Electrochemical hydrogen compressor: Recent progress and challenges
Hydrogen has higher specific energy than conventional fuels but compared per unit volume
under normal conditions, its energy density is lower. This difference is compensated with …
under normal conditions, its energy density is lower. This difference is compensated with …
Towards ultralow platinum loading proton exchange membrane fuel cells
With the upcoming worldwide commercialization of proton exchange membrane fuel cells
(PEMFCs), the challenges regarding their cost, performance and durability urgently need to …
(PEMFCs), the challenges regarding their cost, performance and durability urgently need to …
Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation
Polymeric membranes have been widely used for liquid and gas separation in various
industrial applications over the past few decades because of their exceptional versatility and …
industrial applications over the past few decades because of their exceptional versatility and …
Empowering capacitive devices: harnessing transfer learning for enhanced data-driven optimization
Develo** data-driven models has found successful applications in engineering tasks,
such as material design, process modeling, and process monitoring. In capacitive devices …
such as material design, process modeling, and process monitoring. In capacitive devices …
Transfer Learning Facilitates the Prediction of Polymer–Surface Adhesion Strength
Machine learning (ML) accelerates the exploration of material properties and their links to
the structure of the underlying molecules. In previous work [Shi et al. ACS Applied Materials …
the structure of the underlying molecules. In previous work [Shi et al. ACS Applied Materials …
Determining ion activity coefficients in ion-exchange membranes with machine learning and molecular dynamics simulations
The activity coefficients of ions in polymeric ion-exchange membranes (IEMs) dictate the
equilibrium partitioning coefficient of the ions between the membrane and the liquid. It also …
equilibrium partitioning coefficient of the ions between the membrane and the liquid. It also …
Synergizing data-driven and knowledge-based hybrid models for ionic separations
A hybrid modeling framework has been developed for electrodialysis (ED) and resin-wafer
electrodeionization (EDI) in brackish water desalination, integrating compositional modeling …
electrodeionization (EDI) in brackish water desalination, integrating compositional modeling …
A tutorial review of machine learning-based model predictive control methods
This tutorial review provides a comprehensive overview of machine learning (ML)-based
model predictive control (MPC) methods, covering both theoretical and practical aspects. It …
model predictive control (MPC) methods, covering both theoretical and practical aspects. It …
Plant-wide Modeling, Design Consideration, and Practical Hierarchical Control Strategy Considering Key Variable Integral Characteristics for an Industrial Alkaline …
The alkaline water electrolysis (AEL) system stands out in clean hydrogen production and is
commercially available owing to its high technology readiness level. Despite the current …
commercially available owing to its high technology readiness level. Despite the current …
Towards Reliable Prediction of Performance for Polymer Electrolyte Membrane Fuel Cells via Machine Learning-Integrated Hybrid Numerical Simulations
For mitigating global warming, polymer electrolyte membrane fuel cells have become
promising, clean, and sustainable alternatives to existing energy sources. To increase the …
promising, clean, and sustainable alternatives to existing energy sources. To increase the …