research
∙
04/12/2023
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems
Physics-informed neural networks (PINNs) have proven a suitable mathemat...
share
research
∙
09/27/2021
A Priori Calibration of Transient Kinetics Data via Machine Learning
The temporal analysis of products reactor provides a vast amount of tran...
research
∙
02/04/2021
A Universal Framework for Featurization of Atomistic Systems
Molecular dynamics simulations are an invaluable tool in numerous scient...
research
∙
11/30/2020
Kinetics-Informed Neural Networks
Chemical kinetics consists of the phenomenological framework for the dis...
research
∙
11/17/2020
Data Driven Reaction Mechanism Estimation via Transient Kinetics and Machine Learning
Understanding the set of elementary steps and kinetics in each reaction ...
research
∙
08/26/2020
TAPsolver: A Python package for the simulation and analysis of TAP reactor experiments
An open-source, Python-based Temporal Analysis of Products (TAP) reactor...
research
∙
08/20/2019
