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  4. Huichun (Judy) Zhang

Huichun (Judy) Zhang, PhD

Frank H. Neff Professor, Department of Civil and Environmental Engineering, Case School of Engineering

Examines fate and transformation of organic and inorganic contaminants in natural and engineered environments, develops advanced water/wastewater treatment technologies, employs emerging AI and machine learning tools in various environmental applications.

Teaching Information

Teaching Interests

  • Environmental Organic Chemistry;
  • Water Chemistry;
  • Intro to Environmental Engineering

Research Information

Research Interests

  1. Predictive modeling based on AI and machine learning;
  2. Reduction-oxidation processes in complex mixtures;
  3. Transformation and fate of emerging contaminants in natural and engineered environments;
  4. Interfacial reaction of organic contaminants with natural minerals in complex mixtures;
  5. Polymeric sorbents for the removal of organic contaminants: sorption, ion exchange, novel sorbents, catalytic adsorption and reduction for in-situ regeneration;
  6. Novel Fe/Mn based redox active inorganic materials for contaminant removal;
  7. Capture of dissolved P from agricultural runoff

Awards and Honors

CAPEES Award for Environmental Application of AI/ML
2023
CAPEES
ACS Division of Environmental Chemistry C. Ellen Gonter Award
2025
American Chemical Society
ACS Division of Environmental Chemistry C. Ellen Gonter Award
2024
American Chemical Society
ACS Division of Environmental Chemistry C. Ellen Gonter Award
2023
American Chemical Society
Best Presentation Award
2022
International Congress on Separation and Purification Technology
2021 Best ES&T Paper Award
2022
Environmental Science & Technology
Outstanding Editor of 2021
2021
Frontiers of Environmental Science & Engineering (FESE)
Nanova/CAPEES Frontier Research Award
2019
CAPEES

Professional Memberships

2010 - Present, Member and 2017 President Chinese-American Professors in Environmental Engineering and Science (CAPEES)
2002 - Present, Member and Student award committee American Chemical Society
2023 - Present, Associate Editor ACS ES&T Water
2016 - Present, Member and Secretary Association of Environmental Engineering and Science Professors

