Advancement of capacitive deionization propelled by machine learning approach

H Wang, Y Li, Y Liu, X Xu, T Lu, L Pan - Separation and Purification …, 2024 - Elsevier
The gradual deterioration of ecosystems and the exponential growth of the population have
led to severe freshwater scarcity. Fetching available freshwater from seawater is expected to …

Exploring the potential of machine learning to understand the occurrence and health risks of haloacetic acids in a drinking water distribution system

Y Yu, MM Hossain, R Sikder, Z Qi, L Huo… - Science of The Total …, 2024 - Elsevier
Determining the occurrence of disinfection byproducts (DBPs) in drinking water distribution
system (DWDS) remains challenging. Predicting DBPs using readily available water quality …

Physics-informed transfer learning for process control applications

S Arce Munoz, J Pershing… - Industrial & Engineering …, 2024 - ACS Publications
Advancements in deep learning tools originally designed for natural language processing
are also applied to applications in the field of process control. Transformers, in particular …

Synergizing data-driven and knowledge-based hybrid models for ionic separations

T Olayiwola, LA Briceno-Mena, CG Arges… - ACS ES&T …, 2024 - ACS Publications
A hybrid modeling framework has been developed for electrodialysis (ED) and resin-wafer
electrodeionization (EDI) in brackish water desalination, integrating compositional modeling …