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How dynamics changes ammonia cracking on iron surfaces
Being rich in hydrogen and easy to transport, ammonia is a promising hydrogen carrier.
However, a microscopic characterization of the ammonia cracking reaction is still lacking …
However, a microscopic characterization of the ammonia cracking reaction is still lacking …
Constructing accurate and efficient general-purpose atomistic machine learning model with transferable accuracy for quantum chemistry
Y Chen, W Yan, Z Wang, J Wu, X Xu - Journal of Chemical Theory …, 2024 - ACS Publications
Density functional theory (DFT) has been a cornerstone in computational science, providing
powerful insights into structure–property relationships for molecules and materials through …
powerful insights into structure–property relationships for molecules and materials through …
Analytical ab initio hessian from a deep learning potential for transition state optimization
Identifying transition states—saddle points on the potential energy surface connecting
reactant and product minima—is central to predicting kinetic barriers and understanding …
reactant and product minima—is central to predicting kinetic barriers and understanding …
How does structural disorder impact heterogeneous catalysts? the case of ammonia decomposition on non-stoichiometric lithium imide
Among the many catalysts suggested for ammonia decomposition, Li2NH has been shown
to be quite promising. In the recent past, we have performed extensive ab initio-quality …
to be quite promising. In the recent past, we have performed extensive ab initio-quality …
Data efficient machine learning potentials for modeling catalytic reactivity via active learning and enhanced sampling
Simulating catalytic reactivity under operative conditions poses a significant challenge due
to the dynamic nature of the catalysts and the high computational cost of electronic structure …
to the dynamic nature of the catalysts and the high computational cost of electronic structure …
Modeling Dynamic Catalysis at ab Initio Accuracy: The Need for Free-Energy Calculation
Heterogeneous catalysis plays an increasingly important role in the modern chemical
industry. The active site, as proposed by Taylor, 1 is one of the most fundamental concepts …
industry. The active site, as proposed by Taylor, 1 is one of the most fundamental concepts …
Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation
In the field of computational chemistry, predicting bond dissociation energies (BDEs)
presents well-known challenges, particularly due to the multireference character of reactive …
presents well-known challenges, particularly due to the multireference character of reactive …
Following the dynamics of industrial catalysts under operando conditions
V Van Speybroeck - Proceedings of the National Academy of Sciences, 2024 - pnas.org
Catalytic reactions taking place in industrial processes are often performed under extreme
conditions of temperatures and pressures. A typical example is the Haber–Bosch process to …
conditions of temperatures and pressures. A typical example is the Haber–Bosch process to …
Deep Learning of ab initio Hessians for Transition State Optimization
Identifying transition states--saddle points on the potential energy surface connecting
reactant and product minima--is central to predicting kinetic barriers and understanding …
reactant and product minima--is central to predicting kinetic barriers and understanding …