Local Structure Analysis Research Articles

Computational approaches for structural analysis of wood specimens

Abstract The structure tensor (ST), also named a second-moment matrix, is a popular tool in image processing. Usually, its purpose is to evaluate orientation and to conduct local structural analysis. We present an efficient algorithm for computing eigenvalues and linking eigenvectors of the ST derived from a material structure. The performance and efficiency of our approach are demonstrated through several numerical simulations. The proposed approach is evaluated qualitatively and quantitatively using different two-dimensional/three-dimensional wood image types. This article reviews the properties of the first- and second-order STs, their properties, and their application to illustrate their usefulness in analyzing the wood data. Our results demonstrate that the suggested approach achieves a high-quality orientation trajectory from high-resolution micro-computed tomography ( μ {\rm{\mu }} CT)-imaging. These orientations lead to establishing a description of fiber orientation states in thermo-mechanical models for fiber-reinforced composite materials. We conclude with an overview of open research and problem directions.

Direct simulation and machine learning structure identification unravel soft martensitic transformation and twinning dynamics

Phase transition between ordered phases has garnered attention from the viewpoint of materials science as well as statistical physics. One interesting example is martensitic transformation and the resulting formation of twin structures, in which atoms or molecules that form one crystalline phase move in a concerted and diffusionless manner toward another crystalline phase. Recently martensitic transformation has been observed experimentally also in various soft materials. However, the complex internal structures involving many molecules have eluded direct investigation of the dynamical processes of martensitic transformation. Here, we carry out a direct simulation of mesoscale structural transition of a liquid crystalline blue phase (BP) of cubic symmetry, known as BP II. The dynamics is simulated by a Langevin-type equation for the orientational order parameter with thermal fluctuations. We demonstrate that machine-learning-aided analysis of local structures successfully unravels the transformation process from a perfect lattice of BP II to a twinned lattice of another BP (BP I). The nucleation of BP I is initiated by the breakup of junctions of line defects (disclinations), followed by the deformation of disclination network. We further show that twinned BP I is reversibly transformed to a perfect lattice of BP II by temperature variation. Order-parameter-based simulations with machine-learning-aided local structure identification provide valuable insights into not only the martensitic transformation of soft materials but also a wider class of complex structural transitions between ordered phases.

Microcrystal Growth Pathways Investigated with Machine Learning Segmentation and Classification in Scanning Electron Microscopy.

Advances in electron microscopy have revolutionized material characterization on the nano- and microscales, providing important insights into local ordering, structure, and size and quality distributions. While shape and size can be rigorously quantified through microscopy, it is often limited to local structure analysis and fails to describe bulk sample quality. Herein, a flexible machine learning (ML) tool is described that can segment and classify faceted crystals in scanning electron microscopy (SEM) micrographs to determine sample quality through the crystal size and product distribution. As a case study, this tool was applied to investigate crystal growth pathways (classical nucleation and growth compared to nonclassical growth) in DNA-mediated nanoparticle assembly through size and product (single crystal, fused crystal, or noncrystal) distribution of samples containing over 13000 colloidal crystal products. Strong DNA bond strengths (controlled by DNA sequence) lead to fast nucleation that exhausts the monomer concentration, resulting in smaller colloidal crystals. Alternatively, increased thermal energy and crystallization time lead to nonclassical crystallization pathways (coalescence) that result in larger colloidal crystals. This tool is useful since experimental conditions can now be deliberately identified to control colloidal crystal size and size distribution, important considerations for researchers interested in designing and synthesizing colloidal crystal metamaterials.

Analysis of Local Structure of Mechanical and Thermal Rearrangements in Glasses with the Atomic Cluster Expansion.

We explore the structural signatures of excitations in amorphous materials with the atomic cluster expansion (ACE), a universal and complete linear basis of descriptors of the atomic environment. Body-orderd linear classifiers are constructed that distinguish between active and inactive particles in three different model glass formers, in which structural relaxation occurs either through spontaneous thermal activation or by simple shear. We find that in binary mixtures, maximum prediction accuracy is already achieved with very few two-body correlations, while a polymer glass requires both two- and three-body correlations. Trends are robust across both activation mechanisms.

