Hao‐Wei Pang

438 total citations
18 papers, 263 citations indexed

About

Hao‐Wei Pang is a scholar working on Materials Chemistry, Renewable Energy, Sustainability and the Environment and Organic Chemistry. According to data from OpenAlex, Hao‐Wei Pang has authored 18 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Materials Chemistry, 4 papers in Renewable Energy, Sustainability and the Environment and 3 papers in Organic Chemistry. Recurrent topics in Hao‐Wei Pang's work include Machine Learning in Materials Science (5 papers), Advanced Photocatalysis Techniques (4 papers) and TiO2 Photocatalysis and Solar Cells (4 papers). Hao‐Wei Pang is often cited by papers focused on Machine Learning in Materials Science (5 papers), Advanced Photocatalysis Techniques (4 papers) and TiO2 Photocatalysis and Solar Cells (4 papers). Hao‐Wei Pang collaborates with scholars based in United States, Taiwan and Israel. Hao‐Wei Pang's co-authors include Kuo–Chuan Ho, Yi‐June Huang, William H. Green, Chun‐Ting Li, Chuan‐Pei Lee, Matthew S. Johnson, R. Vittal, A. Mark Payne, Colin A. Grambow and Mengjie Liu and has published in prestigious journals such as Journal of Materials Chemistry A, Construction and Building Materials and Industrial & Engineering Chemistry Research.

In The Last Decade

Hao‐Wei Pang

15 papers receiving 256 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hao‐Wei Pang United States	8	122	74	64	36	31	18	263
Tammie L. Borders United States	9	334 2.7×	55 0.7×	39 0.6×	62 1.7×	26 0.8×	12	453
Michael D. Bronshtein Russia	11	91 0.7×	135 1.8×	219 3.4×	34 0.9×	11 0.4×	22	412
Rathindra Nath Das India	11	176 1.4×	20 0.3×	29 0.5×	38 1.1×	7 0.2×	31	374
Florian Becker Germany	8	63 0.5×	36 0.5×	61 1.0×	62 1.7×	4 0.1×	14	333
J. Wesley Barnett United States	8	150 1.2×	8 0.1×	76 1.2×	79 2.2×	34 1.1×	13	358
Igor V. Volgin Russia	9	151 1.2×	8 0.1×	42 0.7×	103 2.9×	15 0.5×	14	356
Matthew J. O’Malley United States	9	102 0.8×	26 0.4×	80 1.3×	48 1.3×	27 0.9×	23	422
E Xiu‐tian‐feng China	14	175 1.4×	33 0.4×	31 0.5×	259 7.2×	5 0.2×	23	591
Andy S. Anker Denmark	11	203 1.7×	66 0.9×	52 0.8×	38 1.1×	7 0.2×	26	307

Countries citing papers authored by Hao‐Wei Pang

Since Specialization

Citations

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

Fields of papers citing papers by Hao‐Wei Pang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hao‐Wei Pang. 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 Hao‐Wei Pang. The network helps show where Hao‐Wei Pang may publish in the future.

Co-authorship network of co-authors of Hao‐Wei Pang

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

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Graff, David, et al.. (2025). Chemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property Prediction. Journal of Chemical Information and Modeling. 66(1). 28–33.

Qi, Wenyue, et al.. (2025). Predictive Modelling of Alkali-Slag Cemented Tailings Backfill Using a Novel Machine Learning Approach. Materials. 18(6). 1236–1236. 1 indexed citations

Pang, Hao‐Wei, et al.. (2025). RIGR: Resonance-Invariant Graph Representation for Molecular Property Prediction. Journal of Chemical Information and Modeling. 65(20). 10832–10843. 1 indexed citations

Wu, Haoyang, et al.. (2025). Toward Accurate Quantum Mechanical Thermochemistry: (2) Optimal Methods for Enthalpy Calculations from Comprehensive Benchmarks of 284 Model Chemistries. The Journal of Physical Chemistry A. 129(17). 3949–3962.

