Bond Orientational Order Research Articles

Shear rheology of confined double rings of dust particles in a dusty plasma

Abstract Shear rheology is a fundamental property of soft matter, which can be deformed. Although the shear rheology of fluids has been well studied at the macroscopic scale, understanding the microscopic processes of rheology at the single-particle level remains a challenging issue. Dusty plasma serves as an ideal platform for exploring microscopic dynamics of system at the individual particle level. Here, we study the shear rheology of confined double rings of strongly coupled dust particles in a dusty plasma. The outer ring is actively driven to rotate using laser illumination. Depending on the particle number, the inner ring may passively rotate following the outer ring at different angular speeds, resulting in shear rheology. The number of dust particles influences particle arrangement, which is characterized by the pair correlation function, bond-orientational order parameter, and triangle skewness. That further alters structural stability, significantly affecting the shear rheology.

Linear dependence of grain boundary energy on structural orderliness in FCC metals

Establishing the correlation between grain boundary (GB) structure and energy is crucial for advancing the fundamental understanding of polycrystalline materials, yet this correlation remains elusive. In this study, systematic atomic simulations are performed to comprehensively explore numerous GBs in different FCC metals and alloys. The findings unveil a universal linear relationship between the GB energy and GB structural orderliness parameter (GB excess centrosymmetry or excess bond orientational order parameters). Remarkably, the identified linear relationship proves universally applicable across different metal systems, GB types, and length scales, rooted in the linear correlation between atomic potential energy and atomic structural orderliness. Furthermore, the ratio between GB energy and orderliness parameter emerges as a potent indicator for gauging the extent of GB relaxation, thereby providing valuable insights to inform the design of nanocrystalline materials with enhanced GB stability.

Local Structural Features Elucidate Crystallization of Complex Structures.

Complex crystal structures are composed of multiple local environments, and how this type of order emerges spontaneously during crystal growth has yet to be fully understood. We study crystal growth across various structures and along different crystallization pathways, using self-assembly simulations of identical particles that interact via multiwell isotropic pair potentials. We apply an unsupervised machine learning method to features from bond-orientational order metrics to identify different local motifs present during a given structure's crystallization process. In this manner, we distinguish different crystallographic sites in highly complex structures. Tailoring this order parameter to structures of varying complexity and coordination number, we study the emergence of local order along a multistep crystal growth pathway─from a low-density fluid to a high-density, supercooled amorphous liquid droplet and to a bulk crystal. We find a consistent under-coordination of the liquid relative to the average coordination number in the bulk crystal. We use our order parameter to analyze the geometrically frustrated growth of a Frank-Kasper phase and discover how structural defects compete with the formation of crystallographic sites that are more high-coordinated than the liquid environments. The method presented here for classifying order on a particle-by-particle level has broad applicability to future studies of structural self-assembly and crystal growth, and they can aid in the design of building blocks and for targeting pathways of formation of soft-matter structures.

Study of phase transition and local order in equiatomic and nonequiatomic mixtures of HfNbTaTi under uniaxial loading from molecular dynamics simulations

We simulate an alloy of HfNbTaTi mixed in six different proportions and also of the equiatomic system under uniaxial tensile loading at 300 K. Molecular dynamics simulation trajectories are analyzed using radial distribution functions, OVITO, bond-orientational order parameters, and coordination numbers. Equiatomic and the two other alloys (Hf0.31Nb0.23Ta0.23Ti0.23 and Hf0.23Nb0.31Ta0.23Ti0.23) containing comparable fraction of elements deform similarly through the formation of an amorphous state. Two alloys rich in Nb (Hf0.17Nb0.50Ta0.16Ti0.17) and Ta (Hf0.17Nb0.16Ta0.50Ti0.17) deform similarly resulting in the formation of bcc atoms, which transform to fcc at higher loading. Finally, alloys rich in Hf (Hf0.50Nb0.16Ta0.17Ti0.17) and Ti (Hf0.17Nb0.16Ta0.17Ti0.50) deform resulting in high dislocation densities and hcp atoms. These two hcp-rich alloys also undergo strain hardening. In each mixture during loading, local orientational order of all the different elements changes similarly. Atoms prefer to pair with other atoms than to themselves during tensile loading.

