1 citations · 2 across the 3 of their papers we have counts for
4 papers
Fitting micro-kinetic models to transient kinetics of temporal analysis of product reactors using kinetics-informed neural networks
Dingqi Nai, Gabriel S. Gusmão, Zachary A. Kilwein +2
The temporal analysis of products (TAP) technique produces extensive transient kinetic data sets, but it is challenging to translate the large quantity of raw data into physically…
Model-based design of temporal analysis of products (TAP) reactors: A simulated case study in oxidative propane dehydrogenation
Adam C. Yonge, Gabriel S. Gusmão, Rebecca Fushimi +1
Temporal analysis of products (TAP) reactors enable experiments that probe numerous kinetic processes within a single set of experimental data through variations in pulse intensity…
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems
Gabriel S. Gusmão, Andrew J. Medford
Physics-informed neural networks (PINNs) have proven a suitable mathematical scaffold for solving inverse ordinary (ODE) and partial differential equations (PDE). Typical inverse P…
Kinetics-Informed Neural Networks
Gabriel S. Gusmão, Adhika P. Retnanto, Shashwati C. da Cunha +1
Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the r…