Alexander Mitsos

Latest

• Data-driven Product-Process Optimization of N-isopropylacrylamide Microgel Flow-Synthesis
• Molecular Design of Fuels for Maximum Spark-Ignition Engine Efficiency by Combining Predictive Thermodynamics and Machine Learning
• Graph machine learning for design of high-octane fuels
• Geometry optimization of a continuous millireactor via CFD and Bayesian optimization
• Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids
• HybridML: Open source platform for hybrid modeling
• Physical pooling functions in graph neural networks for molecular property prediction
• Machine learning in chemical engineering: A perspective
• Insight to gene expression from promoter libraries with the machine learning workflow Exp2Ipynb
• Designing production-optimal alternative fuels for conventional, flexible-fuel, and ultra-high efficiency engines
• Deterministic global optimization with Gaussian processes embedded
• Obey validity limits of data-driven models through topological data analysis and one-class classification
• Globally optimal working fluid mixture composition for geothermal power cycles
• The potential of hybrid mechanistic/data‐driven approaches for reduced dynamic modeling: application to distillation columns
• Deterministic global superstructure-based optimization of an organic Rankine cycle
• Hybrid mechanistic data-driven modeling for the deterministic global optimization of a transcritical organic Rankine cycle
• Graph neural networks for prediction of fuel ignition quality
• Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning
• Nonlinear scheduling with time‐variable electricity prices using sensitivity‐based truncations of wavelet transforms
• Deterministic global nonlinear model predictive control with neural networks embedded
• Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation
• Simultaneous rational design of ion separation membranes and processes
• Wavelet-based grid-adaptation for nonlinear scheduling subject to time-variable electricity prices
• Impact of accurate working fluid properties on the globally optimal design of an organic Rankine cycle
• Deterministic global process optimization: Flash calculations via artificial neural networks
• Deterministic global optimization with artificial neural networks embedded
• Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks
• Model-based bidding strategies on the primary balancing market for energy-intense processes
• Rational design of ion separation membranes
• Techno-economic optimization of a green-field post-combustion CO2 capture process using superstructure and rate-based models