Skip to Main Content (Press Enter)

Logo UNIMORE
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Terza Missione
  • Attività
  • Competenze

UNI-FIND
Logo UNIMORE

|

UNI-FIND

unimore.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Terza Missione
  • Attività
  • Competenze
  1. Pubblicazioni

Assessing entropy for catalytic processes at complex reactive interfaces

Capitolo di libro
Data di Pubblicazione:
2022
Citazione:
Assessing entropy for catalytic processes at complex reactive interfaces / Kollias, L., Collinge, G., Zhang, D., Allec, S.I., Gurunathan, P.K., Piccini, G., Yuk, S.F., Nguyen, M.-T., Lee, M.-S., Glezakou, V.-A., Rousseau, R. (ANNUAL REPORTS IN COMPUTATIONAL CHEMISTRY). - In: Annual Reports in Computational ChemistryRadarweg 29, PO Box 211, AMSTERDAM, NETHERLANDS : Elsevier Ltd, 2022. - ISBN 9780323990929. - pp. 3-51 [10.1016/bs.arcc.2022.09.004]
Abstract:
When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid-liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.
Tipologia CRIS:
Capitolo/Saggio
Keywords:
Catalysis; Data science; Enhanced sampling; Entropy; Molecular simulations; Reaction pathways
Elenco autori:
Kollias, L.; Collinge, G.; Zhang, D.; Allec, S. I.; Gurunathan, P. K.; Piccini, G.; Yuk, S. F.; Nguyen, M. -T.; Lee, M. -S.; Glezakou, V. -A.; Rousseau, R.
Autori di Ateneo:
PICCINI GIOVANNIMARIA
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1330780
Titolo del libro:
Annual Reports in Computational Chemistry
Pubblicato in:
ANNUAL REPORTS IN COMPUTATIONAL CHEMISTRY
Series
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.6.0.0