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Structure characterization and classification is frequently based on local environment information of all or selected atomic sites in the crystal structure.
Amorphous grain boundary complexions act as toughening features within a microstructure because they can absorb dislocations more efficiently than traditional grain boundaries. This toughening effect should be a strong function of the local internal structure of the complexion, which has recently been shown to be determined by grain boundary crystallography. To test this hypothesis, molecular dynamics are used here to simulate dislocation absorption and damage nucleation for complexions with different distributions of structural short-range order. Here, the complexion with a more disordered structure away from the dislocation absorption site is actually found to better resist crack nucleation, as damage tolerance requires delocalized deformation and the operation of shear-transformation zones through the complexion thickness. The more damage tolerant complexion accommodates plastic strain efficiently within the entire complexion, providing the key mechanistic insight that local patterning and asymmetry of structural short-range order controls the toughening effect of amorphous complexions.
Local ordering of atoms within a crystalline structure is increasingly recognized as essential to understanding the properties of a variety of interesting materials. This is shown by the success of pair distribution function (PDF) analysis of scattering data from powder samples to investigate departures from perfectly crystalline order (Billinge & Kanatzidis, 2004; Egami & Billinge, 2012). Diffuse scattering from single crystals can also be a powerful probe of local order, potentially providing key information that would be difficult to obtain from PDF methods; however, difficulties in both measurement and interpretation of data have too often restricted their use by a larger community. In this issue of IUCrJ, Rothet al.(2020) demonstrate how simple concepts can be applied to better understand single-crystal diffuse scattering from half-Heusler systems.
Over fifty years ago, David Turnbull showed that the temperature of many metallic liquids could be decreased far below their equilibrium melting temperature before crystallization occurred. To explain those surprising results, Charles Frank hypothesized that the local structures of undercooled metallic liquids are different from those of crystal phases, containing a significant degree of icosahedral order that is incompatible with extended periodicity. Such structural differences must create a barrier to the formation crystal phases, explaining the observed undercooling behavior. If true, the nucleation from the liquid of phases with extended icosahedral order should be easier. Icosahedral order is often favored in small clusters, as observed recently in liquid-like clusters of pure Pb on the (111) surface of Si(3), for example. However, it has never been shown that an increasing preference for icosahedral phase formation can be directly linked with the development of icosahedral order in the undercooled liquid. Owing to the combination of very recent advances in levitation techniques and the availability of synchrotron X-ray and high flux neutron facilities.
Over fifty years ago, David Turnbull showed that the temperature of many metallic liquids could be decreased far below their equilibrium melting temperature before crystallization occurred. To explain those surprising results, Charles Frank hypothesized that the local structures of undercooled metallic liquids are different from those of crystal phases, containing a significant degree of icosahedral order that is incompatible with extended periodicity. Such structural differences must create a barrier to the formation crystal phases, explaining the observed undercooling behavior. If true, the nucleation from the liquid of phases with extended icosahedral order should be easier. Icosahedral order is often favored in small clusters, as observed recently in liquid-like clusters of pure Pb on the (111) surface of Si, for example. However, it has never been shown that an increasing preference for icosahedral phase formation can be directly linked with the development of icosahedral order in the undercooled liquid. Owing to the combination of very recent advances in levitation techniques and the availability of synchrotron x-ray and high flux neutron facilities, this is shown here.
Over fifty years ago, David Turnbull showed that the temperature of many metallic liquids could be decreased far below their equilibrium melting temperature before crystallization occurred. To explain those surprising results, Charles Frank hypothesized that the local structures of undercooled metallic liquids are different from those of crystal phases, containing a significant degree of icosahedral order that is incompatible with extended periodicity. Such structural differences must create a barrier to the formation crystal phases, explaining the observed undercooling behavior. If true, the nucleation from the liquid of phases with extended icosahedral order should be easier. Icosahedral order is often favored in small clusters, as observed recently in liquid-like clusters of pure Pb on the (111) surface of Si[3], for example. However, it has never been shown that an increasing preference for icosahedral phase formation can be directly linked with the development of icosahedral order in the undercooled liquid. Owing to the combination of very recent advances in levitation techniques and the availability of synchrotron x-ray and high flux neutron facilities, this is shown here.
