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A Vision for the Future of Multiscale Modeling.
Capone, Matteo; Romanelli, Marco; Castaldo, Davide; Parolin, Giovanni; Bello, Alessandro; Gil, Gabriel; Vanzan, Mirko.
Afiliación
  • Capone M; Department of Physical and Chemical Sciences, University of L'Aquila, L'Aquila 67010, Italy.
  • Romanelli M; Department of Chemical Sciences, University of Padova, Padova 35131, Italy.
  • Castaldo D; Department of Chemical Sciences, University of Padova, Padova 35131, Italy.
  • Parolin G; Department of Chemical Sciences, University of Padova, Padova 35131, Italy.
  • Bello A; Department of Chemical Sciences, University of Padova, Padova 35131, Italy.
  • Gil G; Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, Modena 41125, Italy.
  • Vanzan M; Department of Chemical Sciences, University of Padova, Padova 35131, Italy.
ACS Phys Chem Au ; 4(3): 202-225, 2024 May 22.
Article en En | MEDLINE | ID: mdl-38800726
ABSTRACT
The rise of modern computer science enabled physical chemistry to make enormous progresses in understanding and harnessing natural and artificial phenomena. Nevertheless, despite the advances achieved over past decades, computational resources are still insufficient to thoroughly simulate extended systems from first principles. Indeed, countless biological, catalytic and photophysical processes require ab initio treatments to be properly described, but the breadth of length and time scales involved makes it practically unfeasible. A way to address these issues is to couple theories and algorithms working at different scales by dividing the system into domains treated at different levels of approximation, ranging from quantum mechanics to classical molecular dynamics, even including continuum electrodynamics. This approach is known as multiscale modeling and its use over the past 60 years has led to remarkable results. Considering the rapid advances in theory, algorithm design, and computing power, we believe multiscale modeling will massively grow into a dominant research methodology in the forthcoming years. Hereby we describe the main approaches developed within its realm, highlighting their achievements and current drawbacks, eventually proposing a plausible direction for future developments considering also the emergence of new computational techniques such as machine learning and quantum computing. We then discuss how advanced multiscale modeling methods could be exploited to address critical scientific challenges, focusing on the simulation of complex light-harvesting processes, such as natural photosynthesis. While doing so, we suggest a cutting-edge computational paradigm consisting in performing simultaneous multiscale calculations on a system allowing the various domains, treated with appropriate accuracy, to move and extend while they properly interact with each other. Although this vision is very ambitious, we believe the quick development of computer science will lead to both massive improvements and widespread use of these techniques, resulting in enormous progresses in physical chemistry and, eventually, in our society.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Phys Chem Au Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Phys Chem Au Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Estados Unidos