Publications

  • Yu, P.; K. Zhang; X. Shi; Z. Zheng; and Zhang, H.*; 2026 “Active Learning-Guided Optimization of Moisture Swing Adsorption for Direct Air Capture”, Environ. Sci. Technol. ASAP
  • Zhang, H.*; P. G. Tratnyek; 2026 “In Silico Analysis of Contaminant Persistence: From QSARs to Machine Learning Models”, Environ. Sci. Technol. 60, 12, 8905–8922 (invited). https://doi.org/10.1021/acs.est.5c18542
  • D. Rao, J. Gao, H. Zhang,* and J. Liu*; 2026 “Advancing PFAS Detection through Machine Learning Prediction of 19F NMR spectra”, Environ. Sci. Technol., 60, 736-747. https://doi.org/10.1021/acs.est.5c12004
  • Fu, Xingjia; Sun, Jiachun; Tian, Kun; Liu, Yun; and Zhang, H.; 2025 “Predicting PFAS sorption capacity in soils: Meta-analysis and machine learning modeling”, Environ. Sci. Technol.  59(33), 17699–17710. https://doi.org/10.1021/acs.est.4c11313
  • Gao, Yidan, Camille Gimilaro and Zhang, H.*; 2025 “MnO2 and Oxygen Facilitate Organic Matter Formation via Oxidation and Catalysis in Oxygenated Alkaline Conditions”, Environ. Sci. Technol., 59, 25, 12618–12629. https://doi.org/10.1021/acs.est.4c14026
  • Kai Zhang and Zhang, H.*; 2025 “A data-centric approach for modeling small gas molecules adsorption on granular activated carbons”, Environ. Sci. Technol., 59, 22, 11063–11072. https://doi.org/10.1021/acs.est.4c12168
  • Lin, Chengrui; and Zhang, H.*; 2025 “Predictive models for polymer biodegradation kinetics”, Environ. Sci. Technol. 59, 2, 1253–1263. https://doi.org/10.1021/acs.est.4c11282
  • Liu, Zhao; L. Shang, K. Huang, Z. Yue, A. Y. Han, D. Wang, and Zhang, H.*; 2025 “Combining group contribution method and semi-supervised learning to build machine learning models for predicting hydroxyl radical rate constants of water contaminants”, Environ. Sci. Technol. 59, 1, 857–868. https://doi.org/10.1021/acs.est.4c11950 
  • Cheng, Yushu, Kai Zhang, Kuan Huang and Zhang, H.*; 2024 “Meta-Analysis and Machine Learning Models for Predicting Anaerobic Biodegradation Rates of Organic Contaminants in Sediments and Sludge”, Environ. Sci. Technol., 58, 29, 12976–12988. https://doi.org/10.1021/acs.est.4c01033 
  • Y. Huang, L. Bu, K. Huang, S. Zhou, and Zhang, H.; 2024 “Predicting odor sensory attributes of unidentified chemicals in water using fragmentation mass spectra with machine learning models". Environ. Sci. Technol., 58, 26, 11504–11513. https://doi.org/10.1021/acs.est.4c01763
  • J. Wang, F. Ju, P. Yu, J. Lou, M. Jiang, H. Zhang*, H. Lu*; 2024 “Metabolomics-based estimation of activated 1 sludge microbial composition and prediction of filamentous bulking". Water Res. 121805. https://doi.org/10.1016/j.watres.2024.121805
  • Ai, Haiping, Kai Zhan, Chad Penn, and Zhang, H.*; 2023 “Phosphate removal by low-cost industrial byproduct iron shavings: Efficacy and longevity”, Water Research., 120745. https://doi.org/10.1016/j.watres.2023.120745
  • Gao, Yidan, S. Zhong, K. Zhang, and Zhang, H.*; 2023 “Abiotic reduction of organic and inorganic compounds by Fe(II)-associated reductants: Comprehensive datasets and machine learning modeling”, Environ. Sci. Technol. 57, 46, 18026–18037
  • Ai, Haiping, Kai Zhang, Jiachun Sun, and Zhang, H.*; 2023 “Short-term Lake Erie algal bloom prediction by classification and regression models”, Water Res., 119710. https://doi.org/10.1016/j.watres.2023.119710
  • Banuelos, Jose; Borguet, Eric; Brown, Gordon; Cygan, Randall; De Yoreo, James; Dove, Patricia; Gaigeot, Marie-Pierre; Geiger, Franz; Gibbs, Julianne; Grassian, Vicki; Ilgen, Anastasia; Jun, Young-Shin; Kabengi, Nadine; Katz, Lynn; Kubicki, James; Lutzenkirchen, Johannes; Putnis, Christine; Remsing, Richard; Rosso, Kevin; Rother, Gernot; Sulpizi, Marialore; Villalobos, Mario; Zhang, Huichun. “Oxide- and Silicate-Water Interfaces and Their Roles in Technology and the Environment”. Chemical Reviews 2023, 123, 10, 6413–6544. https://doi.org/10.1021/acs.chemrev.2c00130
  • Huang, Kuan, and Zhang, H.*; 2022 “Classification and Regression machine learning models for predicting aerobic ready and inherent biodegradation of organic chemicals in water”, Environ. Sci. Technol. 56 (17), 12755-12764 https://doi.org/10.1021/acs.est.2c01764
  • Zhang, Kai and Zhang, H.*; 2022 “Predicting solute descriptors for organic chemicals by a deep neural network (DNN) using basic chemical structures and a surrogate metric”, Environ. Sci. Technol. 56, 3, 2054–2064. https://doi.org/10.1021/acs.est.1c05398
