“School of Nano-Sciences”

Back to Papers Home
Back to Papers of School of Nano-Sciences

Paper   IPM / Nano-Sciences / 17893
School of Nano Science
  Title:   Aqueous solution chemistry in silico and the role of data-driven approaches
  Author(s): 
1.  Debarshi Banerjee
2.  Khatereh Azizi
3.  Colin Egan
4.  Edward Danquah Donkor
5.  Cesare Malosso
6.  Solana Di Pino
7.  Gonzalo DÃ?­az MirÃ?³n
8.  Martina Stella
9.  Giulia Sormani
10.  Germaine Neza Hozana
11.  Marta Monti
12.  Uriel N. Morzan
13.  Alex Rodriguez
14.  Giuseppe Cassone
15.  Asja Jelic
16.  Damian Scherlis
17.  Ali Hassanali
  Status:   Published
  Journal: Chem. Phys. Rev.
  No.:  021308
  Vol.:  5
  Year:  2024
  Supported by:  IPM
  Abstract:
The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights into physical chemistry and how this will influence computer simulations of aqueous systems in the future.

Download TeX format
back to top
scroll left or right