Understanding melting of Ti crystals with spherical voids from molecular dynamics simulations

Titanium (Ti) is one of the most important metals used in several industrial applications, and the presence of spherical defect reduces its strength and stability. We simulate the melting of Ti crystals with a spherical void of radii 0.6, 0.8, 1.0, and 1.5 nm and also of the crystal without it. Ti is modeled using embedded atom method ,and all crystals are heated at 1 atm from 300 to 2200 K till it melts completely. All molecular dynamics trajectories are analyzed using radial distribution functions, bond-orientational order parameters, Voronoi tessellation, and velocity auto-correlation functions. The results show that 0.6, 0.8, 1.0, and 1.5 nm voids fill before the crystals melt and they fill immediately within few picoseconds; thereafter, atoms rearrange/order to crystal like arrangements, wherein overall crystallinity remains hcp for crystals with 0.6 and 0.8 nm void and changes to bcc for the crystals with 1.0 and 1.5 nm voids. For all crystals with and without void, melting takes place with the loss of both long- and short-range orders and not from liquid like nuclei as proposed by classical nucleation theory.

Quantum dipole interactions and transient hydrogen bond orientation order in cells, cellular membranes and myelin sheath: Implications for MRI signal relaxation, anisotropy, and T1 magnetic field dependence.

Despite significant impact on the study of human brain, MRI lacks a theory of signal formation that integrates quantum interactions involving proton dipoles (a primary MRI signal source) with brain intricate cellular environment. The purpose of the present study is developing such a theory. We introduce the Transient Hydrogen Bond (THB) model, where THB-mediated quantum dipole interactions between water and protons of hydrophilic heads of amphipathic biomolecules forming cells, cellular membranes and myelin sheath serve as a major source of MR signal relaxation. The THB theory predicts the existence of a hydrogen-bond-driven structural order of dipole-dipole connections within THBs as a primary factor for the anisotropy observed in MRI signal relaxation. We have also demonstrated that the conventional Lorentzian spectral density function decreases too fast at high frequencies to adequately capture the field dependence of brain MRI signal relaxation. To bridge this gap, we introduced a stretched spectral density function that surpasses the limitations of Lorentzian dispersion. In human brain, our findings reveal that at any time point only about 4% to 7% of water protons are engaged in quantum encounters within THBs. These ultra-short (2 to 3 ns), but frequent quantum spin exchanges lead to gradual recovery of magnetization toward thermodynamic equilibrium, that is, relaxation of MRI signal. By incorporating quantum proton interactions involved in brain imaging, the THB approach introduces new insights on the complex relationship between brain tissue cellular structure and MRI measurements, thus offering a promising new tool for better understanding of brain microstructure in health and disease.

Soft colloidal monolayers with reflection symmetry through confined drying.

Colloidal monolayers serve as fundamental building blocks in fabricating diverse functional materials, pivotal for surface modifications, chemical reactivity, and controlled assembly of nanoparticles. In this article, we report the formation of colloidal monolayers generated by drying an aqueous droplet containing soft colloids confined between two hydrophilic parallel plates. The analysis of the kinetics of evaporation in this confined mode showed that: (i) for a significant portion of the drying time, the drops adopt a catenoid configuration; (ii) in the penultimate stage of drying, the catenoid structure undergoes division into two daughter droplets; (iii) the three-phase contact line remains pinned at a specific location while it continuously slips at all other locations. The interplay between interface-assisted particle deposition onto the solid substrate and the time evolution of particle concentration within the droplet during evaporation results in unique microstructural features in the deposited patterns. Notably, these deposit patterns exhibit reflection symmetry. The microstructural features of the dried deposits are further quantified by calculating the particle number density, inter-particle separation, areal disorder parameter, and bond orientational order parameter. The variation of these parameters for deposits formed under different conditions, such as by altering the spacing between parallel plates and the concentration of microgel particles in the droplet, is discussed.

Structures and energies of twist grain boundaries in Mg[formula omitted]SiO4 forsterite

In this work, we investigate twist grain boundary (GB) energies and structures in Mg2SiO4 forsterite using atomistic simulations. We first present a new bond orientational order parameter allowing to highlight disordered regions in this low-symmetry crystal for which classical visualization tools are ineffective. Then we examine three GB planes, (010), (120) and (001), corresponding to the most favorable free surfaces of this crystal. We show that twist GB follow the same energy ordering as corresponding free surfaces. In addition, except for some misorientation angles and for the (120) GB plane, GB energies and structures are quite insensitive to microscopic translational degrees of freedom. The dislocation composition of low-angle twist GB can be related to γ-surfaces in the corresponding planes, and are in good agreement with first-principle calculations. It is also shown that the dislocation core structures in low angle twist GB can strongly differ from the ones of intracrystalline dislocations.

