Iron nitride formation and decomposition during ammonia decomposition over a wustite-based bulk iron catalyst
Hydrogen production using renewable sources shows great promise in lowering the
dependence on fossil fuels in our current energy system, but challenges persist in its storage …
dependence on fossil fuels in our current energy system, but challenges persist in its storage …
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 …
Machine Learning Potentials for Heterogeneous Catalysis
The production of many bulk chemicals relies on heterogeneous catalysis. The rational
design or improvement of the required catalysts critically depends on insights into the …
design or improvement of the required catalysts critically depends on insights into the …
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 …
ML-Accelerated Automatic Process Exploration Reveals Facile O-Induced Pd Step-Edge Restructuring on Catalytic Time Scales
We combine automatic process exploration with an iteratively trained machine-learning
interatomic potential to systematically identify elementary processes occurring during the …
interatomic potential to systematically identify elementary processes occurring during the …
Everything everywhere all at once, a probability-based enhanced sampling approach to rare events
The problem of studying rare events is central to many areas of computer simulations. In a
recent paper [Kang, P., et al., Nat. Comput. Sci. 4, 451-460, 2024], we have shown that a …
recent paper [Kang, P., et al., Nat. Comput. Sci. 4, 451-460, 2024], we have shown that a …
Understanding the Mechanism of Nanocluster Formation from Machine-Learned Potential-based Simulations
V Tiwari, T Karmakar - 2025 - chemrxiv.org
Understanding the mechanism for the formation of metal nanoclusters is an open challenge
in the nanoscience field. Computational modeling can provide molecular details of …
in the nanoscience field. Computational modeling can provide molecular details of …
[PDF][PDF] Exploring the Importance of Dynamics in Materials from the Atomic to the Supramolecular Scale Using Advanced Computational Methods
M Cioni - 2024 - tesidottorato.depositolegale.it
In the field of materials science, metals constitute a fundamental class of material that
possess unique properties and that have been crucial in technological and industrial …
possess unique properties and that have been crucial in technological and industrial …