Henry Chan

4.5k citations

74 papers · 3.5k indexed · 1 hit paper · h-index 29

Impact in

Materials Chemistry top 2%
- Machine Learning in Materials Science
- Pickering emulsions and particle stabilization
- Quantum Dots Synthesis And Properties
- Nanocluster Synthesis and Applications
- 2D Materials and Applications
Structural Biology top 5%

Papers in

Structural Biology 2
Materials Chemistry 45
- Machine Learning in Materials Science 28
- Graphene research and applications 5
- Quantum Dots Synthesis And Properties 5
- 2D Materials and Applications 5

Co-authors: Subramanian K. R. S. Sankaranarayanan Petr Král Mathew J. Cherukara Badri Narayanan Troy D. Loeffler Rafał Klajn Gurvinder Singh Artem Baskin
Journals: npj Computational Materials (6 papers)Nature Communications (6 papers)ACS Nano (6 papers)Nanoscale (5 papers)Chemistry of Materials (4 papers)
Partner nations: United States India Spain

In The Last Decade

Henry Chan

72 papers receiving 3.4k citations

Hit Papers

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Machine learning enabled autonomous microstructural characterization in 3D samples 2020 · 324 citations

Peers

Countries citing papers authored by Henry Chan

Since Specialization

Citations

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

Fields of papers citing papers by Henry Chan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Henry Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Henry Chan Line = papers co-authored together Henry Chan links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite Chemistry of Materials ·Muhammad Babar Imtiaz, Mark J. Meijerink, T. Noguchi, Henry Chan, Nurul Astuti, Ilke Arslan, Subramanian K. R. S. Sankaranarayanan, Valeria Molinero	2025	1
2	Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning The Journal of Physical Chemistry A ·Yoo-Shin Jo, T. B. BLATHWAYT, Karthik Balasubramanian, Kiran Sasikumar, Sukriti Manna, Henry Chan, Subramanian K. R. S. Sankaranarayanan	2024	3
3	Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures The Journal of Chemical Physics ·王若凡, Troy D. Loeffler, Henry Chan, Xiaoyu Wang, G. B. Stephenson, Michael J. Servis, Subramanian K. R. S. Sankaranarayanan	2023	3
4	A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery npj Computational Materials ·Suvo Banik, A Wilson Valencia, Sukriti Manna, Henry Chan, Srilok Srinivasan, Pierre Darancet, Alexander Hexemer, Subramanian K. R. S. Sankaranarayanan	2023	16
5	CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment npj Computational Materials ·Suvo Banik, Debdas Dhabal, Henry Chan, Sukriti Manna, Mathew J. Cherukara, Valeria Molinero, Subramanian K. R. S. Sankaranarayanan	2023	33
6	Understanding and control of Zener pinning via phase field and ensemble learning Computational Materials Science ·Sukriti Manna, Henry Chan, Avishek Ghosh, Tamoghna Chakrabarti, Subramanian K. R. S. Sankaranarayanan	2023	21
7	Defect identification in simulated Bragg coherent diffraction imaging by automated AI MRS Bulletin ·W. James Judge, Henry Chan, Subramanian K. R. S. Sankaranarayanan, Ross Harder, Jordi Cabana, Mathew J. Cherukara	2022	5
8	Learning in continuous action space for developing high dimensional potential energy models Nature Communications ·Sukriti Manna, Troy D. Loeffler, Rohit Batra, Suvo Banik, Henry Chan, Uich NAKAMURA, Kiran Sasikumar, Michael Sternberg, Tom Peterka, Mathew J. Cherukara, Stephen K. Gray, Bobby G. Sumpter, Subramanian K. R. S. Sankaranarayanan	2022	41
9	Machine learning overcomes human bias in the discovery of self-assembling peptides Nature Chemistry ·Rohit Batra, Troy D. Loeffler, Henry Chan, A. Zhokin, Honggang Cui, Ivan V. Korendovych, Vikas Nanda, Liam C. Palmer, Lee A. Solomon, H. Christopher Fry, Subramanian K. R. S. Sankaranarayanan	2022	100
