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At least 73 records · Page 4

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗

Benchmarking Density Functional Theory Methods for Efficient Calculations of a Strongly Correlated Li 1– x Ni 1– y O 2−δ System

Transition metal oxides (TMOs), such as LiNiO 2 , are promising candidates for energy storage and electronic devices due to their unique electronic properties, exceptional physical and chemical characteristics, and ability to adopt multiple oxidation states. However, accurately predicting their properties using mean-field density functional theory (DFT) is challenging due to the presence of strongly correlated d-electrons and the complex interplay between their structural, electronic, and magnetic responses. These challenges are further exacerbated by the need to model defects, surfaces, and interfaces, which require computationally efficient, large-scale simulations. To address these issues, we carry out a benchmark study on the Li 1–x NiO 2 system, evaluating the performance of several popular functionals. Our findings demonstrate that combining SCAN functional relaxation with single-step HSE calculations provides a practical and scalable computational strategy. This approach balances accuracy and efficiency, enabling high-throughput simulations of strongly correlated TMOs and improved predictive modeling capability of TMOs for practical applications.

25 ENERGY STORAGE↗

Computing Edge States without Hard Truncation

We present a numerical method which accurately computes the discrete spectrum and associated bound states of semi-infinite Hamiltonians which model electronic “edge” states localized at boundaries of one- and two-dimensional crystalline materials. The problem is nontrivial since arbitrarily large finite “hard” (Dirichlet) truncations of the Hamiltonian in the infinite bulk direction tend to produce spurious bound states partially supported at the truncation. Our method, which overcomes this difficulty, is to compute the Green's function of the semi-infinite Hamiltonian by imposing an appropriate boundary condition in the bulk direction; then, the spectral data is recovered via Riesz projection. We demonstrate our method's effectiveness by studies of edge states at a graphene zig-zag edge in the presence of defects modeled both by a discrete tight-binding model and a continuum PDE model under finite difference discretization. Our method may also be used to study states localized at domain wall-type edges in one- and two-dimensional materials where the edge Hamiltonian is infinite in both directions; we demonstrate this for the case of a tight-binding model of distinct honeycomb structures joined along a zig-zag edge. Here, we expect our method to be useful for designing novel devices based on precise wave-guiding by edge states.

97 MATHEMATICS AND COMPUTING↗

Irradiation damage reduces alloy corrosion rate via oxide space charge compensation effects

Radiation effects in materials often compound and accelerate other detrimental phenomena such as embrittlement, oxidation and creep. However, irradiation can also decrease the oxidation rate, for instance with ZrNb alloys nuclear fuel cladding. In this study, we rationalize this observation on Zr-0.5Nb alloy by introducing a mechanism based on oxide space charge modification, resulting from irradiation enhanced Nb clustering. Here, this mechanism is investigated using a multiscale approach: from the macroscale, to determine post-irradiation oxidation kinetics, to the atomic scale, using in-situ atom probe tomography sample oxidation, to observe elemental solute redistribution across the oxide/metal interface. The mechanism is further supported by high resolution transmission electron microscopy characterization and density functional theory calculations. A point defect model is proposed to account for oxide space charge effects and their changes under irradiation. This integrated, multiscale experimental and modeling approach challenges the current paradigm on irradiation effects and how they can potentially improve materials performance in extreme environments.

36 MATERIALS SCIENCE↗

Corrosion of rebar in concrete. Part II: Literature survey and statistical analysis of existing data on chloride threshold

The literature is reviewed with respect to defining, measuring, and interpreting the chloride threshold (CT). CT was defined with a strong fundamental basis in the Point Defect Model. which also dictates the nature of the statistical analysis of surveyed CT values. A database of CT for various primary and secondary independent variables has been established. Statistical analyses reveal that CT is lognormally distributed, in accordance with the PDM, with most probable values being 0.85, 0.69, and 1.19 for %total Cl/cem, %free Cl/cem, and [Cl - ]/[OH - ], respectively. The breakdown and corrosion potentials follow normal distributions with means of 0.056 and -0.322 V SCE , respectively.

