Yuanbin Liu

1.3k total citations
40 papers, 1.0k citations indexed

About

Yuanbin Liu is a scholar working on Materials Chemistry, Biomedical Engineering and Computational Mechanics. According to data from OpenAlex, Yuanbin Liu has authored 40 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Materials Chemistry, 11 papers in Biomedical Engineering and 9 papers in Computational Mechanics. Recurrent topics in Yuanbin Liu's work include Machine Learning in Materials Science (11 papers), Advanced Welding Techniques Analysis (5 papers) and Thermochemical Biomass Conversion Processes (5 papers). Yuanbin Liu is often cited by papers focused on Machine Learning in Materials Science (11 papers), Advanced Welding Techniques Analysis (5 papers) and Thermochemical Biomass Conversion Processes (5 papers). Yuanbin Liu collaborates with scholars based in China, United Kingdom and Australia. Yuanbin Liu's co-authors include Bing Cao, Qingjie Sun, Linhua Liu, Weixiang Hong, J.C. Feng, Jun Qiu, M. A. F. Kendall, Jingjing Zhang, Hongbo Xü and Yan Liu and has published in prestigious journals such as Advanced Materials, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Yuanbin Liu

39 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuanbin Liu China 18 288 267 246 203 122 40 1.0k
Yufeng Su China 19 191 0.7× 334 1.3× 211 0.9× 359 1.8× 44 0.4× 91 1.2k
Roozbeh Sabetvand Iran 17 231 0.8× 283 1.1× 374 1.5× 88 0.4× 31 0.3× 56 814
Jerry W. Shan United States 24 166 0.6× 425 1.6× 868 3.5× 63 0.3× 158 1.3× 68 1.5k
Qiang Wen China 18 132 0.5× 940 3.5× 207 0.8× 219 1.1× 119 1.0× 61 1.6k
Jayanta Chakraborty India 20 338 1.2× 481 1.8× 157 0.6× 74 0.4× 140 1.1× 58 1.0k
Lucien Brush United States 14 136 0.5× 371 1.4× 190 0.8× 109 0.5× 40 0.3× 37 642
Qiang Xue China 20 120 0.4× 425 1.6× 452 1.8× 141 0.7× 317 2.6× 74 1.1k
Rodney Herring Canada 12 300 1.0× 419 1.6× 87 0.4× 168 0.8× 18 0.1× 61 925
Shuang Zhang China 16 171 0.6× 265 1.0× 315 1.3× 96 0.5× 42 0.3× 83 1.0k

Countries citing papers authored by Yuanbin Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yuanbin Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuanbin Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Yuanbin Liu. A scholar is included among the top collaborators of Yuanbin Liu 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 Yuanbin Liu. Yuanbin Liu 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.
Liu, Yuanbin, et al.. (2025). Lattice dynamics modeling of thermal transport in solids using machine-learned atomic cluster expansion potentials: A tutorial. Journal of Applied Physics. 137(8). 3 indexed citations
2.
Liu, Yuanbin, Christina Ertural, Aakash Ashok Naik, et al.. (2025). An automated framework for exploring and learning potential-energy surfaces. Nature Communications. 16(1). 7666–7666. 5 indexed citations
3.
Liu, Yuanbin, et al.. (2024). The amorphous state as a frontier in computational materials design. Nature Reviews Materials. 10(3). 228–241. 18 indexed citations
4.
Liu, Yuanbin, et al.. (2024). Machine-learned atomic cluster expansion potentials for fast and quantum-accurate thermal simulations of wurtzite AlN. Journal of Applied Physics. 135(8). 9 indexed citations
5.
Liu, Yuanbin, Xin Liu, & Bing Cao. (2024). Graph attention neural networks for mapping materials and molecules beyond short-range interatomic correlations. Journal of Physics Condensed Matter. 36(21). 215901–215901. 3 indexed citations
6.
Liu, Yuanbin, et al.. (2024). Short-term residential load forecasting via transfer learning and multi-attention fusion for EVs’ coordinated charging. International Journal of Electrical Power & Energy Systems. 164. 110349–110349. 7 indexed citations
7.
Liu, Yuanbin, Huili Liang, Shuang Song, et al.. (2023). Unraveling Thermal Transport Correlated with Atomistic Structures in Amorphous Gallium Oxide via Machine Learning Combined with Experiments. Advanced Materials. 35(24). e2210873–e2210873. 40 indexed citations
8.
Zhang, Luyu, Wenjie Zhang, Yuanbin Liu, & Linhua Liu. (2023). Three-Layered Thin Films for Simultaneous Infrared Camouflage and Radiative Cooling. Materials. 16(11). 4188–4188. 11 indexed citations
9.
Liu, Yuanbin, Weixiang Hong, & Bing Cao. (2022). MolNet‐3D: Deep Learning of Molecular Representations and Properties from 3D Topography. Advanced Theory and Simulations. 5(6). 5 indexed citations
10.
Shen, Yang, Yuanbin Liu, & Bing Cao. (2021). C4+ Surrogate Models for Thermophysical Properties of Aviation Kerosene RP-3 at Supercritical Pressures. Energy & Fuels. 35(9). 7858–7865. 10 indexed citations
11.
Liu, Yuanbin, Jia‐Yue Yang, Gongming Xin, et al.. (2020). Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O3. The Journal of Chemical Physics. 153(14). 144501–144501. 79 indexed citations
12.
Liu, Yuanbin & Bing Cao. (2020). Thermodynamic models for H2O–CO2–H2 mixtures in near-critical and supercritical regions of water. International Journal of Hydrogen Energy. 45(7). 4297–4304. 16 indexed citations
13.
Liu, Yuanbin, Jun Qiu, Linhua Liu, & Bing Cao. (2019). Extracting optical constants of solid materials with micro-rough surfaces from ellipsometry without using effective medium approximation. Optics Express. 27(13). 17667–17667. 8 indexed citations
14.
Liu, Yuanbin, Qingjie Sun, Qingjie Sun, et al.. (2019). Optimization of magnetic oscillation system and microstructural characteristics in arc welding of Al/Mg alloys. Journal of Manufacturing Processes. 39. 69–78. 21 indexed citations
15.
Sun, Qingjie, et al.. (2016). Microstructure and mechanical properties of ultrasonic assisted underwater wet welding joints. Materials & Design. 103. 63–70. 69 indexed citations
16.
Qiu, Jun, et al.. (2016). Investigation of ellipsometric parameters of 2D microrough surfaces by FDTD. Applied Optics. 55(20). 5423–5423. 7 indexed citations
17.
18.
Liu, Yuanbin, et al.. (2007). Characteristics of a micro-biolistic system for murine immunological studies. Biomedical Microdevices. 9(4). 465–474. 9 indexed citations
19.
Liu, Yuanbin. (2007). Simulations of transient shock motion within a biological contoured-shock-tube system. Physica D Nonlinear Phenomena. 237(2). 233–242. 2 indexed citations
20.
Liu, Yuanbin, et al.. (2006). Gas and Particle Dynamics of a Contoured Shock Tube for Pre-clinical Microparticle Drug Delivery. Shock Waves. 15(3-4). 149–164. 20 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.

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