Publications

Full list of publications can be found on Google Scholar.

After joining UoM

[19] J Zhang, P Yaseneva, A Lapkin^*. Developing Sustainable Chemistry with AI. Accounts of Chemical Research, 2026, 59 (20), 3426–3436.

[18] X Cao, J Zhang, S Soritz, X Chen, A Lapkin^*. Prior-Discrepancy-Aware Bayesian Optimization via Adaptive Uncertainty Inflation. Computers & Chemical Engineering, 109942.

[17] A Alsholi, S Tiwari, J Zhang, M Peeters^*. From empirical imprinting to programmable synthetic receptors: a perspective on data science and machine learning for molecularly imprinted polymers. Polymer Chemistry, 2026, 17(35), 3746–3756.

[16] S Zhang¹, J Zhang¹, A Lapkin^*. A knowledge graph framework for digital twins of chemical processes Nature Chemical Engineering. Nature Chemical Engineering, 2026, 3, 286–297.

[15] M Qu, Z Ding, D Zhang, S Foroughi, H Chen, Z Yu, J Zhang, L Xiao, MJ Blunt, X Fan^*, Q Lin^*. A Machine Learning-Driven Pore-Scale Network Model Coupling Reaction Kinetics and Interparticle Transport for Catalytic Process Design. Advanced Science, 2026, 13 (8), e13649.

[14] X Liang, Y Xie, J Zhang, W Huang, B Pan, XY Tai, J Xuan, A Lapkin, H Wang^*. Autonomous in silico optimization framework for high-performance micromixers. Chemical Engineering Journal, 2026, 529, 172957.

[13] J Zhang, S Zhang, A Lapkin. AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions. arXiv, 2025, arXiv:2511.20976

Before joining UoM

[12] Y Shen¹, J Zhang¹, X Liang, K Wang^*. From Optimization to Mechanism: Bayesian Optimization-Guided Exploration of p-Xylene Electro-oxidation. ACS Sustainable Chemistry & Engineering, 2025, 13 (39), 16601–16610.

[11] JF Laub, J Zhang^*, M Heyer, A Lapkin^*. Automated Generation of Mechanistic Models for Chemical Process Digital Twins using Reinforcement Learning-Part II: Compartmentalization and Learning-Based Recalibration. Computers & Chemical Engineering, 2025, 204, 109384.

[10] M Heyer, J Zhang^*, N Sugisawa, JF Laub, A Lapkin^*. Automated Generation of Mechanistic Models for Chemical Process Digital Twins using Reinforcement Learning-Part I: Conceptual Framework and Equation Generation. Computers & Chemical Engineering, 2025, 202, 109281.

[9] X Liang, J Zhang, K Gao, H Wang, K Wang^*, G Luo. Real-time probing of fast chemical reactions at the oil/water interface during microdroplet generation. Journal of Colloid and Interface Science. 2025, 3:137786.

[8] J Zhang, D Semochkina, N Sugisawa, DC Woods, A Lapkin^*. Multi-objective reaction optimization under uncertainties using expected quantile improvement. Computers & Chemical Engineering, 2025, 194, 108983.

[7] J Zhang, N Sugisawa, K Felton, S Fuse, A Lapkin^*. Multi-objective Bayesian optimisation using q-noisy expected hypervolume improvement (qNEHVI) for the Schotten–Baumann reaction. Reaction Chemistry & Engineering, 2024, 9 (3), 706-712.

[6] X Liang, J Zhang, M Li, K Wang^*, G Luo. Dynamic interfacial tension and adsorption kinetics of nonionic surfactants during microfluidic droplet formation process. Chemical Engineering Journal, 2022, 445, 136658.

[5] J Zhang, W Li, K Mumford, W Fei, G Stevens, Y Wang^*. Mass transfer study and combined model for a Karr column. Chemical Engineering Science, 2022, 254, 117581.

[4] J Zhang, W Li, K Mumford, W Fei, G Stevens, Y Wang^*. Drop sizes and population balance model for a Karr column. AIChE Journal 2022, 68 (1), e17413.

[3] J Zhang, J Berry, K Mumford, D Harvie, W Fei, G Stevens, Y Wang^*. Single drop breakage in a reciprocating plate column. *Chemical Engineering Journal 2021, 415, 129049.

[2] J Zhang, Y Wang^*, G Stevens, W Fei. A state-of-the-art review on single drop study in liquid–liquid extraction: Experiments and simulations. Chinese Journal of Chemical Engineering, 2019, 27 (12), 2857-2875.

[1] J Zhang, Y Wang^*, G Stevens, W Fei. An experimental study on single drop rising in a low interfacial tension liquid–liquid system. Chemical Engineering Research and Design 2019, 148, 349-360