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 …
Machine learning in process systems engineering: Challenges and opportunities
This “white paper” is a concise perspective of the potential of machine learning in the
process systems engineering (PSE) domain, based on a session during FIPSE 5, held in …
process systems engineering (PSE) domain, based on a session during FIPSE 5, held in …
A review of recent advances and applications of machine learning in tribology
In tribology, a considerable number of computational and experimental approaches to
understand the interfacial characteristics of material surfaces in motion and tribological …
understand the interfacial characteristics of material surfaces in motion and tribological …
Toward Understanding and Controlling Organic Reactions on Metal Oxide Catalysts
Metal oxides have structurally complex surfaces on which a variety of adsorption site types
can occur, including cation sites, anion sites, oxygen vacancy sites, and Brønsted acid sites …
can occur, including cation sites, anion sites, oxygen vacancy sites, and Brønsted acid sites …
Bayesian Statistics to Elucidate the Kinetics of γ-Valerolactone from n-Butyl Levulinate Hydrogenation over Ru/C
S Capecci, Y Wang, J Delgado… - Industrial & …, 2021 - ACS Publications
The synthesis of γ-valerolactone (GVL), a platform molecule that can be produced from
lignocellulosic biomass, was performed in this work by hydrogenation of an alkyl levulinate …
lignocellulosic biomass, was performed in this work by hydrogenation of an alkyl levulinate …
Microkinetic modeling in electrocatalysis: Applications, limitations, and recommendations for reliable mechanistic insights
The critical challenge for fundamental research in heterogeneous catalysis and
electrocatalysis is to 2 discover atomistic-scale phenomena (eg elementary step …
electrocatalysis is to 2 discover atomistic-scale phenomena (eg elementary step …
Microkinetic Modeling of the Transient CO2 Methanation with DFT‐Based Uncertainties in a Berty Reactor
The transient operation of methanation reactors can become desirable when coupled with
fluctuating renewable energies in Power‐to‐Gas scenarios, which requires suitable kinetic …
fluctuating renewable energies in Power‐to‐Gas scenarios, which requires suitable kinetic …
Uncertainty Quantification of Linear Scaling, Machine Learning, and Density Functional Theory Derived Thermodynamics for the Catalytic Partial Oxidation of Methane …
Accurate and complete microkinetic models (MKMs) are powerful for anticipating the
behavior of complex chemical systems at different operating conditions. In heterogeneous …
behavior of complex chemical systems at different operating conditions. In heterogeneous …
How many data points and how large an R-squared value is essential for Arrhenius plots?
Arrhenius plots estimate the apparent activation energy (E a) of catalytic reactions. The R-
squared value (r 2) often accompanies the Arrhenius plot to support its validity. However, no …
squared value (r 2) often accompanies the Arrhenius plot to support its validity. However, no …
Sequential infinite-dimensional Bayesian optimal experimental design with derivative-informed latent attention neural operator
We develop a new computational framework to solve sequential Bayesian optimal
experimental design (SBOED) problems constrained by large-scale partial differential …
experimental design (SBOED) problems constrained by large-scale partial differential …