Boosting Energy-Storage in High-Entropy Pb-Free Relaxors Engineered by Local Lattice Distortion.

The high-entropy strategy has shown potential in advancing the energy-storage performance of dielectric capacitors, offering benefits to a range of electronic and electrical systems. However, designing high-performance high-entropy relaxor ferroelectrics (RFEs) presents challenges due to the unclear correlation between their core effects and local polarization heterogeneity. Here, we demonstrate that by engineering the local lattice distortion, a core effect in high-entropy systems, to manipulate the local polarization configuration, a giant energy density (Wrec) of 18.7 J cm-3 and high efficiency (η) of 85% can be achieved in (Bi0.5K0.5)TiO3-based high-entropy bulk RFE ceramics. Atomic-level local structural analysis unveils that the local lattice distortion field can be flattened by introducing ions with less size mismatch. The increase in configurational entropy from 1.54 to 2.06R is associated with a smoother polar displacement vector field and a reduction in the size of polar clusters to several unit-cell sizes with weak coupling. Consequently, a substantial decrease in hysteresis and an enhancement in the breakdown field strength can be obtained, leading to a significant improvement in energy density by over 6 times and efficiency by 3 times. Our research establishes a relationship between local lattice distortion, atomic polar displacement, and energy-storage performance in complex high-entropy systems, providing insights for enhancing energy-storage performance via a local structure design.

Study on the Effect of Ce Doping Concentration on the Kinetics of Graphene Formation

The thermodynamic and kinetic processes of Ce-doped graphene were simulated by the method of first-principles molecular dynamics. The structural optimization and annealing, the kinetic properties of Ce-doped graphene composites were calculated by the classical mechanics Forcite module. The results show that with the increase of Ce doping concentration, the order of the radial distribution function in the system increases and presents a state of aggregation. According to the analysis of mean azimuth shift function, the mean square displacement (MSD) value of Ce doped graphene composite increases with the increase of doping concentration, and the corresponding diffusion coefficient also increases. The research of gyration radius and gyration evolution radius shows that with the increase of temperature and doping concentration, the gyration evolution radius of atoms becomes shorter and shorter, indicating that the interatomic force in the system is enhanced and the range of activity is shortened. Combined with the analysis of local cluster structure, it can be seen that the maximum cluster size and number of Ce doped graphene composites do not change significantly with the increase of doping concentration, indicating that Ce atom doping will improve the order in the system, increase the diffusion coefficient and enhance the interaction force between atoms. The paper aims to reduce the error between the theoretical properties and the actual properties, and provide a theoretical basis for the development of new materials with excellent properties.

Local and electronic structures of NaNbO3, AgNbO3, and KNbO3

NaNbO3, AgNbO3, and KNbO3 with ABO3-type perovskite systems are known to possess good ferroelectric properties. In their traditional average structure, a change in the A-site ion size changes the involved tolerance factor. Herein, we directly determined the rattling space of each atom through local structure analysis. By combining a pair distribution function and an extended X-ray absorption fine structure, this analysis revealed that the bonding sites with large fluctuations varied with varying ion sizes. Experimental evidence including soft X-ray absorption spectroscopy, indicates that the A-site ions are hybridized with oxygen.

Liquid thermophysical properties of Ag-Si alloy based on deep learning potential

The knowledge of the thermophysical properties of liquid metals and alloys is essential for expanding the materials database and designing materials with good properties. In this work, we developed an interatomic potential using a deep neural network (DNN) algorithm for liquid Ag-Si alloys. Compared with ab initio molecular dynamics (AIMD) results, the DNN potential provided a good description of the information of energy, force, and structure features of the system in the simulated temperature range. Through this potential, we can obtain the thermophysical properties of different compositions of liquid alloys by simulation way. The computed thermophysical properties are in excellent agreement with the reported experimental data. The analysis of local structure indicates that the liquid ordering and stability strengthen upon cooling at the atomic level, eventually leading to an increase in thermophysical properties.

