Comparison of simulated and measured grain volume changes during grain growth
Not Available
Peng, Xiaoyao (ORCID:0000000220544406)↗
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Simultaneous measurements of volume, pressure, optical images, and crystal structure with a dynamic diamond anvil cell: A real-time event monitoring system
The dynamic diamond anvil cell (dDAC) technique has attracted great interest because it possibly provides a bridge between static and dynamic compression studies with fast, repeatable, and controllable compression rates. The dDAC can be a particularly useful tool to study the pathways and kinetics of phase transitions under dynamic pressurization if simultaneous measurements of physical quantities are possible as a function of time. We report the development of a real-time event monitoring (RTEM) system with dDAC, which can simultaneously record the volume, pressure, optical image, and structure of materials during dynamic compression runs. In particular, the volume measurement using both Fabry–Pérot interferogram and optical images facilitates the construction of an equation of state (EoS) using the dDAC in a home-laboratory. We also developed an in-line ruby pressure measurement (IRPM) system to be deployed at a synchrotron x-ray facility. This system provides simultaneous measurements of pressure and x-ray diffraction in low and narrow pressure ranges. The EoSs of ice VI obtained from the RTEM and the x-ray diffraction data with the IRPM are consistent with each other. The complementarity of both RTEM and IRPM systems will provide a great opportunity to scrutinize the detailed kinetic pathways of phase transitions using dDAC.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation
Quantum volume is a full-stack benchmark for near-term quantum computers. It quantifies the largest size of a square circuit which can be executed on the target device with reasonable fidelity. Error mitigation is a set of techniques intended to remove the effects of noise present in the computation of noisy quantum computers when computing an expectation value of interest. Effective quantum volume is a proposed metric that applies error mitigation to the quantum volume protocol to evaluate the effectiveness not only of the target device but also of the error mitigation algorithm. Digital zero-noise extrapolation is an error mitigation technique that estimates the noiseless expectation value using circuit folding to amplify errors by known scale factors and then extrapolating computed expectation values to the zero-noise limit. Here we demonstrate that zero-noise extrapolation, with global and local unitary folding with fractional scale factors, in conjunction with dynamical decoupling, can increase the effective quantum volume over the vendor-measured quantum volume. Specifically, we measure the effective quantum volume of four IBM Quantum superconducting processor units, obtaining values that are larger than the vendor-measured quantum volume on each device. This is the first such increase reported.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Measuring representative volume elements from high-resolution grain-scale strain fields
Most crystalline materials present a highly heterogeneous response at the microscale, which can be affected by both internal factors (such as microstructural parameters) and external factors (such as loading). Relating microscale inhomogeneities to the macroscale response of a material requires the use of homogenisation techniques, usually based on the concept of a representative volume element (RVE)—the smallest volume of material that represents the global average response. Here, in this work, we present a new and robust experimental method of measuring the size of a strain-based RVE from high-resolution grain-scale strain fields obtained using digital image correlation (DIC). The proposed method is based on the statistical (stereological) nature of the RVE, which has been widely adopted in numerical studies, and involves dividing a strain field into randomly selected regions of varying sizes and statistically analysing the distributions of average strains within them. To validate the new method, we generate a large number of synthetic strain fields from a fractional Gaussian noise algorithm. The proposed stereological method is shown to be capable of producing reliable RVE measurements from a very large range of possible microscale strain fields while at the same time being robust in that it can produce RVE measurement results even in cases where other existing methods may be unable to do so. The proposed method has a low field-of-view requirement, only needing a field-of-view about 1.2 times as large as the RVE to produce reliable measurements. In addition, the stereological method offers significant flexibility since its statistical nature allows for control over how strict the RVE measurement should be in each case.
36 MATERIALS SCIENCE↗
Informed unsupervised machine learning analysis of dislocation microstructure from high-resolution differential aperture X-ray structural microscopy data
This study leverages high-resolution differential-aperture X-ray structural microscopy (DAXM) to probe the local dislocation structure in deformed 304L-stainless steel at small strain, by measuring the lattice rotation and deviatoric elastic strain with a sub-micron resolution. For a single grain in a polycrystalline specimen, the measured lattice rotation field over the measured volume exhibited a multimodal distribution while the deviatoric elastic strain showed a single-mode distribution. An unsupervised Cauchy mixture machine learning model was developed to resolve the multimodal distribution of the lattice rotation. By mapping the lattice rotation data associated with each Cauchy peak in the model back onto the measured volume, we identify contiguous regions of the crystal rotated near the average values corresponding to the peaks of the overall rotation distribution. These regions represent the grain subdivision in the microstructure. Finally, the dislocation density tensor was also computed and its norm was laid over the rotation field to detect the subgrain boundaries. This step provided a validation of the Cauchy mixture model for the analysis of the lattice rotation distribution. The current study highlights the integration of advanced X-ray microscopy techniques with data-driven analysis methods to uncover detailed microstructure scales in deformed crystals.
