Training Stiff Dynamic Process Models via Neural Differential Equations

Computer Aided Chemical Engineering 2022

William Bradley Gabriel S. Gusmão Andrew J. Medford Fani Boukouvala

A common step in developing generalizable, dynamic mechanistic models is to fit unmeasured parameters to measured data. Fitting differential equation-based models can be computationally expensive due to the presence of nonlinearity and stiffness. This work proposes a two-stage indirect approach…

Data-Driven Simultaneous Process Optimization and Adsorbent Selection for Vacuum Pressure Swing Adsorption

Chemical Engineering Research and Design 2022

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges…

Stages and Kinetics of Mechanochemical Depolymerization of Poly(ethylene terephthalate) with Sodium Hydroxide

ACS Sustainable Chem. Eng. 2022

Efficient chemical recycling of consumer plastics (i.e., depolymerization down to monomers) is a crucial step needed to achieve a circular material economy. In this work, depolymerization of poly(ethylene terephthalate) (PET) via mechanochemical hydrolysis with sodium hydroxide is studied, with complete…

Perspectives on the Integration between First-Principles and Data-Driven Modeling

Computers & Chemical Engineering 2022

Efficiently embedding and/or integrating mechanistic information with data-driven models is essential if it is desired to simultaneously take advantage of both engineering principles and data-science. The opportunity for hybridization occurs in many scenarios, such as the development of a faster…

Two-Stage Approach to Parameter Estimation of Differential Equations Using Neural ODEs

Industrial & Engineering Chemistry Research 2021

Modeling physiochemical relationships using dynamic data is a common task in fields throughout science and engineering. A common step in developing generalizable, mechanistic models is to fit unmeasured parameters to measured data. However, fitting differential equation-based models can be computation-intensive…