Global-local state analysis and monitoring-based velocity measurement of oil–gas–water three-phase flow

The mixture fluids of oil–gas–water metamorphose through the change of phase, properties and structure. This poses a challenge to decipher their dynamic entanglement for phase velocity measurement. It is evident that progressively grasp of process states provides valuable prior information for further flow velocity measurement. As a significant flow characteristic, multiscale gives unique inspiration for flow state monitoring and velocity measurement from a global–local view. In this work, empirical wavelet transform-based Hilbert-Huang transform (EWT-based HHT) and multiscale robust empirical permutation entropy (Ms-rePE) are employed for the analysis of CWUD and conductance signals respectively, achieving the joint characterization of oil–gas–water flow structure by acoustic-electrical dual-mode information. On this basis, a data-mechanism dual-driven model for flow velocity measurement is established under a unified multiscale framework. And a novel approach of hypergraph-based global–local structure analysis (HGLSA) is proposed to simultaneously extract global–local information embodied in the complex flow process. The proposed scheme of global–local state monitoring-based flow velocity measurement is verified by the dynamic experiment of oil–gas–water three phase flow.

Structural characterisation of Eastern Canada’s old industrial masonry buildings via typological analysis: part II – building database analysis

The typological analysis conducted in the companion paper is further expanded within this work through the critical analysis of a new extensive building database specifically conceived for old industrial masonry buildings in Eastern Canada. The identification of recurrent unreinforced masonry (URM) building archetypes in this low-to-moderate seismic region is essential to decrease uncertainties currently prevalent in the analysis of local old URM structures, often targeted for adaptive reuse. The database assembled herein comprises various heritage designated buildings across Eastern Canada and was compiled harmonising existing repositories at the federal, provincial and municipal level with an unprecedented focus on structural features. The characteristics of these resources are quantitatively analysed and applied to a case study of the city of Montréal, one of the most important industrial centres in nineteenth and twentieth century Canada. Outcomes from this study will guide practitioners and researchers involved in the structural and seismic assessment and retrofit of old industrial URM constructions, enable more and less invasive rational retrofit designs and inform the new Existing Structures provisions to be included in the 2030 National Building Code of Canada.

Ultrahigh energy storage performance in BNT-based binary ceramic via relaxor design and grain engineering

Dielectric capacitors attract much attention for advanced electronic systems owing to their ultra-fast discharge rate and high power density. However, the low energy storage density (Wrec) and efficiency (η) severely limit their applications. Herein, Bi0.5Na0.5TiO3-K0.5Na0.5NbO3 binary ceramic is developed to obtain excellent energy storage performance with strong relaxor behavior, together with large polarization and distorted lattice calculated by first-principles calculations. The atomic-scale local structure analysis of 0.75Bi0.5Na0.5TiO3–0.25K0.5Na0.5NbO3 ceramic reveals distorted polarization distribution and small polar nanoregion related with the enhanced relaxation and low hysteresis. Finite element analysis demonstrates ultrafine grain and increased grain boundary density following hot-pressing sintering are crucial factors in significantly enhancing the breakdown strength (Eb). As a result, ultrahigh Wrec of 12.39 J/cm3 and η of 87.1 % are achieved at a superhigh Eb of 713 kV/cm. Encouragingly, excellent performance of temperature, frequency and fatigue stability at 400 kV/cm are obtained, and high power density of ∼ 306 MW/cm3 as well as fast discharge speed of ∼ 23.3 ns are also realized. This work proposes a simple binary design with strong relaxor behavior, and highlights the potential of grain engineering to achieve outstanding energy storage performance with great stability and excellent charge-discharge property for pulse power devices.