  • Huang, Kuan and Zhang, H.*; 2022 “A comprehensive kinetic model for phenol oxidation in seven advanced oxidation processes and considering the effects of halides and carbonate”, Water Res. X, 100129. https://doi.org/10.1016/j.wroa.2021.100129
  • Shifa Zhong, Yanping Zhang, Zhang, H.*, 2022 “Machine Learning-Assisted QSAR Models on Contaminant Reactivity Toward Four Oxidants: Combining Small Data Sets and Knowledge Transfer”. Environ. Sci. Technol.56, 1, 681–692. https://doi.org/10.1021/acs.est.1c04883
  • Hongrui Yang, Kuan Huang, Kai Zhang, Qin Weng, Zhang, H.*, Feier Wang; 2021”Predicting heavy metal adsorption in soil with machine learning and mapping global distribution of soil adsorption capacities”. Environ. Sci. Technol. 55 (20), 14316-14328 https://doi.org/10.1021/acs.est.1c02479
  • Shifa Zhong, Kai Zhang, Majid Bagheri, Joel G. Burken, April Gu, Baikun Li, Xingmao Ma, Babetta L. Marrone, Zhiyong Jason Ren, Joshua Schrier, Wei Shi, Haoyue Tan, Tianbao Wang, Xu Wang, Bryan M. Wong, Xusheng Xiao, Xiong Yu, Jun-Jie Zhu, Zhang, H.,* 2021 “Machine learning: New ideas and tools in Environmental Science and Engineering”, Invited feature article in Environ. Sci. Technol. 55, 19, 12741–12754. https://doi.org/10.1021/acs.est.1c01339. (2021 ES&T Best Paper Award) 
  • Huang, Jianzhi, A. Jones, T. D. Waite, Y. Chen, X. Huang, A. Jones, K. M. Rosso, A. Kappler, M. Mansor, P. G. Tratnyek, and Zhang, H.*; 2021 “Fe(II) Redox Chemistry in the Environment”, Chemical Reviews, 121, 13, 8161–8233. https://doi.org/10.1021/acs.chemrev.0c01286
  • Gao, Y., Zhong, S., Torralba-Sanchez, T., Tratnyek, P., Weber, E., Chen, Y., ... Zhang, H. (2021). Quantitative structure activity relationships (QSARs) and machine learning models for abiotic reduction of organic compounds by an aqueous Fe(II) complex. Water Res. 192, 116843.  https://doi.org/10.1016/j.watres.2021.116843.
  • Huang, K., & Zhang, H. (2020). Highly efficient bromide removal from shale gas produced water by un-activated peroxymonosulfate for disinfection byproduct formation control in impacted water supplies. Environ. Sci. Technol., 54 (8), 5186-5196. https://doi.org/10.1021/acs.est.9b06825.
  • Zhang, K., Zhong, S., & Zhang, H. (2020). Predicting aqueous adsorption of organic compounds on biochars, carbon nanotubes, granular activated carbons, and resins by machine learning. Environ. Sci. Technol., 54(11), 7008-7018. doi.org/10.1021/acs.est.0c02526.
  • Zhang, K., & Zhang, H. (2020). Coupling a Feedforward Network (FN) Model to Real Adsorbed Solution Theory (RAST) to Improve Prediction of Bisolute Adsorption on Resins. Environ. Sci. Technol., 54 (23), 15385-15394..
  • Zhang, K., Zhong, S., & Zhang, H. (2020). Predicting Aqueous Adsorption of Organic Compounds onto Biochars, Carbon Nanotubes, Granular Activated Carbons, and Resins with Machine Learning. Environ. Sci. Technol., 54 (11), 7008-7018.
  • Huang, K., & Zhang, H. (2019). Direct Electron Transfer-Based Peroxymonosulfate Activation by Iron-Doped Manganese Oxide (δ-MnO2) and the Development of Galvanic Advanced Oxidation Processes (GAOPs). Environ. Sci. Technol., 53 (21), 12610-12620.
  • Huang, J., & Zhang, H. (2019). Manganese Oxides as Catalysts for Water and Wastewater Treatment: A Critical Review. Environ. Intern., 133 (), 105141.
  • Zhong, S., & Zhang, H. (2019). New insight into the reactivity of Mn(III) in bisulfite/permanganate for organic compounds oxidation: The catalytic role of Bisulfite and Oxygen. Wat. Res., 148 (), 198-207.
  • Zhong, S., & Zhang, H. (2019). New insight into the reactivity of Mn(III) in bisulfite/permanganate for organic compounds oxidation: The catalytic role of Bisulfite and Oxygen. Water Res., 148 (), 198-207.
  • Zhong, S., & Zhang, H. (2018). New insight into the reactivity of Mn(III) in bisulfite/permanganate for organic compounds oxidation: The catalytic role of Bisulfite and Oxygen. Wat. Res., 148 (), 198-207.
  • Huang, J., Zhong, S., Dai, Y., Liu, C., & Zhang, H. (2018). Effect of Phase Structure of MnO2 on the Oxidation Reactivity toward Contaminant Degradation. Environ. Sci. Technol., 52 (19), 11309–11318.
  • Huang, J., Zhong, S., Dai, Y., Liu, C., & Zhang, H. (2018). Effect of Phase Structure of MnO2 on the Oxidation Reactivity toward Bisphenol A Degradation. Environ. Sci. Technol., 52 (19), 11309-11318.