The Ruddlesden–Popper (RP) layered perovskite structure is of great interest due to its inherent tunability, and the emergence and growth of the compositionally complex oxide (CCO) concept endows the RP family with further possibilities. Here, a comprehensive assessment of thermodynamic stabilization, local order/disorder, and lattice distortion was performed in the first two reported examples of lanthanum-deficient La n+1 B n O 3n+1 (n = 1, B = Mg, Co, Ni, Cu, Zn) obtained via various processing conditions. Chemical short-range order (CSRO) at the B-site and the controllable excess interstitial oxygen (δ) in RP-CCOs are uncovered by neutron pair distribution function analysis. Reverse Monte Carlo analysis of the data, Metropolis Monte Carlo simulations, and extended x-ray absorption fine structure analysis implies a modest degree of magnetic element segregation on the local scale. Further, ab initio molecular dynamics simulations results obtained from special quasirandom structure disagree with experimentally observed CSRO but confirm Jahn–Teller distortion of CuO 6 octahedra. These findings highlight potential opportunities to control local order/disorder and excess interstitial oxygen in layered RP-CCOs and demonstrate a high degree of freedom for tailoring application-specific properties. They also suggest a need for expansion of theoretical and data modeling approaches in order to meet the innate challenges of CCO and related high-entropy phases.
Here, we report an intrinsically disordered MOF in the MOF-74 family, Mg 2−x (as-dobpdc) (as-dobpdc 4− = 3′,4-dioxidobiphenyl-3,4′-dicarboxylate). Despite the absence of crystallinity, this material exhibits local ordering consistent with that of its crystalline isomers, maintains porosity, and exhibits a high density of open metal sites. Metal–organic frameworks (MOFs) are typically valued for their combination of crystallinity, porosity, and tunability. However, amorphous MOFs can retain local order while introducing advantages, such as broader distribution of active sites types, reduced thermal conductivity, and emergent modes of tunability via control over the type of disorder. Conventional amorphization strategies rely on external stimuli including pressure, temperature, stress, electrical discharge, or fast precipitation. Recently, amorphous MOFs have been accessed directly using low symmetry organic linkers.
Due to the limited capacity of GPU memory, the majority of prior work on graph applications on GPUs has been restricted to graphs of modest sizes that fit in memory. Recent hardware and software advances make it possible to address much larger host memory transparently as a part of a feature known as unified virtual memory. While accessing host memory over an interconnect is understandably slower, the problem space has not been sufficiently explored in the context of a challenging workload with low computational intensity and an irregular data access pattern such as graph traversal. We analyse the performance of breadth first search (BFS) for several large graphs in the context of unified memory and identify the key factors that contribute to slowdowns. Next, we propose a lightweight offline graph reordering algorithm, HALO (Harmonic Locality Ordering), that can be used as a pre-processing step for static graphs. HALO yields speedups of 1.5x-1.9x over baseline in subsequent traversals. Our method specifically aims to cover large directed real world graphs in addition to undirected graphs whereas prior methods only account for the latter. Additionally, we demonstrate ties between the locality ordering problem and graph compression and show that prior methods from graph compression such as recursive graph bisection can be suitably adapted to this problem.
Continuous phase transitions can be classified into ones characterized by local-order parameters and others that need additional topological constraints. The critical dynamics near the former transitions have been extensively studied, but the latter is less understood. We fill this gap in knowledge by studying the transition dynamics to a parity-breaking topological ground state called the chiral soliton lattice in quantum chromodynamics at finite temperature, baryon chemical potential, and an external magnetic field. We find a slowing down of the soliton’s translational motion as the critical magnetic field approaches, while the local relaxation rate to the solitonic state remains finite. The time required to converge to the stationary state strongly depends on the symmetry of the initial configuration, determining whether translational motion occurs during the dynamic process. Published by the American Physical Society 2024
This paper reports a dramatic increase in the grain boundary strengthening or Hall-Petch coefficient, K, by systematically investigating the effect of Al addition on tensile yield strength in CoFeNi and CoCrFeNi high entropy alloys (HEAs) or complex concentrated alloys (CCAs). Additionally, detailed atom probe tomography (APT) revealed a high number density of Ni-Al rich nano-clusters in the Al 0.3 CoFeNi and Al 0.3 CoCrFeNi HEAs/CCAs, which can be rationalized based on the strong chemical ordering tendency between these elements. Consequently, the huge increase in K value can be attributed to the additional stress required for overcoming coherency strain fields arising from these nano-clusters.
