Xiaoting Jia
- Materials Chemistry top 0.2%
- Graphene research and applications 17
- Carbon Nanotubes in Composites 7
- Biomedical Engineering top 0.5%
- Advanced Sensor and Energy Harvesting Materials 13
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- Advanced Fiber Optic Sensors 6
- Photonic and Optical Devices 6
- Polymers and Plastics top 2%
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- Neuroscience and Neural Engineering 12
- Photoreceptor and optogenetics research 10
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- Neural dynamics and brain function 6
- Co-authors
- M. S. DresselhausJing KongAlfonso ReinaDaniel NezichHyungbin SonVladimir BulovićJohn HoYumeng Shi
- Journals
- Nano Letters (9 papers)Nature Communications (6 papers)Advanced Functional Materials (4 papers)
- Partner nations
- United StatesJapanChina
In The Last Decade
Xiaoting Jia
66 papers receiving 11.9k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Materials Chemistry 9.1k
- Biomedical Engineering 4.1k
- Electrical and Electronic Engineering 4.7k
- Electronic, Optical and Magnetic Materials 1.4k
- Polymers and Plastics 764
Countries citing papers authored by Xiaoting Jia
This map shows the geographic impact of Xiaoting Jia'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 Xiaoting Jia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoting Jia more than expected).
Fields of papers citing papers by Xiaoting Jia
This network shows the impact of papers produced by Xiaoting Jia. 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 Xiaoting Jia. The network helps show where Xiaoting Jia may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaoting Jia, 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 | 2024 | 1 | |
| 2 | 2024 | 16 | |
| 3 | 2024 | 6 | |
| 4 | 2023 | 10 | |
| 5 | 2023 | 21 | |
| 6 | 2022 | 10 | |
| 7 | 2021 | 14 | |
| 8 | 2021 | 55 | |
| 9 | 2020 | 47 | |
| 10 | 2020 | 106 | |
| 11 | 2020 | 45 | |
| 12 | 2020 | 10 | |
| 13 | 2020 | 207 | |
| 14 | 2019 | 32 | |
| 15 | One-step optogenetics with multifunctional flexible polymer fibers | 2017 | 2 |
| 16 | 2017 | 289 | |
| 17 | Multifunctional fibers for simultaneous optical, electrical and chemical interrogation of neural circuits in vivobreakdown → | 2015 | 532 |
| 18 | 2015 | 1 | |
| 19 | 2010 | 350 | |
| 20 | Growth and Characterization of CVD Graphene | 2009 | 1 |
About Xiaoting Jia
Xiaoting Jia is a scholar working on Cellular and Molecular Neuroscience, Structural Biology and Biomedical Engineering, having authored 67 papers that have together received 12.1k indexed citations. Recurring topics across this work include Graphene research and applications (17 papers), Advanced Sensor and Energy Harvesting Materials (13 papers), Neuroscience and Neural Engineering (12 papers), Photoreceptor and optogenetics research (10 papers), Carbon Nanotubes in Composites (7 papers), Advanced Fiber Optic Sensors (6 papers), Photonic and Optical Devices (6 papers) and Neural dynamics and brain function (6 papers). The work is most often cited by research in Materials Chemistry (9.1k citations), Biomedical Engineering (4.1k citations) and Electrical and Electronic Engineering (4.7k citations). Xiaoting Jia has collaborated with scholars based in United States, Japan and China. Frequent co-authors include M. S. Dresselhaus, Jing Kong, Alfonso Reina, Daniel Nezich, Hyungbin Son, Vladimir Bulović, John Ho, Yumeng Shi, Ki Kang Kim and Mario Hofmann. Their work appears in journals such as Nano Letters, Nature Communications, Advanced Functional Materials, ACS Nano and Advanced Healthcare Materials.
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.