Literature DB >> 29300479

Exploring Chemical Space with Alchemical Derivatives: BN-Simultaneous Substitution Patterns in C60.

Robert Balawender1, Michał Lesiuk2, Frank De Proft3, Paul Geerlings3.   

Abstract

With the idea of using alchemical derivatives to explore in an efficient, computer- and cost-effective way Chemical Space was launched several years ago. In the context of Conceptual DFT response functions, these energies vs nuclear charge derivatives permit the estimatation of the energy of transmutants of a given starting or reference molecule showing different nuclear compositions. After an explorative study on small and planar molecules ( Balawender et al. J. Chem. Theory Comput. 2013 , 9 , 5327 ) by the present authors of this paper, the present study fully exploits the computational advantages of the alchemical derivatives in larger three-dimensional systems. Starting from a single reference calculation on C60, the complete BN substitution pattern, from single substituted C58BN via the belt (C20(BN)20 and the ball C12(BN)24 structures to the fully substituted (BN)30, is explored. Successive and simultaneous substitution strategies are followed and compared, indicating that both techniques yield identical results up to 13 substitutions but that for higher substitutions the simultaneous approach needs to be taken. Due to the cost-efficiency of the algorithm this path can indeed be followed as opposed to earlier work in the literature where for each step a full SCF calculation was at stake leading to prohibitively large computational demands for adopting the simultaneous approach. Previously formulated rules governing the substitution pattern by Kar and co-workers are scrutinized in this context and reformulated giving chemical insight in the gradual substitution process and the relative energies of the isomers. In its present form the method offers an interesting venue to study BN substitution patterns in higher fullerenes and graphene and in general paves the way for more efficient exploration of the Chemical Space.

Entities:  

Year:  2018        PMID: 29300479     DOI: 10.1021/acs.jctc.7b01114

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


  3 in total

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Review 2.  Ab Initio Machine Learning in Chemical Compound Space.

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3.  Simplifying inverse materials design problems for fixed lattices with alchemical chirality.

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  3 in total

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