Polyelectrolyte complexation offers unique opportunities to compatibilize polymers with very different backbone chemistries and to control the morphology of the resulting blend via electrostatic manipulation. In this study, we demonstrate the ability to formulate homogeneous complexes of a conjugated polyelectrolyte with a polymeric ionic liquid, utilizing the electrostatic attraction among their oppositely charged side chains. Variation of electrostatic parameters, such as counterion concentration or polymer charge fraction, tunes the morphology of these polymer complexes from homogeneously disordered blend to weakly structured microemulsion where the local ordering arises from backbone-immiscibility-induced microphase segregation. Our experimental observations are in qualitative agreement with both field-theoretic simulation and random-phase approximation calculations. Simulated morphology snapshots suggest and experimental evidence also indicates that the microphase-segregated complex likely takes on a cocontinuous microemulsion structure. Our findings show that ionic interactions are an effective pathway to compatibilize polymers at macroscopic length scales while achieving controlled nanostructures in these ionic blends. Such systems have great potential for engineering the nanostructure of polymers to tailor applications such as nanofiltration, catalysis, and energy storage, where local ordering can enhance the physical properties of an otherwise macroscopically homogeneous structure.
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The development of manganese (Mn)-rich cathodes for Li-ion batteries promises to alleviate potential supply chain bottlenecks in battery manufacturing. Fundamental challenges in Mn-rich cathodes arise from phenomena such as structural changes due to cooperative Jahn-Teller (JT) distortions of in octahedral environments, Mn migration, and phase transformations to spinel-like order, all of which affect the electrochemical performance. These physically complex phenomena motivate an re-examination of the Li-Mn-O rock-salt space, with a focus on the thermodynamics of the prototypical, polymorphs. It is found that the generalized gradient approximation (GGA-PBEsol) and meta-GGA ( ) density functionals with empirically fitted on-site Hubbard corrections yield spurious stable phases for , such as predicting a phase with -like order ( ) to be the ground state instead of the orthorhombic (Pmmn) phase, which is the experimentally known ground state. Accounting for antiferromagnetic order in each structure is shown to have a substantial effect on the total energies and resulting phase stability. By using hybrid-GGA (HSE06) and GGA with self-consistent Hubbard parameters (on-site and inter-site ) calculated from linear response theory, the experimentally observed phase stability trends are recovered. The calculated on-site between Mn- states in the experimentally observed orthorhombic, layered, and spinel phases are significantly smaller than in and disordered layered structures, by within GGA. The smaller values of are shown to be correlated with a collinear ordering of JT distortions, in which all orbitals are oriented in the same direction. This cooperative JT effect can lead to greater electron delocalization from Mn along the states due to increased Mn-O covalency, which contributes to the greater electronic stability compared to the phases with noncollinear JT arrangements. The structures with collinear ordering of JT distortions also generate greater vibrational entropy, which helps stabilize these phases at high temperature. These phases are shown to be strongly insulating with large calculated band gaps , which are computed using HSE06 and .
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Rapid crystallization behavior of amorphous TexSe1−x thin films limits the use of these alloys as coatings and in optoelectronic devices. Understanding the short- and medium-range ordering of the amorphous structure and the fundamental physics governing the crystallization of the films is crucial. Although the lack of long range crystalline order restricts the characterization of the amorphous films, electron microscopy offers a way to extract information about the nanoscale ordering. In this paper, the local ordering of amorphous TexSe1−x thin films with x=0.22, 0.61, 0.70, 0.90, and 1 grown by thermal evaporation is investigated using radial distribution function (RDF) and fluctuation electron microscopy (FEM) analysis. RDF results show that the nearest-neighbor distances of selenium (Se) and tellurium (Te) in their crystalline structure are preserved, and their bond lengths increase with the addition of Te. Density functional theory (DFT) calculations predict structures with interatomic distances similar to those measured experimentally. Additionally, fluctuations in atomic coordination are analyzed. Medium range order (MRO) analysis obtained from FEM and DFT calculations suggests that there are at least two populations within the chain network structure, which are close to the Se–Se and Te–Te intrachain distances. For the binary alloy with x > 0.61, TexSe1−x, Te–Te like populations increase and Te fragments might form, suggesting that the glass forming ability decreases rapidly.
A new approach to texture classification based on local rank correlation is proposed here. Its performance is compared with Laws' method which uses local convolution with feature masks. In the experiments, texture samples are classified based on their distribution of local statistics, either rank correlations or convolutions. The new method achieves generally optimal classification rates. It appears to be more robust because local order statistics are unaffected by local sample differences due to monotonic shifts of texture gray values and are less sensitive to noise.