4.2k
- Cellular and Molecular Neuroscience 1.4k
- Polymers and Plastics 995
- Renewable Energy, Sustainability and the Environment 780
Countries citing papers authored by Mario Lanza
This map shows the geographic impact of Mario Lanza'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 Mario Lanza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Lanza more than expected).
Fields of papers citing papers by Mario Lanza
This network shows the impact of papers produced by Mario Lanza. 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 Mario Lanza. The network helps show where Mario Lanza may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mario Lanza, 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 | 2025 | 3 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 9 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 8 | |
| 8 | 2024 | 11 | |
| 9 | 2024 | 10 | |
| 10 | 2023 | 20 | |
| 11 | 2023 | 3 | |
| 12 | 2023 | 7 | |
| 13 | 2023 | 8 | |
| 14 | 2022 | 26 | |
| 15 | 2020 | 83 | |
| 16 | 2019 | 38 | |
| 17 | 2018 | 32 | |
| 18 | 2017 | 276 | |
| 19 | 2017 | 24 | |
| 20 | 2016 | 5 |
About Mario Lanza
Mario Lanza is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Cellular and Molecular Neuroscience, Acoustics and Ultrasonics and Atomic and Molecular Physics, and Optics, having authored 220 papers that have together received 8.8k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (108 papers), Ferroelectric and Negative Capacitance Devices (76 papers), Semiconductor materials and devices (60 papers), Graphene research and applications (42 papers), Neuroscience and Neural Engineering (29 papers), 2D Materials and Applications (29 papers), Force Microscopy Techniques and Applications (24 papers) and Electronic and Structural Properties of Oxides (23 papers). The work is most often cited by research in Electrical and Electronic Engineering (6.4k citations), Materials Chemistry (4.2k citations), Cellular and Molecular Neuroscience (1.4k citations), Polymers and Plastics (995 citations) and Renewable Energy, Sustainability and the Environment (780 citations). Mario Lanza has collaborated with scholars based in China, Saudi Arabia and Spain. Frequent co-authors include Fei Hui, Yuanyuan Shi, Chao Wen, M. Porti, M. Nafrı́a, Deji Akinwande, Bin Yuan, Husam N. Alshareef, Kaichen Zhu and Xianhu Liang. Their work appears in journals such as Advanced Materials, Advanced Functional Materials, ACS Applied Materials & Interfaces, Advanced Electronic Materials and Applied Physics 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.