Spinel cobalt-based binary metal oxides as emerging materials for energy harvesting devices: synthesis, characterization and synchrotron radiation-enabled investigation.

The synthesis and characterization of spinel cobalt-based metal oxides (MCo2O4) with varying 3d-transition metal ions (Ni, Fe, Cu, and Zn) were explored using a hydrothermal process (140 °C for two hours) to be used as alternative counter electrodes for Pt-free dye-sensitized solar cells (DSSCs). Scanning electron microscopy (SEM) and atomic force microscopy (AFM) revealed distinct morphologies for each metal oxide, such as NiCo2O4 nanosheets, Cu Co2O4 nanoleaves, Fe Co2O4 diamond-like, and Zn Co2O4 hexagonal-like structures. The X-ray diffraction analysis confirmed the cubic spinel structure for the prepared MCo2O4 films. The functional groups of MCo2O4 materials were recognized in metal oxides throughout Fourier transform infrared (FTIR) analysis. The local structure analysis using X-ray absorption fine structure (XAFS) at Fe and Co K-edge identified octahedral (Oh) Co3+ and tetrahedral (Td) Co2+ coordination, with Zn2+ and Cu2+ favoring Td sites, while Ni3+ and Fe3+ preferred Oh active sites. Further investigations utilizing the Fourier transformation (FT) analysis showed comparable coordination numbers and interatomic distances ranked as Co-Cu > Co-Fe > Zn-Co > Co-Ni. Furthermore, the utilization of MCo2O4 thin films as counter electrodes in DSSC fabrication showed promising results. Notably, solar cells based on CuCo2O4 and ZnCo2O4 counter electrodes showed 1.9% and 1.13% power conversion efficiency, respectively. These findings indicate the potential of employing these binary metal oxides for efficient and cost-effective photovoltaic device production.

Local structural modelling and local pair distribution function analysis for Zr–Pt metallic glass

In disordered glass structures, the structural modelling and analyses based on local experimental data are not yet established. Here we investigate the icosahedral short-range order (SRO) in a Zr–Pt metallic glass using local structural modelling, which is a reverse Monte Carlo simulation dedicated to two-dimensional angstrom-beam electron diffraction (ABED) patterns, and local pair distribution function (PDF) analysis. The local structural modelling invariably leads to the icosahedral SRO atomic configurations that are similarly distorted by starting from some different initial configurations. Furthermore, the SRO configurations with 11–13 coordination numbers reproduce almost identical ABED patterns, indicating that these SRO structures are similar to each other. Further local PDF analysis explicitly indicates the presence of the wide distribution of atomic bond distances, which is comparable to the global PDF profile, even at the SRO level. The SRO models based on the conventional MD simulation can be strengthened by comparison with those obtained by the present local structural modelling and local PDF analysis based on the ABED data.

Simple and efficient methods for local structural analysis in polydisperse hard disk systems.

In nonequilibrium statistical physics, quantifying the nearest (and higher-order) neighbors and free volumes of particles in many-body systems is crucial to elucidating the origin of macroscopic collective phenomena, such as glass/granular jamming transitions and various aspects of the behavior of active matter. However, conventional techniques (based on a fixed-distance cutoff or the Voronoi construction) have mainly been applied to equilibrated, homogeneous, and monodisperse particle systems. In this paper, we implement simple and efficient methods for local structure analysis in nonequilibrium, inhomogeneous, and polydisperse hard disk systems. We show how these novel methods can overcome the difficulties encountered by conventional techniques as well as demonstrate some applications.

Strong Local Polarization Fluctuations Enabled High Electrostatic Energy Storage in Pb-Free Relaxors.