36 MATERIALS SCIENCE↗

Fundamental Insights into Cathode Stability: Linking Compositional Tuning and Local Coordination in Complex Metal Oxides under Aqueous Transformations

Compositional tuning of complex metal oxides in Li-ion battery materials influences their performance as well as their end-of-life behavior, in particular, the tendency to release toxic metal cations in aqueous solution. We modeled ternary variants of a parent LiCoO 2 delafossite structure by varying the metal identity and relative amounts. This yielded ten model formulations of Li(A 4/6 B 1/6 C 1/6 )O 2 , where the material is enriched with the A metal and doped with B and C, with Ni, Mn, Co, Fe, Al, V, and Ti as constituent metals. To assess their stability in aqueous conditions, metal release energetics were calculated using a combination of Density Functional Theory calculations and thermodynamics. Metal release in ternary oxides is dictated by subtle variations in the coordination environment of the leaving group. To identify governing chemical features across diverse compositions with varying local coordination environments, we leverage random forest regression and descriptor importance analysis. A key result is that metal–oxygen orbital hybridization, quantified using a projected density-of-states-derived descriptor, H d/p , provides a physically grounded measure of interaction strength that governs metal release energetics. This refined perspective goes beyond conventional oxidation state considerations and offers more robust insights for materials science. Finally, we model defect surface-bound O 2 dimer formation as a proxy for reactive oxygen species (ROS) generation. The results show that Ni-rich compositions more readily stabilize spin-polarized O 2 dimers, corroborating experimental reports of an increased ROS-driven biological response. In conclusion, our results establish a compositional and electronic basis for metal release and surface oxygen reactivity that form a rationale for complex metal oxide design principles.

36 MATERIALS SCIENCE↗

Ultra-low binder content 3D printed calcium phosphate graphene scaffolds as resorbable, osteoinductive matrices that support bone formation in vivo

Bone regenerative engineering could replace autografts; however, no synthetic material fulfills all design criteria. Nanocarbons incorporated into three-dimensional printed (3DP) matrices can improve properties, but incorporation is constrained to low wt%. Further, unmodified nanocarbons have limited osteogenic potential. Functionalization to calcium phosphate graphene (CaPG) imparts osteoinductivity and osteoconductivity, but loading into matrices remained limited. This work presents ultra-high content (90%), 3DP-CaPG matrices. 3DP-CaPG matrices are highly porous (95%), moderately stiff (3 MPa), and mechanically robust. In vitro, they are cytocompatible and induce osteogenic differentiation of human mesenchymal stem cells (hMSCs), indicated by alkaline phosphatase, mineralization, and COL1α1 expression. In vivo, bone regeneration was studied using a transgenic fluorescent-reporter mouse non-union calvarial defect model. 3DP-CaPG stimulates cellular ingrowth, retains donor cells, and induces osteogenic differentiation. Histology shows TRAP staining around struts, suggesting potential osteoclast activity. Apparent resorption of 3DP-CaPG was observed and presented no toxicity. 3DP-CaPG represents an advancement towards a synthetic bone regeneration matrix.

60 APPLIED LIFE SCIENCES↗

Resolving local structural motifs across the phase evolution of zinc titanates with computational x-ray absorption spectroscopy