First-principles molecular dynamics study on the behaviors of Cs in a mixed system of liquid metal and LiCl-KCl molten salt.

The structure and dynamic properties of Cs in the mixed system of LiCl-KCl molten salt and a liquid metal (Bi and Pb) electrode are investigated through first-principles molecular dynamics simulation. It is found that the dynamic properties of different ions in molten salt could be significantly affected when the liquid metal electrode is coupled and this influence varies with the type of liquid metal applied. The microstructures of the mixed systems of molten salt and liquid metal electrode: MS-Cs-Bi, MS-CsCl-Bi, MS-Cs-Pb, and MS-CsCl-Pb, are also investigated by the bond angle distribution function, Voronoi tessellation analysis, five-fold symmetry parameter, and bond-orientational order parameter. The comparison study of the microstructures of the mixed systems when different liquid metal electrodes are applied provides information on the liquid metal electrode selection when conducting electrolysis. The present study represents the first demonstration of the study of a mixed system of salt and liquid electrode for practical applications and would be greatly beneficial to the development of pyroprocessing of spent nuclear fuel.

Atomistically informed hierarchical modeling for revisiting the constituent structures from heredity and nano-micro mechanics of sheath-core carbon fiber.

To better understand the heterogeneous anisotropic nanocomposite features and provide reliable underlying constitutive parameters of carbon fiber for continuum-level simulations, hierarchical modeling approaches combining quantum chemistry, molecular dynamics, numerical and analytical micromechanics are employed for studying the structure-performance relationships of the precursor-inherited sheath-core carbon fiber layers. A robust debonding force field is derived from energy matching protocols, including bond dissociation enthalpy calculations and rigid-constraint potential energy surface scan. Logistic long range bond stretching curves with exponential parameters and shifted force vdW curves are designed to diminish energy perturbations. The pseudo-crystalline microstructure is proposed and validated using virtual wide angle X-ray diffraction patterns and bond-orientational order parameters. The distribution or alignment features of the nanocomposite microstructures are collected from quantum chemical topology analysis and normal vector extractions. Non-equilibrium tensile loading simulation predicts the decomposed strain energy contributions, principal-axis modulus, strength limit, localized stress, and fracture morphologies of the model. Finally, an atomistically-informed stiffness prediction model combining numerical homogenization and analytical self-consistent Eshelby-Mori-Tanaka-type effective mean field micromechanics theory is proposed, giving a successful estimation of the overall stiffness matrix of the sheath-core carbon fiber system. The hierarchical models in combination with the carbonization reaction template will help in providing efficient and feasible schemes for the synergistic process-performance control of distinct types of carbon fiber.

Symmetry-specific characterization of bond orientation order in DNA-assembled nanoparticle lattices.

Bond-orientational order in DNA-assembled nanoparticles lattices is explored with the help of recently introduced Symmetry-specific Bond Order Parameters (SymBOPs). This approach provides a more sensitive analysis of local order than traditional scalar BOPs, facilitating the identification of coherent domains at the single bond level. The present study expands the method initially developed for assemblies of anisotropic particles to the isotropic ones or cases where particle orientation information is unavailable. The SymBOP analysis was applied to experiments on DNA-frame-based assembly of nanoparticle lattices. It proved highly sensitive in identifying coherent crystalline domains with different orientations, as well as detecting topological defects, such as dislocations. Furthermore, the analysis distinguishes individual sublattices within a single crystalline domain, such as pair of interpenetrating FCC lattices within a cubic diamond. The results underscore the versatility and robustness of SymBOPs in characterizing ordering phenomena, making them valuable tools for investigating structural properties in various systems.

Persistent Homology and Bond Orientational Order in Ir–Cu Solid-Solution Alloy Nanoparticles: Implications for Electrocatalysts

Persistent Homology and Bond Orientational Order in Ir–Cu Solid-Solution Alloy Nanoparticles: Implications for Electrocatalysts

The influence of engineering strain rates on the atomic structure, crack propagation and cavitation formation in Al based metallic glass

