Literature DB >> 26799516

Libraries of Extremely Localized Molecular Orbitals. 1. Model Molecules Approximation and Molecular Orbitals Transferability.

Benjamin Meyer1,2, Benoît Guillot3,4, Manuel F Ruiz-Lopez1,2, Alessandro Genoni1,2.   

Abstract

Despite more and more remarkable computational ab initio results are nowadays continuously obtained for large macromolecular systems, the development of new linear-scaling techniques is still an open and stimulating field of research in theoretical chemistry. In this family of methods, an important role is occupied by those strategies based on the observation that molecules are generally constituted by recurrent functional units with well-defined intrinsic features. In this context, we propose to exploit the notion of extremely localized molecular orbitals (ELMOs) that, due to their strict localization on small molecular fragments (e.g., atoms, bonds, or functional groups), are in principle transferable from one molecule to another. Accordingly, the construction of orbital libraries to almost instantaneously build up approximate wave functions and electron densities of very large systems becomes conceivable. In this work, the ELMOs transferability is further investigated in detail and, furthermore, suitable rules to construct model molecules for the computation of ELMOs to be stored in future databanks are also defined. The obtained results confirm the reliable transferability of the ELMOs and show that electron densities obtained from the transfer of extremely localized molecular orbitals are very close to the corresponding Hartree-Fock ones. These observations prompt us to construct new ELMOs databases that could represent an alternative/complement to the already popular pseudoatoms databanks both for determining electron densities and for refining crystallographic structures of very large molecules.

Year:  2016        PMID: 26799516     DOI: 10.1021/acs.jctc.5b01007

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  8 in total

1.  DiSCaMB: a software library for aspherical atom model X-ray scattering factor calculations with CPUs and GPUs.

Authors:  Michał L Chodkiewicz; Szymon Migacz; Witold Rudnicki; Anna Makal; Jarosław A Kalinowski; Nigel W Moriarty; Ralf W Grosse-Kunstleve; Pavel V Afonine; Paul D Adams; Paulina Maria Dominiak
Journal:  J Appl Crystallogr       Date:  2018-02-01       Impact factor: 3.304

2.  lamaGOET: an interface for quantum crystallography.

Authors:  Lorraine A Malaspina; Alessandro Genoni; Simon Grabowsky
Journal:  J Appl Crystallogr       Date:  2021-04-16       Impact factor: 3.304

Review 3.  Quantum crystallography.

Authors:  Simon Grabowsky; Alessandro Genoni; Hans-Beat Bürgi
Journal:  Chem Sci       Date:  2017-03-27       Impact factor: 9.825

4.  Transferable Machine-Learning Model of the Electron Density.

Authors:  Andrea Grisafi; Alberto Fabrizio; Benjamin Meyer; David M Wilkins; Clemence Corminboeuf; Michele Ceriotti
Journal:  ACS Cent Sci       Date:  2018-12-26       Impact factor: 14.553

5.  Multipolar Atom Types from Theory and Statistical Clustering (MATTS) Data Bank: Restructurization and Extension of UBDB.

Authors:  Kunal Kumar Jha; Barbara Gruza; Aleksandra Sypko; Prashant Kumar; Michał Leszek Chodkiewicz; Paulina Maria Dominiak
Journal:  J Chem Inf Model       Date:  2022-08-09       Impact factor: 6.162

6.  Refinement of organic crystal structures with multipolar electron scattering factors.

Authors:  Barbara Gruza; Michał Leszek Chodkiewicz; Joanna Krzeszczakowska; Paulina Maria Dominiak
Journal:  Acta Crystallogr A Found Adv       Date:  2020-01-01       Impact factor: 2.290

7.  The advanced treatment of hydrogen bonding in quantum crystallography.

Authors:  Lorraine A Malaspina; Alessandro Genoni; Dylan Jayatilaka; Michael J Turner; Kunihisa Sugimoto; Eiji Nishibori; Simon Grabowsky
Journal:  J Appl Crystallogr       Date:  2021-04-16       Impact factor: 3.304

8.  Electron density learning of non-covalent systems.

Authors:  Alberto Fabrizio; Andrea Grisafi; Benjamin Meyer; Michele Ceriotti; Clemence Corminboeuf
Journal:  Chem Sci       Date:  2019-09-09       Impact factor: 9.825

  8 in total

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