Resolving the local structure motifs that characterize phase evolution as a function of composition is a key challenge in structure characterization of complex materials. Here, in this study, we combine first-principles simulations and x-ray absorption near-edge structures (XANES) analysis to gain insights into the structure evolution revealed by measurements across a combinatorial zinc titanate thin film, which was grown with smoothly varying composition over a wide range of the Ti:Zn ratio. Specifically, we propose a cluster blind-signal-separation (cBSS) method for XANES spectral analysis based on a library of the structures and spectra of representative local motifs. In addition to motifs from zinc titanate crystals, two types of Ti-defect models constructed in this study are key to the understanding of the structure characteristics in the Zn-rich region. The cBSS method makes use of both spectral clustering of the simulated site-XANES spectra library and the BSS procedure to construct high-fidelity spectral basis functions from an experimental spectral sequence. The method provides a rigorous measure of the spectral sensitivity and basis completeness. The results of the XANES analysis are corroborated with other experimental modalities, including x-ray diffraction and spectroscopic ellipsometry, to validate the cBSS method. The calculated motif weights resulting from fitting the XANES spectra with the cBSS basis probe the atomic structure characteristics of both crystalline and amorphous phases as a function of the Ti/Zn composition. The insights of the local structure motif evolution are pivotal to the understanding of the nonmonotonic trend in the optical gap, which may lead to potential applications through tuning the optical properties of zinc titanate. The workflow of the XANES spectral analysis developed in this work can be generalized to construct the structure-property relationship in a broad material space.

36 MATERIALS SCIENCE↗

Thin-film chemical expansion of ceria based solid solutions: laser vibrometry study

The chemical expansion of Pr 0.1 Ce 0.9 O 2-δ (PCO) and CeO 2-δ thin films is investigated in the temperature range between 600 °C and 800 °C by laser Doppler vibrometry (LDV). It enables non-contact determination of nanometer scale changes in film thickness at high temperatures. The present study is the first systematic and detailed investigation of chemical expansion of doped and undoped ceria thin films at temperatures above 650 °C. The thin films were deposited on yttria stabilized zirconia substrates (YSZ), operated as an electrochemical oxygen pump, to periodically adjust the oxygen activity in the films, leading to reversible expansion and contraction of the film. This further leads to stresses in the underlying YSZ substrates, accompanied by bending of the overall devices. Film thickness changes and sample bending are found to reach up to 10 and several hundred nanometers, respectively, at excitation frequencies from 0.1 to 10 Hz and applied voltages from 0–0.75 V for PCO and 0–1 V for ceria. At low frequencies, equilibrium conditions are approached. As a consequence maximum thin-film expansion of PCO is expected due to full reduction of the Pr ions. The lower detection limit for displacements is found to be in the subnanometer range. At 800 °C and an excitation frequency of 1 Hz, the LDV shows a remarkable resolution of 0.3 nm which allows, for example, the characterization of materials with small levels of expansion, such as undoped ceria at high oxygen partial pressure. As the correlation between film expansion and sample bending is obtained through this study, a dimensional change of a free body consisting of the same material can be calculated using the high resolution characteristics of this system. A minimum detectable dimensional change of 5 pm is estimated even under challenging high-temperature conditions at 800 °C opening up opportunities to investigate electro-chemo-mechanical phenomena heretofore impossible to investigate. The expansion data are correlated with previous results on the oxygen nonstoichiometry of PCO thin films, and a defect model for bulk ceria solid solutions is adopted to calculate the cation and anion radii changes in the constrained films during chemical expansion. The constrained films exhibit anisotropic volume expansion with displacements perpendicular to the substrate plane nearly double that of bulk samples. The PCO films used here generate high total displacements of several 100 nm’s with high reproducibility. Consequently, PCO films are identified to be a potential core component of high-temperature actuators. They benefit not only from high displacements at temperatures where most piezoelectric materials no longer operate while exhibiting, low voltage operation and low energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composition stability limits for the rocksalt-structure phase /Pb1-y Sny/1-xTex from lattice parameter measurements.

The parameter values measured are in agreement with those reported by Mazelsky and Lubell (1963) and data of Bis and Dixon (1969). The measurements for SnTe introduce a large amount of data into a defect model analysis that shows that the ratio of the number of holes per tin-vacancy acceptor to the 77 K Hall factor is independent of the apparent hole concentration. The measurements reveal some interesting problems in handling the Sn-rich alloys in fine powder form due to the uptake of oxygen.

