Lin Shen

2.6k total citations · 1 hit paper
112 papers, 2.0k citations indexed

About

Lin Shen is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Lin Shen has authored 112 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Materials Chemistry, 28 papers in Electrical and Electronic Engineering and 24 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Lin Shen's work include Spectroscopy and Quantum Chemical Studies (15 papers), Machine Learning in Materials Science (12 papers) and Advanced Chemical Physics Studies (12 papers). Lin Shen is often cited by papers focused on Spectroscopy and Quantum Chemical Studies (15 papers), Machine Learning in Materials Science (12 papers) and Advanced Chemical Physics Studies (12 papers). Lin Shen collaborates with scholars based in China, United States and Hong Kong. Lin Shen's co-authors include Weitao Yang, Wei‐Hai Fang, Jingyu Sun, Xianzhong Yang, Jingheng Wu, Ziyan Chen, Xiang Gao, Yiwen Su, Yuhan Zou and Jiang Zhou and has published in prestigious journals such as Journal of the American Chemical Society, Advanced Materials and Angewandte Chemie International Edition.

In The Last Decade

Lin Shen

107 papers receiving 2.0k citations

Hit Papers

Emerging strategies for steering orientational deposition... 2022 2026 2023 2024 2022 50 100 150 200

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lin Shen China 22 824 659 351 329 273 112 2.0k
Hyun Woo Kim South Korea 25 505 0.6× 1.1k 1.7× 219 0.6× 289 0.9× 206 0.8× 88 2.3k
Kenta Hongo Japan 22 570 0.7× 1.2k 1.9× 187 0.5× 84 0.3× 256 0.9× 111 2.0k
Yang Song China 24 379 0.5× 626 0.9× 147 0.4× 228 0.7× 491 1.8× 68 2.2k
Katherine C. Elbert United States 10 609 0.7× 1.2k 1.8× 160 0.5× 88 0.3× 77 0.3× 16 1.9k
Manabu Ihara Japan 24 747 0.9× 1.5k 2.2× 291 0.8× 80 0.2× 178 0.7× 166 2.0k
Haibo Ma China 31 1.5k 1.8× 1.4k 2.2× 190 0.5× 287 0.9× 710 2.6× 129 3.2k
Daniel P. Tabor United States 23 1.8k 2.2× 586 0.9× 297 0.8× 63 0.2× 303 1.1× 47 2.6k
Zhihai Li China 23 1.1k 1.3× 484 0.7× 80 0.2× 183 0.6× 530 1.9× 87 1.9k
Konstantinos D. Vogiatzis United States 28 299 0.4× 1.6k 2.5× 293 0.8× 125 0.4× 266 1.0× 78 3.1k

Countries citing papers authored by Lin Shen

Since Specialization
Citations

This map shows the geographic impact of Lin Shen'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 Lin Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Shen more than expected).

Fields of papers citing papers by Lin Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lin Shen. 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 Lin Shen. The network helps show where Lin Shen may publish in the future.