To enhance the toughness of metallic glasses (MGs), considerable scientific efforts have been made to investigate the physical mechanism of fracture behavior of MGs in past few years. However, many unresolved puzzles remain about the fracture mechanisms of MGs at present. In this paper, Molecular Dynamics (MD) simulations have been used to investigate the tensile fracture behavior of Al based MGs under nine different Engineering strain rates. Our results show that the higher the Engineering strain rate is, the longer the period of plastic deformation, the shorter the crack length. We have observed that Al amorphous with notch gradually crystallizes during tensile fracture, however, there are differences in the degree of crystallization and atomic arrangement as well as micro-structure in different regions with different Engineering strain rates. In the process of tensile fracture of Al based MGs, the crack propagation mainly along the hexagonal-close-packed (HCP) grain boundaries between face-centered-cubic (FCC) crystal blocks. As the Engineering strain increases, numerous HCP atoms located at grain boundaries gradually migrate into the interior of FCC crystal blocks, the velocity of crack propagation will also increase and finally induce the brittle fracture of Al based MGs. Meanwhile, we effectively demonstrated the existence of HCP and FCC atoms in Al based MGs during tensile deformation by analyzing the bond-orientational order parameters ql. The analysis of thermodynamics (entropy) showed that there is a positive correlation between the Engineering strain rate and the strain of maximum entropy when the Engineering strain rate exceeds 0.002 ps−1. The formation of cavitation ahead of crack could be attributed to the migrate of atoms from the higher entropy cavity region to the lower entropy crystallization region. This study enriches the traditional tensile deformation theories and provides a new understanding for the physical origins of cavitation in the crack tip of MGs.

Impact of hierarchical water dipole orderings on the dynamics of aqueous salt solutions

Ions exhibit highly ion-specific complex behaviours when solvated in water, which remains a mystery despite the fundamental importance of ion solvation in nature, science, and technology. Here we explain these ion-specific properties by the ion-induced hierarchical dipolar, translational, and bond-orientational orderings of ion hydration shell under the competition between ion-water electrostatic interactions and inter-water hydrogen bonding. We first characterise this competition by a new length λHB(q), explaining the ion-specific effects on solution dynamics. Then, by continuously tuning ion size and charge, we find that the bond-orientational order of the ion hydration shell highly develops for specific ion size and charge combinations. This ordering drastically stabilises the hydration shell; its degree changes the water residence time around ions by 11 orders of magnitude for main-group ions. These findings are fundamental to ionic processes in aqueous solutions, providing a physical principle for electrolyte design and application.

Effect of graphene on solid–liquid coexistence in Cu nanodroplets

The microstructure determines the macro properties, so the chemical and physical properties of nanoparticles can be tuned by changing their structures. A molecular dynamics simulation for the rapid solidification of Cu nanodroplets on the graphene sheet is conducted to investigate the effect of substrate on nanoparticles. The phase transition, structure evolution, and crystallinity are quantified by the potential energy, the largest standard cluster analysis, and Bond-orientation order parameters. It is found that the solidification is inhomogeneous and stepwise crystallization. Interestingly, originating from the graphene wettability, different solid–liquid coexistence states are obtained that may have the potential to modify the chemical and physical reactions on nanoparticles. The temperature of this solid–liquid coexistence state depends strongly on the structural evolution of crystallization and thus can be regulated by the wetting properties of the graphene substrate. These results significantly extend the fundamental understanding of heterogeneous nucleation in nanodroplets, providing important insights for designing and fabricating composite materials with multifunctional properties.

Analysis of Structural Change across the Liquid-Liquid Transition and the Widom Line in Supercooled Stillinger-Weber Silicon.

We consider the changes in the structure of supercooled Stillinger-Weber silicon at pressures at which the studied range of temperatures traverses the liquid-liquid transition or the "Widom line" (at which the isothermal compressibility or the specific heat exhibits a maximum). In addition to the conventional characterizations in terms of the pair-correlation function and bond orientational order, we analyze the statistics of rings in the bond network as well as the statistics of clusters of low density liquid (LDL)- and high density liquid (HDL)-like atoms. We investigate the nature of the change in these structural characterizations when the liquid-liquid transition line or the Widom line is crossed. We find that the isobaric temperature variation of these structural features reveals clear indications of maximal structural heterogeneity or frustration upon crossing the liquid-liquid transition or the Widom line, as in the case of water, but with some differences in detail, which we discuss.