Brebrick, R. F.↗

Defect chemistry and characterization of (Hg, Cd)Te

Single crystal samples of phosphorus doped Hg sub 0.8 Cd sub 0.2 Te were anneald at temperatures varying from 450 C to 600 C in various Hg atmospheres. The samples were quenched to room temperature from the annealing temperatures. Hall effect and mobility measurements were performed at 77 K on all these samples. The results indicate the crystals to be p type for a total phosphorus concentration of 10 to the 19th power/cu cm in all the samples. The hole concentration at 77 K increases with increasing Hg pressures at 450 C and 500 C contrary to the observation in undoped crystals. Also, at low Hg pressures the concentration of holes in the phosphorus doped crystals is lower than in the undoped crystals. The hole concentration in all the samples is lower than the intrinsic carrier concentration at the annealing temperatures. The hole mobility in the doped crystals is similar to that in the undoped crystals. A defect model according to which phosphorus behaves as a single acceptor interstitially, occupying Te lattice sites while it acts as a single donor occupying Hg lattice sites was established. Equilibrum constants established for the incorporation of all the phosphorus species explain the experimental results

Vydyanath, H. R.↗

Transport Equation Based Wall Distance Computations Aimed at Flows With Time-Dependent Geometry

Eikonal, Hamilton-Jacobi and Poisson equations can be used for economical nearest wall distance computation and modification. Economical computations may be especially useful for aeroelastic and adaptive grid problems for which the grid deforms, and the nearest wall distance needs to be repeatedly computed. Modifications are directed at remedying turbulence model defects. For complex grid structures, implementation of the Eikonal and Hamilton-Jacobi approaches is not straightforward. This prohibits their use in industrial CFD solvers. However, both the Eikonal and Hamilton-Jacobi equations can be written in advection and advection-diffusion forms, respectively. These, like the Poisson s Laplacian, are commonly occurring industrial CFD solver elements. Use of the NASA CFL3D code to solve the Eikonal and Hamilton-Jacobi equations in advective-based forms is explored. The advection-based distance equations are found to have robust convergence. Geometries studied include single and two element airfoils, wing body and double delta configurations along with a complex electronics system. It is shown that for Eikonal accuracy, upwind metric differences are required. The Poisson approach is found effective and, since it does not require offset metric evaluations, easiest to implement. The sensitivity of flow solutions to wall distance assumptions is explored. Generally, results are not greatly affected by wall distance traits.

Tucker, Paul G.↗

Transport Equation Based Wall Distance Computations Aimed at Flows With Time-Dependent Geometry

Eikonal, Hamilton-Jacobi and Poisson equations can be used for economical nearest wall distance computation and modification. Economical computations may be especially useful for aeroelastic and adaptive grid problems for which the grid deforms, and the nearest wall distance needs to be repeatedly computed. Modifications are directed at remedying turbulence model defects. For complex grid structures, implementation of the Eikonal and Hamilton-Jacobi approaches is not straightforward. This prohibits their use in industrial CFD solvers. However, both the Eikonal and Hamilton-Jacobi equations can be written in advection and advection-diffusion forms, respectively. These, like the Poisson's Laplacian, are commonly occurring industrial CFD solver elements. Use of the NASA CFL3D code to solve the Eikonal and Hamilton-Jacobi equations in advective-based forms is explored. The advection-based distance equations are found to have robust convergence. Geometries studied include single and two element airfoils, wing body and double delta configurations along with a complex electronics system. It is shown that for Eikonal accuracy, upwind metric differences are required. The Poisson approach is found effective and, since it does not require offset metric evaluations, easiest to implement. The sensitivity of flow solutions to wall distance assumptions is explored. Generally, results are not greatly affected by wall distance traits.