  • Jadbabaei, N., Ye, T., Shuai, D., & Zhang, H. (2017). Development of Palladium-Resin Composites for Catalytic Hydrodechlorination of 4-Chlorophenol – Impact of Support Structures. Applied Catalysis B: Environmental, 205 (), 576–586.
  • Zhang, H., & Wang, S. (2017). Modeling of Bi-Solute Adsorption by Polymeric Resin based on Adsorbed Solution Theories (ASTs). Environ. Sci. Technol. , 51 (10), 5552–5562.
  • Jadbabaei, N., Slobodjian, R., Shuai, D., & Zhang, H. (2017). Catalytic reduction of 4-nitrophenol by palladium-resin composites. App. Cat. A, 543 (), 209-217.
  • Jadbabaei, N., Ye, T., Shuai, D., & Zhang, H. (2017). Development of palladium-resin composites for catalytic hydrodechlorination of 4-chlorophenol. App. Cat. B, 205 (), 576-586.
  • Zhang, H., & Wang, S. (2017). Modeling Bisolute Adsorption of Aromatic Compounds Based on Adsorbed Solution Theories. Environmental science & technology, 51 (10), 5552-5562.
  • Chen, Y., Dong, S., & Zhang, H. (2016). Experimental and Computational Evidence for the Reduction Mechanisms of Aromatic N-oxides by Aqueous FeII –Tiron Complex. Environ. Sci. Technol., 50 (1), 249–258.
  • Taujale, S., Baratta, L., & Zhang, H. (2016). Interactions in ternary mixtures of MnO2, Al2O3, and natural organic matter (NOM) and the impact on MnO2 oxidative reactivity. Environ. Sci. Technol., 50 (5), 2345–2353.
  • Zhang, H., Taujale, S., Huang, J., & Lee, G. (2015). Effects of NOM on oxidative reactivity of manganese dioxide in binary oxide mixtures with goethite or hematite. Langmuir, 31 (), 2790-2799.
  • Jadbabaei, N., & Zhang, H. (2014). Sorption mechanism and predictive models for removal of cationic organic contaminants by cation exchange resins. Environ. Sci. Technol., 48 (), 14572-14581.
  • Zhang, H., Shields, A., Jadbabaei, N., Nelson, M., Pan, B., & Suri, R. (2014). Understanding and Modeling Removal of Anionic Organic Contaminants (AOCs) by Anion Exchange Resins. Environ. Sci. Technol., 48 (), 7494-7502.
  • Pan, B., & Zhang, H. (2014). Reconstruction of adsorption potential in Polanyi-based models and application to various adsorbents. Environ. Sci. Technol., 48 (), 6772−6779.
  • Chen, Y., & Zhang, H. (2013). Complexation facilitated reduction of aromatic N-oxides by aqueous FeII-tiron Complex: Reaction kinetics and mechanisms. Environ. Sci. Technol., 47 (), 11023−11031.
  • Zhang, H., & Weber, E. (2013). Identifying indicators of reactivity for chemical reductants in natural sediments. Environ. Sci. Technol., 47 (), 6959–6968.
  • Pan, B., & Zhang, H. (2013). Interaction mechanisms and predictive model for the sorption of aromatic compounds onto nonionic resins. J. Phys. Chem. C, 117 (), 17707−17715.
  • Pan, B., & Zhang, H. (2012). A modified Polanyi-based model for mechanistic understanding of adsorption of phenolic compounds onto polymeric adsorbents. Environ. Sci. Technol., 46 (12), 6806-6814.
  • Taujale, S., & Zhang, H. (2012). Impact of interactions between metal oxides to oxidative reactivity of manganese dioxide. Environ. Sci. Technol., 46 (), 2764−2771.
  • Zhang, H., & Weber, E. (2009). Elucidating the role of electron shuttles in reductive transformations in anaerobic sediments. Environ. Sci. Technol., 43 (4), 1042-1048.
  • Zhang, H., Chen, W., & Huang, C. (2008). Kinetic modeling of oxidation of antibacterial agents by manganese oxide. Environ. Sci. Technol., 42 (), 5548-5554.
  • Zhang, H., & Lemley, A. (2006). Reaction mechanism and kinetic modeling of DEET degradation by flow-through anodic Fenton treatment (FAFT). Environ. Sci. Technol., 40 (14), 4488-4494.
  • Zhang, H., & Huang, C. (2005). Oxidative transformation of fluoroquinolone antibacterial agents and structurally related amines by manganese oxide. Environmental science & technology, 39 (12), 4474-4483.
  • Zhang, H., & Huang, C. (2005). Reactivity and transformation of antibacterial N-oxides in the presence of manganese oxide. Environ. Sci. Technol., 39 (), 593-601.
  • Zhang, H., & Huang, C. (2003). Oxidative transformation of triclosan and chlorophene by manganese oxides. Environ. Sci. Technol., 37 (), 2421-2430.

Education

PhD
Environmental Engineering
Georgia Institute of Technology
2004
Master of Science
Environmental Science
Nanjing University
1997
Bachelor of Science
Environmental Chemistry
Nanjing University
1994