Entropic stabilization and descriptors of structural transformation in high entropy alloys

With first-principles theoretical analysis of the local structure using Bond-Orientational Order parameters and Voronoi partitioning, we establish (a) HCP→BCC structural transformation in high-entropy alloys (HEAs) Nbx(HfZrTi)y at 16% Nb-concentration, and (b) that the internal lattice distortions (ILDs) peak at the transition. We demonstrate that the relative stability of HCP and BCC structures is driven by energetics, while the overall stability is achieved with contribution from the vibrational entropy that exceeds the configurational entropy of mixing. We show that along with atomic size mismatch, low average number (<5) of valence electrons and disparity in the crystal structures of constituent elements are responsible for larger ILDs in Nbx(HfZrTi)y than in HEAs like NbaMobWcTad.

Disordering two-dimensional magnet-particle configurations using bidispersity.

In various types of many-particle systems, bidispersity is frequently used to avoid spontaneous ordering in particle configurations. In this study, the relation between bidispersity and disorder degree of particle configurations is investigated. By using magnetic dipole-dipole interaction, magnet particles are dispersed in a two-dimensional cell without any physical contact between them. In this magnetic system, bidispersity is introduced by mixing large and small magnets. Then, the particle system is compressed to produce a uniform particle configuration. The compressed particle configuration is analyzed by using Voronoi tessellation for evaluating the disorder degree, which strongly depends on bidispersity. Specifically, the standard deviation and skewness of the Voronoi cell area distribution are measured. As a result, we find that the peak of standard deviation is observed when the numbers of large and small particles are almost identical. Although the skewness shows a non-monotonic behavior, a zero skewness state (symmetric distribution) can be achieved when the numbers of large and small particles are identical. In this ideally random (disordered) state, the ratio between pentagonal, hexagonal, and heptagonal Voronoi cells becomes roughly identical, while hexagons are dominant under monodisperse (ordered) conditions. The relation between Voronoi cell analysis and the global bond orientational order parameter is also discussed.

Phase behavior of active and passive dumbbells.

We report phase separation in a mixture of "hot" and "cold" three-dimensional dumbbells which interact by Lennard-Jones potential. We also have studied the effect of asymmetry of dumbbells and the variation of ratio of "hot" and "cold" dumbbells on their phase separation. The ratio of the temperature difference between hot and cold dumbbells to the temperature of cold dumbbells is a measure of the activity χ of the system. From constant density simulations of symmetric dumbbells, we observe that the "hot" and "cold" dumbbells phase separate at higher activity ratio (χ>5.80) compared to that of a mixture of hot and cold Lennard-Jones monomers (χ>3.44). We find that, in the phase-separated system, the hot dumbbells have high effective volume and hence high entropy which is calculated by two-phase thermodynamic method. The high kinetic pressure of hot dumbbells forces the cold dumbbells to form dense clusters such that at the interface the high kinetic pressure of hot dumbbells is balanced by the virial pressure of cold dumbbells. We find that phase separation pushes the cluster of cold dumbbells to have solidlike ordering. Bond orientation order parameters reveal that the cold dumbbells form solidlike ordering consisting of predominantly face-centered cubic and hexagonal-close packing packing, but the individual dumbbells have random orientations. The simulation of the nonequilibrium system of symmetric dumbbells at different ratios of number of hot dumbbells to cold dumbbells reveals that the critical activity of phase separation decreases with increase in fraction of hot dumbbells. The simulation of equal mixture of hot and cold asymmetric dumbbells revealed that the critical activity of phase separation was independent of the asymmetry of dumbbells. We also observed that the clusters of cold asymmetric dumbbells showed both crystalline and noncrystalline order depending on the asymmetry of dumbbells.

Deep learning techniques for the localization and classification of liquid crystal phase transitions

Deep Learning techniques such as supervised learning with convolutional neural networks and inception models were applied to phase transitions of liquid crystals to identify transition temperatures and the respective phases involved. In this context achiral as well as chiral systems were studied involving the isotropic liquid, the nematic phase of solely orientational order, fluid smectic phases with one-dimensional positional order and hexatic phases with local two-dimensional positional, so-called bond-orientational order. Discontinuous phase transition of 1st order as well as continuous 2nd order transitions were investigated. It is demonstrated that simpler transitions, namely Iso-N, Iso-N*, and N-SmA can accurately be identified for all unseen test movies studied. For more subtle transitions, such as SmA*-SmC*, SmC*-SmI*, and SmI*-SmF*, proof-of-principle evidence is provided, demonstrating the capability of deep learning techniques to identify even those transitions, despite some incorrectly characterized test movies. Overall, we demonstrate that with the provision of a substantial and varied dataset of textures there is no principal reason why one could not develop generalizable deep learning techniques to automate the identification of liquid crystal phase sequences of novel compounds.