Journal Articles

Ma, Y, Yuan, X, Yewale, A, Benyahia, B (2026) Recent advances in the digital transformation of crystallization process development and operation: Synergy between model- and AI-driven strategies, Particuology, 110(2026), pp.223-253, ISSN: 1674-2001. DOI: 10.1016/j.partic.2026.01.014.

Gazis, TA, Teixeira, R, Volpin, G, Yewale, A, Ince, MC, Ford, MJ, Harmsen, J, Uboldi, M, Melocchi, A, Sponchioni, M, Aramini, A, Luisi, R, Benyahia, B, Vilé, G (2025) Towards greener-by-design fine chemicals. Part 2: technological frontiers, Chemical Society Reviews, 55(2), pp.675-713, ISSN: 0306-0012. DOI: 10.1039/d5cs00930h.

Yewale, A, Yang, Y, Nazemifard, N, Papageorgiou, CD, Rielly, CD, Benyahia, B (2025) Deep Reinforcement Learning-Based Self-Optimization of Flow Chemistry, ACS Engineering Au, ISSN: 2694-2488. DOI: 10.1021/acsengineeringau.5c00004.

Conferences

Yewale, A and Benyahia, B (2026) Identification and self-optimization of robust nominal operating ranges using proximal policy optimization. In The 36th European Symposium on Computer Aided Process Engineering; Systems and Control Transactions: Proceedings of the 36th European Symposium on Computer Aided Process Engineering ESCAPE 36, Sheffield, United Kingdom, pp.2587-2593, ISBN: 9781777940355. DOI: 10.69997/sct.189137.

Yewale, A, Yang, Y, Nazemifard, N, Papageorgiou, CD, Rielly, C, Benyahia, B (2024) Multi-objective reinforcement learning for self-optimization of flow chemistry [Abstract]. In Manenti, F and Reklaitis, GVR (ed) 34th European Symposium on Computer Aided Process Engineering (ESCAPE34) and PSE 24; 34th European Symposium on Computer Aided Process Engineering /15th International Symposium on Process Systems Engineering, Florence, Italy, pp.3031-3036, ISBN: 9780443288241. DOI: 10.1016/B978-0-443-28824-1.50506-8.

Yewale, A, Rielly, C, Benyahia, B (2023) Reinforcement learning strategy for the optimization of flow chemistry [Extended abstract]. In 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology (ECCE&ECAB 2023), Berlin, Germany.

Datasets

Yewale, A, Yang, Y, Nazemifard, N, D. Papageorgiou, C, Rielly, C, Benyahia, B (2025) Supplementary information files for article "Deep reinforcement learning-based self-optimization of flow chemistry", DOI: 10.17028/rd.lboro.31452229.