Co-authorship network of co-authors of Lin Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Lin Shen. A scholar is included among the top collaborators of Lin Shen 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 Lin Shen. Lin Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Long, Shijun, et al.. (2025). Superhydrophobic Polypropylene Surface via Migration of SiO 2 Nanoparticles with Low Surface Energy. Macromolecular Rapid Communications. 46(16). e2500195–e2500195. 1 indexed citations
2.
Xie, Bin‐Bin, et al.. (2025). Stacking machine learning models for predicting photophysical properties of iridium complexes. Journal of Photochemistry and Photobiology A Chemistry. 466. 116374–116374.
3.
He, Zhiqun, et al.. (2025). Influence of Additional Gaussian Noises on Mixed Quantum-Classical Nonadiabatic Dynamics Simulations of Photoisomerization of cis-Azobenzene. The Journal of Physical Chemistry Letters. 16(35). 9143–9151. 1 indexed citations
4.
Zhou, Yang, Qian Wang, Yibo Shi, et al.. (2025). Molecular design of sensitizers for high-efficiency OLEDs: exploration of energy transfer dynamics. Chemical Science. 16(37). 17304–17315.
5.
Yuan, Ting, Guimin Zhao, Xianzhi Song, et al.. (2025). Symmetric Boron-Bridged Carbon Quantum Frameworks for Light-Emitting Diodes with over 20% External Quantum Efficiency. Journal of the American Chemical Society. 147(31). 28504–28512. 3 indexed citations
6.
Song, Xianzhi, Chen Zhang, Yang Zhang, et al.. (2025). Pure-violet oxygen-doped carbon quantum rings with near-unity quantum yield and a full-width at half-maximum of 18 nm. Nature Synthesis. 5(2). 262–271. 1 indexed citations
7.
Song, Yupeng, et al.. (2024). Fabrication of layered SnS2 as co-triboelectric layers for high performance PDMS-based triboelectric nanogenerators. Materials Letters. 372. 137003–137003. 2 indexed citations
8.
Shen, Lin, Yongteng Qian, Dong‐Hwan Kim, & Dae Joon Kang. (2024). A methodological approach for fabricating hybrid CoP2/THQ@NF electrocatalysts for enhanced HER catalytic performance. International Journal of Hydrogen Energy. 61. 996–1003. 1 indexed citations
10.
Bai, Qi, Jing Kang, Lin Shen, et al.. (2024). The performance of OPC and OPC3 water models in predictions of 2D structures under nanoconfinement. The Journal of Chemical Physics. 160(16). 3 indexed citations
11.
Wei, Xin, et al.. (2023). Analyzing of metal organic frameworks performance in CH4 adsorption using machine learning techniques: A GBRT model based on small training dataset. Journal of environmental chemical engineering. 11(3). 110086–110086. 20 indexed citations
12.
Qian, Yongteng, et al.. (2023). High-Performance Flexible Energy Storage Devices Based on Graphene Decorated with Flower-Shaped MoS2 Heterostructures. Micromachines. 14(2). 297–297. 9 indexed citations
13.
Yin, Bo‐Wen, et al.. (2023). Understanding the Excited-State Relaxation Mechanisms of Xanthophyll Lutein by Multi-configurational Electronic Structure Calculations. Journal of Chemical Information and Modeling. 63(15). 4679–4690. 5 indexed citations
14.
Ao, Yu‐Fei, Lin Shen, Chenghai Sun, et al.. (2023). Structure‐ and Data‐Driven Protein Engineering of Transaminases for Improving Activity and Stereoselectivity. Angewandte Chemie International Edition. 62(23). e202301660–e202301660. 29 indexed citations
15.
Liu, L.H., et al.. (2023). Machine Learning Prediction of Hydration Free Energy with Physically Inspired Descriptors. The Journal of Physical Chemistry Letters. 14(7). 1877–1884. 11 indexed citations
17.
Shen, Lin, et al.. (2022). Fewest-Switches Surface Hopping with Long Short-Term Memory Networks. The Journal of Physical Chemistry Letters. 13(44). 10377–10387. 12 indexed citations
18.
Shen, Lin, et al.. (2020). Role of Multistate Intersections in Photochemistry. The Journal of Physical Chemistry Letters. 11(20). 8490–8501. 20 indexed citations
19.
Shen, Lin, et al.. (2019). Quantum Trajectory Mean-Field Method for Nonadiabatic Dynamics in Photochemistry. The Journal of Physical Chemistry A. 123(34). 7337–7350. 11 indexed citations
20.
Fang, Wei‐Hai, et al.. (2019). Combining Meyer–Miller Hamiltonian with electronic structure methods for on-the-fly nonadiabatic dynamics simulations: implementation and application. Physical Chemistry Chemical Physics. 21(31). 17109–17117. 18 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026