Han Hao
Impact in
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- Scientific Computing and Data Management
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- Machine Learning in Materials Science
Papers in
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- Machine Learning in Materials Science 5
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- Innovative Microfluidic and Catalytic Techniques Innovation 6
- Co-authors
- Alán Aspuru‐Guzik (11 shared papers)Sergio Pablo‐García (6 shared papers)Kourosh Darvish (3 shared papers)Felix Strieth‐Kalthoff (2 shared papers)Yang Cao (4 shared papers)Naruki Yoshikawa (4 shared papers)Marta Skreta (2 shared papers)Martin Seifrid (3 shared papers)
- Journals
- RSC Advances (2 papers)Chemical Science (2 papers)Construction and Building Materials (2 papers)Matter (2 papers)Advanced Materials (2 papers)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Han Hao
45 papers receiving 774 citations
Han Hao's Hit Papers
Peers
Comparison fields: 5 of 94
- Information Systems and Management 42
- Materials Chemistry 253
- Inorganic Chemistry 63
- Electrochemistry 25
- Renewable Energy, Sustainability and the Environment 66
Countries citing papers authored by Han Hao
This map shows the geographic impact of Han Hao'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 Han Hao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Han Hao more than expected).
Fields of papers citing papers by Han Hao
This network shows the impact of papers produced by Han Hao. 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 Han Hao. The network helps show where Han Hao may publish in the future.
Co-authors
The 25 scholars most cited alongside Han Hao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Self-Driving Laboratories for Chemistry and Materials Science Hit paper breakdown → | 2024 | 269 |
| 2 | 2024 | 56 | |
| 3 | 2024 | 48 | |
| 4 | 2022 | 38 | |
| 5 | 2015 | 38 | |
| 6 | 2021 | 36 | |
| 7 | 2022 | 24 | |
| 8 | 2019 | 23 | |
| 9 | 2023 | 15 | |
| 10 | 2025 | 14 | |
| 11 | 2017 | 14 | |
| 12 | 2025 | 14 | |
| 13 | 2017 | 14 | |
| 14 | 2017 | 13 | |
| 15 | 2016 | 13 | |
| 16 | 2020 | 13 | |
| 17 | 2014 | 12 | |
| 18 | 2024 | 11 | |
| 19 | 2024 | 10 | |
| 20 | 2018 | 9 |
About Han Hao
Han Hao is a scholar working on Materials Chemistry, Biomedical Engineering, Organic Chemistry, Electrical and Electronic Engineering and Inorganic Chemistry, having authored 50 papers that have together received 785 indexed citations. Recurring topics across this work include Advanced Photocatalysis Techniques (7 papers), Innovative Microfluidic and Catalytic Techniques Innovation (6 papers), Catalytic C–H Functionalization Methods (5 papers), Machine Learning in Materials Science (5 papers), Metal-Organic Frameworks: Synthesis and Applications (4 papers), Asymmetric Hydrogenation and Catalysis (4 papers), Catalytic Alkyne Reactions (3 papers) and Scientific Computing and Data Management (3 papers). The work is most often cited by research in Information Systems and Management (42 citations), Materials Chemistry (253 citations), Inorganic Chemistry (63 citations), Electrochemistry (25 citations) and Renewable Energy, Sustainability and the Environment (66 citations). Han Hao has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Alán Aspuru‐Guzik, Sergio Pablo‐García, Kourosh Darvish, Felix Strieth‐Kalthoff, Yang Cao, Naruki Yoshikawa, Marta Skreta, Martin Seifrid, Gun Deniz Akkoc and Gary Tom. Their work appears in journals such as RSC Advances, Chemical Science, Construction and Building Materials, Matter and Advanced 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.