10	Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data The Journal of Physical Chemistry C ·Troy D. Loeffler, Tarak K. Patra, Henry Chan, Mathew J. Cherukara, Subramanian K. R. S. Sankaranarayanan	2020	28
11	Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies The Journal of Physical Chemistry Letters ·Rohit Batra, Henry Chan, Ganesh Kamath, Rampi Ramprasad, Mathew J. Cherukara, Subramanian K. R. S. Sankaranarayanan	2020	66
12	Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures Chemistry of Materials ·Kiran Sasikumar, Henry Chan, Badri Narayanan, Subramanian K. R. S. Sankaranarayanan	2019	19
13	Ligand dynamics control structure, elasticity, and high-pressure behavior of nanoparticle superlattices Nanoscale ·Tarak K. Patra, Henry Chan, Paul Podsiadlo, Elena V. Shevchenko, Subramanian K. R. S. Sankaranarayanan, Badri Narayanan	2019	21
14	Machine learning a bond order potential model to study thermal transport in WSe₂nanostructures Nanoscale ·Henry Chan, Kiran Sasikumar, Srilok Srinivasan, Mathew J. Cherukara, Badri Narayanan, Subramanian K. R. S. Sankaranarayanan	2019	28
15	Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data The Journal of Physical Chemistry C ·Henry Chan, Badri Narayanan, Mathew J. Cherukara, Fatih G. Sen, Kiran Sasikumar, Stephen K. Gray, Maria K. Y. Chan, Subramanian K. R. S. Sankaranarayanan	2019	80
16	Defect Dynamics in 2-D MoS₂ Probed by Using Machine Learning, Atomistic Simulations, and High-Resolution Microscopy ACS Nano ·Tarak K. Patra, Fu Zhang, Daniel S. Schulman, Henry Chan, Mathew J. Cherukara, Mauricio Terrones, Saptarshi Das, Badri Narayanan, Subramanian K. R. S. Sankaranarayanan	2018	87
17	Crude-Oil-Repellent Membranes by Atomic Layer Deposition: Oxide Interface Engineering ACS Nano ·Hao‐Cheng Yang, Yunsong Xie, Henry Chan, Badri Narayanan, Lin Chen, Ruben Z. Waldman, Subramanian K. R. S. Sankaranarayanan, Jeffrey W. Elam, Seth B. Darling	2018	162
18	Thermomechanical Response of Self-Assembled Nanoparticle Membranes ACS Nano ·Yifan Wang, Henry Chan, Badri Narayanan, Sean McBride, Subramanian K. R. S. Sankaranarayanan, Xiao‐Min Lin, Heinrich M. Jaeger	2017	14
19	Machine learnt bond order potential to model metal–organic (Co–C) heterostructures Nanoscale ·Badri Narayanan, Henry Chan, Alper Kınacı, Fatih G. Sen, Stephen K. Gray, Maria K. Y. Chan, Subramanian K. R. S. Sankaranarayanan	2017	13
20	Carbon‐Encapsulated Radioactive ^99mTc Nanoparticles Advanced Materials ·Henry Chan, Rohman, Horrick Sharma, William Frost, Valérie Caps, R. A. Shields, Tingkai Yang	2004	31

About Henry Chan

Henry Chan is a scholar working on Structural Biology, Materials Chemistry, Surfaces, Coatings and Films, Physical and Theoretical Chemistry and Radiation, having authored 74 papers that have together received 3.5k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (28 papers), nanoparticles nucleation surface interactions (8 papers), Advanced Memory and Neural Computing (6 papers), Computational Drug Discovery Methods (6 papers), Graphene research and applications (5 papers), Quantum Dots Synthesis And Properties (5 papers), 2D Materials and Applications (5 papers) and Protein Structure and Dynamics (4 papers). The work is most often cited by research in Materials Chemistry (1.9k citations), Structural Biology (54 citations), Biomaterials (399 citations), Surfaces, Coatings and Films (208 citations) and Electronic, Optical and Magnetic Materials (495 citations). Henry Chan has collaborated with scholars based in United States, India and Spain. Frequent co-authors include Subramanian K. R. S. Sankaranarayanan, Petr Král, Mathew J. Cherukara, Badri Narayanan, Troy D. Loeffler, Rafał Klajn, Gurvinder Singh, Artem Baskin, Stephen K. Gray and Gongpu Zhao. Their work appears in journals such as npj Computational Materials, Nature Communications, ACS Nano, Nanoscale and Chemistry of 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.

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