Bridging the complexity gap in computational heterogeneous catalysis with machine learning
Heterogeneous catalysis underpins a wide variety of industrial processes including energy
conversion, chemical manufacturing and environmental remediation. Significant advances …
conversion, chemical manufacturing and environmental remediation. Significant advances …
Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors
Artificial intelligence (AI), machine learning (ML), and data science are leading to a
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
Kinetics of chemical processes: From molecular to industrial scale
Combining spectroscopic and transient kinetic techniques provides access to the
identification and quantification of active sites and corresponding turnover frequencies of …
identification and quantification of active sites and corresponding turnover frequencies of …
Machine learning enabled customization of performance-oriented hydrogen storage materials for fuel cell systems
Hydrogen storage materials with different crystal configurations have been extensively
investigated for hydrogen promotion. To escape the dilemma of traditional trial-and-error …
investigated for hydrogen promotion. To escape the dilemma of traditional trial-and-error …
Improving the predictive power of microkinetic models via machine learning
S Rangarajan, H Tian - Current Opinion in Chemical Engineering, 2022 - Elsevier
Microkinetic modeling is commonly used in heterogeneous catalysis to study reaction
mechanisms and compute information such as the reaction rates, selectivity, degrees of rate …
mechanisms and compute information such as the reaction rates, selectivity, degrees of rate …
PolyODENet: Deriving mass-action rate equations from incomplete transient kinetics data
Kinetics of a reaction network that follows mass-action rate laws can be described with a
system of ordinary differential equations (ODEs) with polynomial right-hand side. However, it …
system of ordinary differential equations (ODEs) with polynomial right-hand side. However, it …
Machine learning based prediction of subcooled bubble condensation behavior, validation with experimental and numerical results
Measuring a full life cycle of condensing subcooled bubbles using either the experimental
and/or numerical approaches is a very challenging problem. In present study this problem is …
and/or numerical approaches is a very challenging problem. In present study this problem is …
Temporal analysis of product (TAP)
R Fushimi - Springer Handbook of Advanced Catalyst …, 2023 - Springer
Abstract The Temporal Analysis of Products (TAP) pulse response method for
characterization of catalyst kinetic properties and mechanistic features is presented …
characterization of catalyst kinetic properties and mechanistic features is presented …
Recent progress toward catalyst properties, performance, and prediction with data-driven methods
Data-driven approaches are currently renovating the field of heterogenous catalysis and
open the door to advance catalyst design. Their success depends heavily on the synergy …
open the door to advance catalyst design. Their success depends heavily on the synergy …
Is ChatGPT A reliable source for writing review articles in catalysis research? A case study on CO2 hydrogenation to higher alcohols
Q Zhong, X Tan, R Du, J Liu, L Liao, C Wang, R Sun… - 2023 - preprints.org
ChatGPT is an AI language model trained on vast amounts of text data, including scientific
papers, providing a comprehensive understanding of catalysis. However, its reliability in …
papers, providing a comprehensive understanding of catalysis. However, its reliability in …