Tucker, Paul G.↗

Atomistically-informed modeling of point defect clustering and evolution in irradiated ThO 2

A cluster dynamics (CD) model has been developed to investigate the nucleation and growth of point defect clusters, i.e., interstitial prismatic loops and nanoscale and sub-nanoscale voids, in ThO 2 during irradiation by energetic particles. The model considers cluster off-stoichiometry due to the asymmetry of point defect generation on the O and Th sublattices under irradiation, as well as the point defect diffusivities and the defect binding energies to clusters. The energies were established using detailed molecular dynamics simulations considering the statistical variability of cluster configuration. A high-order adaptive time-integration has been used to solve the model. The predicted loop density and their average size is in good agreement with reported experimental observations for proton irradiated ThO 2 at 600°C. In conclusion, the model did not predict void evolution due to the sluggish kinetics of cation vacancies, explaining the absence of voids in proton irradiated ThO 2 (and other oxides) at relatively low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Process/Device Modeling and Point Defect Engineering of Cu(In,Ga)Se 2 Solar Cells

Point defects directly impact solar cell device performance by limiting the carrier lifetime. In this work, density functional theory calculations are first used to determine the formation energy and diffusion energy barriers of dominant defects in Cu(In,Ga)Se 2 . Next, continuum reaction–diffusion models are developed to analyze the redistribution of defects during manufacturing processes. We estimate defect capture cross sections using a first-principles-based approach. Here, these cross sections are combined with our calculated defect profiles and trap energy levels to parameterize a Shockley–Read–Hall recombination model, which we implement into a device simulator to predict carrier lifetimes and device performance. In that way, a predictive technology computer aided design model is built to predict and optimize the performance of Cu(In,Ga)Se 2 solar cells.

14 SOLAR ENERGY↗

Chemical composition based machine learning model to predict defect formation in additive manufacturing

With a goal of exploiting additive manufacturing to improve the manufacturing of existing reactor materials, we developed a chemical composition-based machine learning model to predict the printability of any given alloy in laser powder bed fusion (L-PBF) using experimental data from peer-reviewed literature. We defined printability as the ability to avoid defects like cracking, balling, porosity, and lack of fusion, that are caused by thermal stresses (during solidification or liquation), molten pool disintegration into disconnected small beads or lack of heat input respectively. Our models predict the tendency of balling defect formation and porosity percentage for a given composition, under a given set of processing conditions. To predict the likelihood of balling defect, three models: a random forest classifier, a gradient boost regressor and a neural network were trained on a dataset containing both traditional alloys and high entropy alloys. The neural network model showed the highest accuracy of 92.3 % in predicting the balling defect formation. A random forest regressor, gradient boost regressor and neural network were trained and tested on a dataset of various alloys to predict porosity. The random forest regressor showed the best predictions with an R 2 score of 0.97. The models also revealed the relative importance of the input descriptors on defect-formation tendency. Of particular significance was the identification of carbon as an important element in determining the occurrence of balling and percent porosity in alloys like steel, as well as being moderately important to the percentage porosity in other alloys as well as steel. Manganese was also identified as a key descriptor for the percentage of porosity in steel and other alloys. Manganese’s low thermal conductivity and consistent presence in the dataset is the likely cause for its contribution. Carbon’s role is attributable to its relatively high specific heat and high melting temperature. In conclusion, our model serves as a swift, chemistry-based tool to design experiments and find modified compositions better suited for additive manufacturing.

36 MATERIALS SCIENCE↗

Lattice realizations of topological defects in the critical (1+1)-d three-state Potts model

Topological/perfectly-transmissive defects play a fundamental role in the analysis of the symmetries of two dimensional conformal field theories (CFTs). In the present work, spin chain regularizations for these defects are proposed and analyzed in the case of the three-state Potts CFT. In particular, lattice versions for all the primitive defects are presented, with the remaining defects obtained from the fusion of the primitive ones. The defects are obtained by introducing modified interactions around two given sites of an otherwise homogeneous spin chain with periodic boundary condition. The various primitive defects are topological on the lattice except for one, which is topological only in the scaling limit. The lattice models are analyzed using a combination of exact diagonalization and density matrix renormalization group techniques. Low-lying energy spectra for different defect Hamiltonians as well as entanglement entropy of blocks located symmetrically around the defects are computed. The latter provides a convenient way to compute the g-function which characterizes various defects. Finally, the eigenvalues of the line operators in the “crossed channel” and fusion of different defect lines are also analyzed. The results are all in agreement with expectations from conformal field theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