The fruitful interplay of high-resolution spectroscopy and quantum chemistry has a long history, especially in the field of small, semi-rigid molecules. However, in recent years, the targets of spectroscopic studies are shifting toward flexible molecules, characterized by a large number of closely spaced energy minima, all contributing to the overall spectrum. Here, artificial intelligence comes into play since it is at the basis of powerful unsupervised techniques for the exploration of soft degrees of freedom. Integration of such algorithms with a two-stage QM/QM′ (Quantum Mechanical) exploration/refinement strategy driven by a user-friendly graphical interface is the topic of the present paper. We will address in particular: (i) the performances of different semi-empirical methods for the exploration step and (ii) the comparison between stochastic and meta-heuristic algorithms in achieving a cheap yet complete exploration of the conformational space for medium sized chromophores. As test cases, we choose three amino acids of increasing complexity, whose full conformer enumeration has been reached only very recently. Next, we show that systems in condensed phases can be treated at the same level and with the same efficiency when employing a polarizable continuum description of the solvent. Finally, the challenging issue represented by the vibrational circular dichroism spectra of some rhodium complexes with flexible ligands has been addressed, showing that our fully unsupervised approach leads to remarkable agreement with the experiment.
Skip Nav Destination
Article navigation
28 September 2020
Research Article|
September 24 2020
Unsupervised search of low-lying conformers with spectroscopic accuracy: A two-step algorithm rooted into the island model evolutionary algorithm
Special Collection:
Machine Learning Meets Chemical Physics
Giordano Mancini
;
Giordano Mancini
a)
1
Scuola Normale Superiore
, Piazza dei Cavalieri 7, 56125 Pisa, Italy
a)Author to whom correspondence should be addressed: giordano.mancini@sns.it
Search for other works by this author on:
Marco Fusè
;
Marco Fusè
1
Scuola Normale Superiore
, Piazza dei Cavalieri 7, 56125 Pisa, Italy
Search for other works by this author on:
Federico Lazzari
;
Federico Lazzari
1
Scuola Normale Superiore
, Piazza dei Cavalieri 7, 56125 Pisa, Italy
Search for other works by this author on:
Balasubramanian Chandramouli
;
Balasubramanian Chandramouli
2
Super Computing Applications and Innovation, CINECA
, Via Magnanelli, 6/3, Casalecchio di Reno, BO, Italy
Search for other works by this author on:
Vincenzo Barone
Vincenzo Barone
1
Scuola Normale Superiore
, Piazza dei Cavalieri 7, 56125 Pisa, Italy
Search for other works by this author on:
a)Author to whom correspondence should be addressed: giordano.mancini@sns.it
Note: This paper is part of the JCP Special Topic on Machine Learning Meets Chemical Physics.
J. Chem. Phys. 153, 124110 (2020)
Article history
Received:
June 16 2020
Accepted:
September 02 2020
Citation
Giordano Mancini, Marco Fusè, Federico Lazzari, Balasubramanian Chandramouli, Vincenzo Barone; Unsupervised search of low-lying conformers with spectroscopic accuracy: A two-step algorithm rooted into the island model evolutionary algorithm. J. Chem. Phys. 28 September 2020; 153 (12): 124110. https://doi.org/10.1063/5.0018314
Download citation file:
Sign in
Don't already have an account? Register
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Sign in via your Institution
Sign in via your InstitutionPay-Per-View Access
$40.00