Electrostatic energy-storage ceramic capacitors are essential components of modern electrified power systems. However, improving their energy-storage density while maintaining high efficiency to facilitate cutting-edge miniaturized and integrated applications remains an ongoing challenge. Herein, we report a record-high energy-storage density of 20.3 J cm-3 together with a high efficiency of 89.3% achieved by constructing a relaxor ferroelectric state with strongly enhanced local polarization fluctuations. This is realized by incorporating highly polarizable, heterovalent, and large-sized Zn and Nb ions into a Bi0.5Na0.5TiO3-BaTiO3 ferroelectric matrix with very strong tetragonal distortion. Element-specific local structure analysis revealed that the foreign ions strengthen the magnitude of the unit-cell polarization vectors while simultaneously reducing their orientation anisotropy and forming strong fluctuations in both magnitude and orientation within 1-3 nm polar clusters. This leads to a particularly high polarization variation (ΔP) of 72 μC cm-2, low hysteresis, and a high effective polarization coefficient at a high breakdown strength of 80 kV mm-1. This work has surpassed the current energy density limit of 20 J cm-3 in bulk Pb-free ceramics and has demonstrated that controlling the local structure via the chemical composition design can open up new possibilities for exploring relaxors with high energy-storage performance.

Exploring the Effects of the Photochromic Response and Crystallization on the Local Structure of Noncrystalline Niobium Oxide.

Niobium oxide (Nb2O5) is a versatile semiconductor material with photochromic properties. This study investigates the local structure of noncrystalline, short-range-ordered niobium oxide synthesized via a sol-gel method. X-ray atomic pair distribution function analysis unravels the structural arrangements within the noncrystalline materials at a local scale. In the following, in situ scattering and diffraction experiments elucidate the heat-induced structure transformation of the amorphous material into crystalline TT-Nb2O5 at 550 °C. In addition, the effect of photocatalytic conditions on the structure of the material was investigated by exposing the short-range-ordered and crystalline materials to ultraviolet light, resulting in a reversible color change from white to dark brown or blue. This photochromic response is due to the reversible elongation of the nearest Nb-O neighbors, as shown by local structure analysis based on in situ PDF analyses. Optical band gap calculations based on the ultraviolet-visible spectra collected for both the short-range-ordered and crystalline materials show that the band gap values reduced for the darkened materials return to their initial state after bleaching. Furthermore, electron energy loss spectroscopy reveals the reduction of Nb5+ to Nb4+ centers as a persistent effect. The study establishes a correlation between the band gap and the structure of niobium oxide, providing insights into the structure-performance relation at the atomic level.

Local structure and phase composition of Neodymium-Zircon solid solution (NdxZr1-xSiO4-x/2)

To address the structural stability of host materials for immobilizing radioactive actinides in nuclear waste management applications, the present study is focused on the effect of various concentrations of Nd substitution on structural properties of synthetic zircon (NdxZr1-xSiO4-x/2). To achieve this, both pure and Nd-substituted zircon powders were prepared using the solid-state synthesis route. Rietveld refinement of X-ray Diffraction (XRD) data was employed to investigate the impact of various Nd substitutions on the phase composition of the zircon (ZrSiO4) crystal structure. This refined data was then utilized as input for the analysis of X-ray absorption spectroscopy (XAS) data. The results were further supported by observations from Raman spectroscopy, which indicated the substitution of Zr by Nd. In this work, we present an analysis of both regimes of XAS i.e. X-ray Absorption Near Edge Structure (XANES) and Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy. Qualitative analysis of XANES data suggests that disorder in the samples increases with higher levels of Nd doping. Additionally, EXAFS analysis around Zr absorption edge also confirms an increased disorder in the system with higher Nd doping levels. However, EXAFS fitting around Nd edge indicated that disorder induced changes are more prominent and Nd–O bond is elongated as compared to Zr–O bond. This disorder in the system escalates at a Nd concentration of 10 atomic % (at %). An important finding of this study is the phase composition analysis using Rietveld refinement of XRD data. While XAS provided an insight into the changes in the local structure, the overall crystal structure remained unaffected even at a high doping of 10 at %. This work provides a comprehensive local structure analysis on this system. Such analysis would help in understanding the structural stability of the system and to determining the maximum loading of actinides in the host zircon for potential nuclear waste management applications.

