Xianhu Liang
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- Photoreceptor and optogenetics research 2
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- Advanced Memory and Neural Computing 8
- Ferroelectric and Negative Capacitance Devices 6
- Semiconductor materials and devices 3
- Polymers and Plastics top 10%
- Materials Chemistry top 10%
- Graphene research and applications 6
- 2D Materials and Applications 3
- MXene and MAX Phase Materials 3
- Hardware and Architecture top 10%
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- Topological Materials and Phenomena 3
- Co-authors
- Yuanyuan ShiMario LanzaFei HuiBin YuanVictoria ChenEric PopH.‐S. Philip WongZhouchangwan Yu
- Cited by
- Cellular and Molecular NeuroscienceElectrical and Electronic EngineeringPolymers and Plastics
- Partner nations
- ChinaUnited StatesIsrael
In The Last Decade
Xianhu Liang
15 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 36
- Cellular and Molecular Neuroscience 357
- Electrical and Electronic Engineering 1.1k
- Polymers and Plastics 206
- Materials Chemistry 434
- Hardware and Architecture 38
Countries citing papers authored by Xianhu Liang
This map shows the geographic impact of Xianhu Liang'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 Xianhu Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xianhu Liang more than expected).
Fields of papers citing papers by Xianhu Liang
This network shows the impact of papers produced by Xianhu Liang. 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 Xianhu Liang. The network helps show where Xianhu Liang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xianhu Liang, 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 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 14 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 2 | |
| 6 | 2021 | 2 | |
| 7 | 2021 | 102 | |
| 8 | 2020 | 37 | |
| 9 | 2020 | 23 | |
| 10 | Wafer-scale integration of two-dimensional materials in high-density memristive crossbar arrays for artificial neural networksbreakdown → | 2020 | 349 |
| 11 | 2019 | 23 | |
| 12 | 2019 | 75 | |
| 13 | 2019 | 1 | |
| 14 | 2018 | 1 | |
| 15 | 2018 | 15 | |
| 16 | Electronic synapses made of layered two-dimensional materialsbreakdown → | 2018 | 555 |
| 17 | 2017 | 18 |
About Xianhu Liang
Xianhu Liang is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Polymers and Plastics, having authored 17 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (8 papers), Graphene research and applications (6 papers), Ferroelectric and Negative Capacitance Devices (6 papers), 2D Materials and Applications (3 papers), MXene and MAX Phase Materials (3 papers), Semiconductor materials and devices (3 papers), Topological Materials and Phenomena (3 papers) and Photoreceptor and optogenetics research (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (357 citations), Electrical and Electronic Engineering (1.1k citations) and Polymers and Plastics (206 citations). Xianhu Liang has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Yuanyuan Shi, Mario Lanza, Fei Hui, Bin Yuan, Victoria Chen, Eric Pop, H.‐S. Philip Wong, Zhouchangwan Yu, Haitong Li and Fang Yuan.
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.