Harold W. Hatch

738 total citations
41 papers, 548 citations indexed

About

Harold W. Hatch is a scholar working on Materials Chemistry, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, Harold W. Hatch has authored 41 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Materials Chemistry, 15 papers in Biomedical Engineering and 12 papers in Molecular Biology. Recurrent topics in Harold W. Hatch's work include Phase Equilibria and Thermodynamics (13 papers), Material Dynamics and Properties (10 papers) and Protein Structure and Dynamics (8 papers). Harold W. Hatch is often cited by papers focused on Phase Equilibria and Thermodynamics (13 papers), Material Dynamics and Properties (10 papers) and Protein Structure and Dynamics (8 papers). Harold W. Hatch collaborates with scholars based in United States, Egypt and Slovakia. Harold W. Hatch's co-authors include Vincent K. Shen, Henry S. Ashbaugh, Nathan A. Mahynski, Pablo G. Debenedetti, Jeetain Mittal, Frank H. Stillinger, Daniel W. Siderius, Marco A. Blanco, Jeffrey R. Errington and Joseph E. Curtis and has published in prestigious journals such as Journal of the American Chemical Society, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.

In The Last Decade

Harold W. Hatch

35 papers receiving 546 citations

Peers

Harold W. Hatch
Harold W. Hatch
Citations per year, relative to Harold W. Hatch Harold W. Hatch (= 1×) peers А. В. Аникеенко

Countries citing papers authored by Harold W. Hatch

Since Specialization
Citations

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

Fields of papers citing papers by Harold W. Hatch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Harold W. Hatch. 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 Harold W. Hatch. The network helps show where Harold W. Hatch may publish in the future.

Co-authorship network of co-authors of Harold W. Hatch

This figure shows the co-authorship network connecting the top 25 collaborators of Harold W. Hatch. A scholar is included among the top collaborators of Harold W. Hatch 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 Harold W. Hatch. Harold W. Hatch 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.
Hatch, Harold W., David S. Corti, David A. Kofke, & Vincent K. Shen. (2025). Best Practices for Developing Monte Carlo Methodologies in Molecular Simulations [Article v1.0]. 6(1). 3289–3289.
2.
Yeh, Chen‐Hao, Harold W. Hatch, Bhuvnesh Bharti, et al.. (2025). Colloidal Monolayers with Short-Range Attractions and Dipolar Repulsions. The Journal of Physical Chemistry B. 129(25). 6428–6438.
3.
Chremos, Alexandros, William P. Krekelberg, Harold W. Hatch, et al.. (2025). Development of SAFT-Based Coarse-Grained Models of Carbon Dioxide and Nitrogen. The Journal of Physical Chemistry B. 129(13). 3443–3453.
4.
Hatch, Harold W., Christina Bergonzo, Marco A. Blanco, et al.. (2024). Anisotropic coarse-grain Monte Carlo simulations of lysozyme, lactoferrin, and NISTmAb by precomputing atomistic models. The Journal of Chemical Physics. 161(9). 3 indexed citations
5.
Hatch, Harold W., Daniel W. Siderius, & Vincent K. Shen. (2024). Monte Carlo molecular simulations with FEASST version 0.25.1. The Journal of Chemical Physics. 161(9). 6 indexed citations
6.
Siderius, Daniel W., et al.. (2024). Elucidating Thermodynamically Driven Structure–Property Relations for Zeolite Adsorption Using Neural Networks. SHILAP Revista de lepidopterología. 4(12). 4673–4690. 5 indexed citations
7.
Yuan, Guangcui, Paul F. Salipante, Steven D. Hudson, et al.. (2024). Flow Activation Energy of High-Concentration Monoclonal Antibody Solutions and Protein–Protein Interactions Influenced by NaCl and Sucrose. Molecular Pharmaceutics. 21(9). 4553–4564. 5 indexed citations
8.
Xu, Amy Y., Marco A. Blanco, Maria Monica Castellanos, et al.. (2023). Role of Domain–Domain Interactions on the Self-Association and Physical Stability of Monoclonal Antibodies: Effect of pH and Salt. The Journal of Physical Chemistry B. 127(39). 8344–8357. 8 indexed citations
9.
Hatch, Harold W., et al.. (2023). pH response of sequence-controlled polyampholyte brushes. Soft Matter. 19(23). 4333–4344. 11 indexed citations
10.
Hatch, Harold W., Daniel W. Siderius, Jeffrey R. Errington, & Vincent K. Shen. (2023). Efficiency Comparison of Single- and Multiple-Macrostate Grand Canonical Ensemble Transition-Matrix Monte Carlo Simulations. The Journal of Physical Chemistry B. 127(13). 3041–3051. 8 indexed citations
11.
Siderius, Daniel W., Harold W. Hatch, Jeffrey R. Errington, & Vincent K. Shen. (2022). Comments on “Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights”. AIChE Journal. 68(8). 7 indexed citations
12.
Siderius, Daniel W., Harold W. Hatch, & Vincent K. Shen. (2022). Temperature Extrapolation of Henry’s Law Constants and the Isosteric Heat of Adsorption. The Journal of Physical Chemistry B. 126(40). 7999–8009. 8 indexed citations
13.
Murphy, Ryan P., Harold W. Hatch, Nathan A. Mahynski, Vincent K. Shen, & Norman J. Wagner. (2020). Dynamic arrest of adhesive hard rod dispersions. Soft Matter. 16(5). 1279–1286. 10 indexed citations
14.
Hatch, Harold W.. (2020). Parallel Prefetching for Canonical Ensemble Monte Carlo Simulations. The Journal of Physical Chemistry A. 124(35). 7191–7198. 2 indexed citations
15.
Blanco, Marco A., Harold W. Hatch, Joseph E. Curtis, & Vincent K. Shen. (2018). A methodology to calculate small-angle scattering profiles of macromolecular solutions from molecular simulations in the grand-canonical ensemble. The Journal of Chemical Physics. 149(8). 84203–84203. 3 indexed citations
16.
Blanco, Marco A., Harold W. Hatch, Joseph E. Curtis, & Vincent K. Shen. (2018). Evaluating the Effects of Hinge Flexibility on the Solution Structure of Antibodies at Concentrated Conditions. Journal of Pharmaceutical Sciences. 108(5). 1663–1674. 15 indexed citations
17.
Hatch, Harold W., Nathan A. Mahynski, Ryan P. Murphy, Marco A. Blanco, & Vincent K. Shen. (2018). Monte Carlo simulation of cylinders with short-range attractions. AIP Advances. 8(9). 95210–95210. 9 indexed citations
18.
Hatch, Harold W., Sally Jiao, Nathan A. Mahynski, Marco A. Blanco, & Vincent K. Shen. (2017). Communication: Predicting virial coefficients and alchemical transformations by extrapolating Mayer-sampling Monte Carlo simulations. The Journal of Chemical Physics. 147(23). 231102–231102. 14 indexed citations
19.
Hatch, Harold W., et al.. (2016). Self-assembly of trimer colloids: effect of shape and interaction range. Soft Matter. 12(18). 4170–4179. 23 indexed citations
20.
Ashbaugh, Henry S., et al.. (2010). Assessing the thermodynamic signatures of hydrophobic hydration for several common water models. The Journal of Chemical Physics. 132(12). 124504–124504. 71 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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