Qi, Wenyue, Qingxin Zhao, Yanli Huang, et al.. (2024). A novel alkali-slag cemented tailings backfill: Recycling of soda residue and calcium carbide slag. Construction and Building Materials. 445. 137875–137875. 16 indexed citations

Pang, Hao‐Wei, et al.. (2024). Oxygen Chemistry in Polymer Fouling: Insights from Multiphase Detailed Kinetic Modeling. Industrial & Engineering Chemistry Research. 63(2). 1013–1028. 3 indexed citations

Pang, Hao‐Wei, et al.. (2024). Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation. The Journal of Physical Chemistry A. 128(14). 2891–2907. 6 indexed citations

Johnson, Matthew S., Hao‐Wei Pang, A. Mark Payne, & William H. Green. (2024). ReactionMechanismSimulator.jl: A modern approach to chemical kinetic mechanism simulation and analysis. International Journal of Chemical Kinetics. 56(12). 732–747. 5 indexed citations

Johnson, Matthew S., Hao‐Wei Pang, Mengjie Liu, & William H. Green. (2024). Species selection for automatic chemical kinetic mechanism generation. International Journal of Chemical Kinetics. 57(2). 93–107. 3 indexed citations

10.

Wu, Haoyang, A. Mark Payne, Hao‐Wei Pang, et al.. (2024). Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions. The Journal of Physical Chemistry A. 128(21). 4335–4352. 7 indexed citations

11.

Pang, Hao‐Wei, et al.. (2023). Detailed Multiphase Chemical Kinetic Model for Polymer Fouling in a Distillation Column. Industrial & Engineering Chemistry Research. 62(36). 14266–14285. 7 indexed citations

12.

Johnson, Matthew S., Alon Grinberg Dana, Yunsie Chung, et al.. (2022). RMG Database for Chemical Property Prediction. Journal of Chemical Information and Modeling. 62(20). 4906–4915. 88 indexed citations

13.

Pang, Hao‐Wei, et al.. (2020). Formation of Two-Ring Aromatics in Hexylbenzene Pyrolysis. Energy & Fuels. 34(2). 1365–1377. 6 indexed citations

14.

Pang, Hao‐Wei, et al.. (2018). Electrospun membranes of imidazole-grafted PVDF-HFP polymeric ionic liquids for highly efficient quasi-solid-state dye-sensitized solar cells. Journal of Materials Chemistry A. 6(29). 14215–14223. 38 indexed citations

15.

Lee, Chuan‐Pei, et al.. (2018). One-step synthesis of graphene hollow nanoballs with various nitrogen-doped states for electrocatalysis in dye-sensitized solar cells. Materials Today Energy. 8. 15–21. 20 indexed citations

16.

Huang, Yi‐June, Chuan‐Pei Lee, Hao‐Wei Pang, et al.. (2017). Microemulsion-controlled synthesis of CoSe 2 /CoSeO 3 composite crystals for electrocatalysis in dye-sensitized solar cells. Materials Today Energy. 6. 189–197. 22 indexed citations

17.

Kao, Sheng−Yuan, Hsin−Che Lu, Yi‐Feng Lin, et al.. (2017). Electrospun nanofibers composed of poly(vinylidene fluoride-co-hexafluoropropylene) and poly(oxyethylene)-imide imidazolium tetrafluoroborate as electrolytes for solid-state electrochromic devices. Solar Energy Materials and Solar Cells. 177. 32–43. 17 indexed citations

18.

Li, Chun‐Ting, Chuan‐Pei Lee, R. Vittal, et al.. (2017). Hierarchical TiO_1.1Se_0.9-wrapped carbon cloth as the TCO-free and Pt-free counter electrode for iodide-based and cobalt-based dye-sensitized solar cells. Journal of Materials Chemistry A. 5(27). 14079–14091. 23 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