Predicting Solid Compounds Using Simulated Annealing

Schön, J. Christian; Jansen, Martin

doi:10.1002/9783527632831.ch4

Cited by 6 publications

(3 citation statements)

References 247 publications

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“…To round up this section, it should be noted that a variety of techniques have been used in the literature for related optimization problems; among those are Monte Carlo or molecular dynamics-based techniques such as simulated annealing, 81 , 82 basin-hopping, 83 − 85 minima-hopping, 86 , 87 and eventually evolutionary approaches such as genetic algorithms. 61 − 67 , 79 , 80 , 88 − 91 The decision on the method of choice relies on the specific problem: for instance, as Hofmann et al.…”

Section: Identifications Of Self-assembly Scenariosmentioning

confidence: 99%

Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions

Hartl

Sharma²,

Brügner³

et al. 2020

J. Chem. Theory Comput.

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We propose a computationally lean, two-stage approach that reliably predicts self-assembly behavior of complex charged molecules on metallic surfaces under electrochemical conditions. Stage one uses ab initio simulations to provide reference data for the energies (evaluated for archetypical configurations) to fit the parameters of a conceptually much simpler and computationally less expensive force field of the molecules: classical, spherical particles, representing the respective atomic entities; a flat and perfectly conducting wall represents the metallic surface. Stage two feeds the energies that emerge from this force field into highly efficient and reliable optimization techniques to identify via energy minimization the ordered ground-state configurations of the molecules. We demonstrate the power of our approach by successfully reproducing, on a semiquantitative level, the intricate supramolecular ordering observed experimentally for PQP + and ClO 4 – molecules at an Au(111)–electrolyte interface, including the formation of open-porous, self-host–guest, and stratified bilayer phases as a function of the electric field at the solid–liquid interface. We also discuss the role of the perchlorate ions in the self-assembly process, whose positions could not be identified in the related experimental investigations.

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Section: Identifications Of Self-assembly Scenariosmentioning

confidence: 99%

Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions

Hartl

Sharma²,

Brügner³

et al. 2020

J. Chem. Theory Comput.

View full text Add to dashboard Cite

show abstract

“…Exhaustively sampling the corresponding vast configuration space demands an unfeasible amount of computational resources. Still a variety of different techniques, ranging from Monte Carlo or molecular dynamics-based techniques such as simulated annealing, 8 , 9 Basin-Hopping, 10 − 12 or minima hopping 13 , 14 to evolutionary approaches such as genetic algorithms 15 − 19 have been successfully developed. Although most of these efforts were dedicated to gas-phase structures or bulk crystals, recently, structure search was extended to organic/inorganic interfaces.…”

mentioning

confidence: 99%

Structure Prediction for Surface-Induced Phases of Organic Monolayers: Overcoming the Combinatorial Bottleneck

et al. 2017

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Structure determination and prediction pose a major challenge to computational material science, demanding efficient global structure search techniques tailored to identify promising and relevant candidates. A major bottleneck is the fact that due to the many combinatorial possibilities, there are too many possible geometries to be sampled exhaustively. Here, an innovative computational approach to overcome this problem is presented that explores the potential energy landscape of commensurate organic/inorganic interfaces where the orientation and conformation of the molecules in the tightly packed layer is close to a favorable geometry adopted by isolated molecules on the surface. It is specifically designed to sample the energetically lowest lying structures, including the thermodynamic minimum, in order to survey the particularly rich and intricate polymorphism in such systems. The approach combines a systematic discretization of the configuration space, which leads to a huge reduction of the combinatorial possibilities with an efficient exploration of the potential energy surface inspired by the Basin-Hopping method. Interfacing the algorithm with first-principles calculations, the power and efficiency of this approach is demonstrated for the example of the organic molecule TCNE (tetracyanoethylene) on Au(111). For the pristine metal surface, the global minimum structure is found to be at variance with the geometry found by scanning tunneling microscopy. Rather, our results suggest the presence of surface adatoms or vacancies that are not imaged in the experiment.

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“…Indeed, the structure with optimal properties will frequently be metastable, and will be of interest only if it can be synthesized. It is my hope that this volume, reviewing most of the major methods of crystal structure prediction, all the way from topological approaches [4] to optimization methods [19,22,25,27,29,32] and methods to appraise synthesizability of a material [43], will be useful to a wide readership of physicists, chemists, materials scientists and earth scientists. The best approach for computing the absolute activation energies of solid-solid phase transitions is the transition path sampling method [42], reviewed in this volume by Leoni and Boulfelfel [43].…”

mentioning

confidence: 99%

Introduction: Crystal Structure Prediction, a Formidable Problem

2010

Modern Methods of Crystal Structure Prediction

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Predicting Solid Compounds Using Simulated Annealing

Cited by 6 publications

References 247 publications

Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions

Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions

Structure Prediction for Surface-Induced Phases of Organic Monolayers: Overcoming the Combinatorial Bottleneck

Introduction: Crystal Structure Prediction, a Formidable Problem

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