Local-order metric for condensed-phase environments

Martelli, Fausto; Ko, Hsin-Yu; Oğuz, Erdal C.; Car, Roberto

doi:10.1103/physrevb.97.064105

Cited by 50 publications

(51 citation statements)

References 47 publications

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“…Specifically, by using the LOM developed in Ref. [34], we searched for locally ordered crystalline domains composed by the first and/or second shell of neigh-bors in the amorphous ices formed during the Ih-to-HDA and the LDA-to-HDA pressure-induced transformations. Our results confirm that LDA and HDA are indeed amorphous, i.e., they lack of polydispersed ice-like structures.…”

Section: Discussionmentioning

confidence: 99%

Searching for crystal-ice domains in amorphous ices

Martelli

Giovambattista

Torquato

et al. 2018

Phys. Rev. Materials

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We employ classical molecular dynamics simulations to investigate the molecular-level structure of water during the isothermal compression of hexagonal ice (Ih) and low-density amorphous (LDA) ice at low temperatures. In both cases, the system transforms to high-density amorphous ice (HDA) via a first-order-like phase transition. We employ a sensitive local order metric (LOM) [Martelli et. al., Phys. Rev. B, 97, 064105 (2018)], that can discriminate among different crystalline and non crystalline ice structures and is based on the positions of the oxygen atoms in the first and/or second hydration shell. Our results confirm that LDA and HDA are indeed amorphous, i.e., they lack of polydispersed ice domains. Interestingly, HDA contains a small number of domains that are reminiscent of the unit cell of ice IV, although the hydrogen-bond network (HBN) of these domains differ from the HBN of ice IV. The presence of ice IV-like domains provides some support to the hypothesis that HDA could be the result of a detour on the HBN rearrangement along the Ih-to-ice IV pressure induced transformation. Both nonequilibrium LDA-to-HDA and Ih-to-HDA transformations are two-steps processes where a small distortion of the HBN first occurs at low pressures and then, a sudden, extensive re-arrangement of hydrogen bonds at the corresponding transformation pressure follows. Interestingly, the Ih-to-HDA and LDA-to-HDA transformations occur when LDA and Ih have similar local order, as quantified by the site-averaged LOMs. Since Ih has a perfect tetrahedral HBN, while LDA does not, it follows that higher pressures are needed to transform Ih into HDA than that for the conversion of LDA to HDA. In correspondence with both first-order-like phase transitions, the samples are composed of a large HDA cluster that percolates within the Ih/LDA samples. Our results shed light on the debated structural properties of amorphous ices and indicate that the kinetics of the Ih-to-HDA and LDA-to-HDA transformations require an in depth inspection of the underlying HBN. Such investigation is currently ongoing.

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Section: Discussionmentioning

confidence: 99%

Searching for crystal-ice domains in amorphous ices

Martelli

Giovambattista

Torquato

et al. 2018

Phys. Rev. Materials

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“…More and more simulations nucleate and grow crystals, even highly complex ones, directly from the melt [2][3][4][5][6][7][8] . Bond orientational order parameters 9 and related approaches [10][11][12][13][14][15][16] reliably detect the presence of global and local order and identify a few simple crystals, including face-centered cubic, hexagonal close-packed, and body-centered cubic [17][18][19][20][21] . A more general structure characterization requires local fingerprints 22,23 that are fed into machine learning algorithm [24][25][26][27][28][29] .…”

Section: Introductionmentioning

confidence: 99%

Point Group Analysis in Particle Simulation Data

Engel¹

2021

Preprint

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A routine crystallography technique, crystal structure analysis, is rarely performed in computational condensed matter research. The lack of methods to identify and characterize crystal structures reliably in particle simulation data complicates the comparison of simulation outcomes to experiment and the discovery of new materials. Algorithms are sought that not only classify local structure but also analyze the type and degree of crystallographic order. Here, we develop an algorithm that analyzes point group symmetry directly from particle coordinates. The algorithm operates on functions defined on the surface of the sphere, such as the bond orientational order diagram. Other use cases are the orientation of crystals and adoption as generalized order parameters for detecting the appearance of order as well as following its development.

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“…However, the CVs suitable to this task are often designed for specific classes of structural transformations (Lechner and Dellago 2008;Martoňák et al 2003;Giberti et al 2015;Haji-Akbari and Debenedetti 2015): no general CV scheme was proved successful for a wide class of different problems, in particular those involving disordered systems. Recently, on the other hand, several distance metrics have been developed with the aim of distinguishing and classifying structures of molecular or extended systems, based on atomic environment and/or interatomic networks (Valle and Oganov 2010;Gallet and Pietrucci 2013;Pietrucci and Martoňák 2015;Pietrucci and Saitta 2015;Zhu et al 2016;De et al 2016;Piaggi and Parrinello 2017;Martelli et al 2018;Barthel et al 2018). In this context, an important question is whether a given metric is able, besides classifying locally stable structures, to also track dynamical transitions in a continuous and accurate way.…”

Section: The Difficult Case Of Water Poly(a)morphism: a Simple Metricmentioning

confidence: 99%

Novel Enhanced Sampling Strategies for Transitions Between Ordered and Disordered Structures

Pietrucci¹

2018

Handbook of Materials Modeling

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Local-order metric for condensed-phase environments

Cited by 50 publications

References 47 publications

Searching for crystal-ice domains in amorphous ices

Searching for crystal-ice domains in amorphous ices

Point Group Analysis in Particle Simulation Data

Novel Enhanced Sampling Strategies for Transitions Between Ordered and Disordered Structures

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