Ming-Chiang Chang

407 total citations
9 papers, 326 citations indexed

About

Ming-Chiang Chang is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Ming-Chiang Chang has authored 9 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Materials Chemistry, 3 papers in Electrical and Electronic Engineering and 2 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Ming-Chiang Chang's work include Machine Learning in Materials Science (2 papers), Advanced Thermoelectric Materials and Devices (2 papers) and Thermal properties of materials (1 paper). Ming-Chiang Chang is often cited by papers focused on Machine Learning in Materials Science (2 papers), Advanced Thermoelectric Materials and Devices (2 papers) and Thermal properties of materials (1 paper). Ming-Chiang Chang collaborates with scholars based in United States, Switzerland and Australia. Ming-Chiang Chang's co-authors include Carla P. Gomes, G. Jeffrey Snyder, E. Wu, Michael O. Thompson, Nabila El‐Bassel, R. B. van Dover, Louisa Gilbert, Nicholas R. Geisendorfer, Cheng‐Hung Hou and Cheng‐Yen Wen and has published in prestigious journals such as Nature Communications, Applied Physics Letters and Acta Materialia.

In The Last Decade

Ming-Chiang Chang

8 papers receiving 320 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming-Chiang Chang United States 6 216 81 53 39 37 9 326
Moojoon Kim South Korea 8 85 0.4× 58 0.7× 203 3.8× 9 0.2× 27 0.7× 66 345
Zhuojun Li China 12 184 0.9× 54 0.7× 42 0.8× 46 1.2× 32 0.9× 32 406
Kou Yang China 13 119 0.6× 185 2.3× 150 2.8× 4 0.1× 26 0.7× 43 440
Yong Xin China 14 359 1.7× 29 0.4× 39 0.7× 4 0.1× 16 0.4× 39 610
Mingun Lee United States 12 87 0.4× 89 1.1× 50 0.9× 8 0.2× 17 0.5× 21 327
William J. Bowers United States 11 151 0.7× 33 0.4× 58 1.1× 7 0.2× 74 2.0× 17 411
R. N. Patil India 11 493 2.3× 153 1.9× 32 0.6× 11 0.3× 9 0.2× 39 693
Antônio Carlos Seabra Brazil 11 67 0.3× 134 1.7× 147 2.8× 17 0.4× 4 0.1× 44 335
Lingyan Lin China 17 684 3.2× 950 11.7× 43 0.8× 12 0.3× 8 0.2× 69 1.2k
Tae‐Kwon Song South Korea 16 599 2.8× 259 3.2× 257 4.8× 10 0.3× 12 0.3× 28 735

Countries citing papers authored by Ming-Chiang Chang

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Chiang Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming-Chiang Chang. 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 Ming-Chiang Chang. The network helps show where Ming-Chiang Chang may publish in the future.

Co-authorship network of co-authors of Ming-Chiang Chang

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

All Works

9 of 9 papers shown
1.
Chang, Ming-Chiang, Maximilian Amsler, Lan Zhou, et al.. (2025). Probabilistic phase labeling and lattice refinement for autonomous materials research. npj Computational Materials. 11(1).
2.
Zhou, Lan, Aniketa Shinde, Ming-Chiang Chang, et al.. (2023). High throughput identification of complex rutile alloys for the acidic oxygen evolution reaction. Journal of Materials Chemistry A. 11(46). 25262–25267. 2 indexed citations
3.
Chang, Celesta S., et al.. (2022). Initial nucleation of metastable γ-Ga2O3 during sub-millisecond thermal anneals of amorphous Ga2O3. Applied Physics Letters. 121(6). 18 indexed citations
4.
Amsler, Maximilian, Ming-Chiang Chang, Dan Guevarra, et al.. (2021). Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams. Science Advances. 7(51). eabg4930–eabg4930. 54 indexed citations
5.
Chang, Ming-Chiang, Po‐Hsun Ho, Fangyuan Lin, et al.. (2020). Fast growth of large-grain and continuous MoS2 films through a self-capping vapor-liquid-solid method. Nature Communications. 11(1). 3682–3682. 103 indexed citations
6.
Peng, Jun, Ian T. Witting, Nicholas R. Geisendorfer, et al.. (2019). 3D extruded composite thermoelectric threads for flexible energy harvesting. Nature Communications. 10(1). 5590–5590. 70 indexed citations
7.
Chang, Ming-Chiang, Matthias T. Agne, Richard A. Michi, David C. Dunand, & G. Jeffrey Snyder. (2018). Compressive creep behavior of hot-pressed GeTe based TAGS-85 and effect of creep on thermoelectric properties. Acta Materialia. 158. 239–246. 17 indexed citations
8.
Lee, Agatha D., Natasha Leporé, Yi‐Yu Chou, et al.. (2009). The multivariate A/C/E model and the genetics of fiber architecture. PubMed. 2009. 125–128. 5 indexed citations
9.
El‐Bassel, Nabila, et al.. (2007). Intimate partner violence prevalence and HIV risks among women receiving care in emergency departments: implications for IPV and HIV screening. Emergency Medicine Journal. 24(4). 255–259. 57 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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2026