Local structure and defect analysis of KVO3 doped BiFeO3–BaTiO3 ceramics facing conductivity, permittivity, and magnetic properties

This study discovers the effects of KVO3 doping on BiFeO3–BaTiO3 regarding phase transitions, defect formation, and changes in electronic and magnetic behavior. The synthesized material (1-x-y)BiFeO3-xBaTiO3-yKVO3 with (x = 0.33, 0.38 and y = 0, 0.01) have pseudo-cubic structure, where the FeO6 octahedron was elongated in the z-axis, and Fe has an oxidation state of 3+ and 4+. The electrons in the 3d subshell initially showed a high spin state, transitioning to a low state after KVO3 doping. Further investigation identified phase transition Rhombohedral + Pseudo Cubic to Rhombohedral for FT33 at T∼100°C and Pseudo Cubic phase to Cubic phase for FT38 at T∼200°C. Conductivity at low temperatures ascribed to unbinding electrons, while the presence of defect-creating dipole strengthened the dipole polarization. The magnetization hysteresis of KVO3-doped samples significantly decreased due to the high spin state transformed to the low spin state of the 3d subshell of Fe in the octahedron FeO6.

Local defect and mid-gap state analysis of GaN using monochromated EELS combined with nanodiffraction and atomic-resolution imaging

Defects in semiconductor materials significantly impact their inherent properties, making the evaluation of local defects and their energy levels crucial for controlling device performance. With advancements in monochromators, electron energy loss spectroscopy (EELS) combined with scanning transmission electron microscopy (STEM) has emerged as a promising approach for assessing crystal and band structures of semiconductor materials at the nanoscale. However, there is limited experimental research investigating the relationship between actual defective structures in local regions and mid-gap states. In this study, we conducted high-energy resolution EELS (HR-EELS) measurements with an energy resolution of less than 100 meV to detect the mid-gap states of GaN. Various defects were intentionally induced through Ga-ion implantation, and the defect concentration varied in the depth direction. To understand the origin of the mid-gap states, we performed 4D-STEM analysis and atomic-resolution STEM observations. The HR-EELS measurements provided insights into the depth-dependent valence-loss spectra, revealing that the intensities corresponding to mid-gap states gradually increased toward the surface, whereas the slope at the onsets corresponding to interband transition decreased. Furthermore, local structural analysis unveiled the presence of structural disorder and defective structures, indicating the existence of extended defects such as stacking faults and domain boundaries. Observably, these defective structures were abundant near the surface and less pronounced in deeper regions. Based on these experimental findings, we concluded that the variations in valence-loss spectra can be utilized to qualitatively evaluate the crystal imperfections at the nanoscale.

Chemical Framework to Design Linear-like Relaxors toward Capacitive Energy Storage.

ABO3-type perovskite relaxor ferroelectrics (RFEs) have emerged as the preferred option for dielectric capacitive energy storage. However, the compositional design of RFEs with high energy density and efficiency poses significant challenges owing to the vast compositional space and the absence of general rules. Here, we present an atomic-level chemical framework that captures inherent characteristics in terms of radius and ferroelectric activity of ions. By categorizing A/B-site ions as host framework, rattling, ferroelectrically active, and blocking ions and assembling these four types of ions with specific criteria, linear-like relaxors with weak locally correlated and highly extendable unit-cell polarization vectors can be constructed. As example, we demonstrate two new compositions of Bi0.5K0.5TiO3-based and BaTiO3-based relaxors, showing extremely high recoverable energy densities of 17.3 and 12.1 J cm-3, respectively, both with a high efficiency of about 90%. Further, the role of different types of ions in forming heterogeneous polar structures is identified through element-specific local structure analysis using neutron total scattering combined with reverse Monte Carlo modeling. Our work not only opens up new avenues toward rational compositional design of high energy storage performance lead-free RFEs but also sheds light on atomic-level manipulation of functional properties in compositionally complex ferroelectrics.