Machine learning; Lattice rotation; High-energy X-↗
Assessment of Mechanical Draft Cooling Tower Thermal Emissions from Visual Images of Plumes
Using a one-dimensional code, we computed the power (enthalpy discharge rate) of a twelve-cell mechanical draft cooling tower (MDCT) using over two hundred visible condensed water vapor plume volume measurements derived from images, weather data, and tower operating conditions. The plume images were simultaneously captured by multiple stationary digital cameras surrounding the cooling tower. An analysis technique combining structure from motion (SfM), a neural-network-based image segmentation algorithm, and space carving was used to quantify the volumes. Afterwards, the power output was computed using novel techniques in the one-dimensional code that included cooling tower exhaust plume adjacency effects implemented with a modified version of the entrainment function, weather data averaged from eleven stations, and fan operations at the times when plume volumes were measured. The model was then compared with the averaged observed power output, and it validated well with an average error ranging from 6 to 12%, depending on the meteorological data used in the simulations. This methodology can possibly determine power plant fuel consumption rates by applying visible imagery.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DECOVALEX-2023: Task D Final Report
Task D of DECOVALEX-2023 is focused on the simulation of the coupled thermal hydraulic-mechanical (THM) behaviour in the full-scale engineered barrier system (EBS). The Horonobe EBS experiment is the demonstration of the full-scale EBS in the underground research laboratory (URL) (performed by JAEA in the Horonobe URL in Japan). Task D consisted of the three steps, a preliminary step (Step 0), simulation of the laboratory tests (Step 1) and simulation of the in-situ full-scale EBS experiment (Step 2). Since the Horonobe EBS experiment demonstrates the vertical emplacement option of the EBS, the experiment gallery is also backfilled with the backfill material. Therefore, interaction between the EBS and the backfill material can also be demonstrated, such as deformation (change of density) of the buffer material. The underground water in the Horonobe URL is saline. This fact adds chemical processes to THM behaviour. For example, mechanical properties (such as swelling pressure of the buffer material and backfill material) and hydraulic properties (such as permeability of the buffer material and backfill material) change depending on the water chemistry. Task D was therefore a challenging Task focused on not only the relatively simple THM behaviour but also complex THM behaviour including chemical processes. Six research teams (BGR, CAS, JAEA, KAERI, SNL and Taipower) participated the Task D. BGR, CAS, JAEA, KAERI and Taipower research teams selected a THM approach, while the SNL research team selected a TH approach. Step 1 involved the simulation of laboratory test results and was important to check the numerical codes developed by the research teams. Step 1 was divided into four sub steps. The simulation results through the Step 1 identified the parameters for simulation of the Step 2. Basic parameters of the materials (buffer material, backfill material, rock mass, concrete, sand) were provided by JAEA. Special parameters which research team needed were identified by back analysis of Step 1. Most notably the mechanical behaviour of swelling and displacement depended on the applied model (elastic model or elastoplastic model). Parameters such as Young’s modulus were found to need smaller values than characterised in the fundamental laboratory test results (Step 1-1, 1-2) for the elastic model. Although laboratory experiments are usually simple, test results contained some error. For example, if the saturation level is 100 % or higher, it should be considered an error. This situation was presented in the Step 1-3. A possible reason is that the buffer material is a mixture of bentonite and silica sand. When a specimen is cut to measure volume or weight, sand grains will affect the measurement data. In Step 2, boundary conditions such as temperature on the surface of the simulated overpack, heater power of the electrical heaters installed in the simulated overpack, injection pressure and inflow rate of the test water, were applied. The outer boundary conditions can be selected using measured data (injection pressure and inflow rate of the test water that is controlled by the injection systems installed in the sand layer around the buffer material and in the boundary between backfill material and concrete support). Since such measured data has some noise, research teams developed their own simplified boundary conditions. Inner boundary conditions can be selected using measured data as heater power and temperature on the surface of the simulated overpack. These data also contain some noise, so research teams developed their own simplified developed boundary conditions. Task D validated various approaches thorough the simulation of the in-situ full scale EBS system including backfill of the gallery: variations in the coupling processes (THM or THC), analysis codes, and boundary conditions. Temperature distribution in the buffer material was simulated well by all research teams. This means thermal behaviour is not sensitive to the simulation approaches. Although the water content distribution on the outside of the buffer material was well simulated by all research teams, the simulation results differ from the measured values inside the buffer material (at the centre and inside, near the simulated overpack). The buffer material is made from tap water, but in the in-situ experiment, saline groundwater infiltrates the buffer material. Therefore, the selection of the hydraulic parameters of the buffer material greatly affects the simulation results of the re saturation behaviour of the buffer material. In the Horonobe EBS experiment, measured values suitable for validating the simulation results were not obtained near the simulated overpack. When simulating the pressure and deformation of the buffer material, the measurement data is easily affected by the installation conditions of the measurement sensors, so verifying the measurement data itself remains an issue. Mechanical simulation results differ depending on whether they are considered as elastic or elastoplastic phenomena. The accuracy of measured in-situ data can be assessed by detailed analysis comparing sampling specimen analysis and measured data. The Horonobe EBS experiment is scheduled to be dismantled in the future (FY2026 and 2027). This detailed dismantling investigation will finally confirm the measured data.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Utah FORGE 5-2615: Laboratory Data for Insights on Hydraulic Fracture Closure and Stress Measurement
This dataset includes data from injection/fall-off experiments conducted in controlled laboratory settings. The aim is to investigate the physics governing fracture closure and the associated stress measurements during hydraulic fracturing. These time series data include flow rate, pressure, and volume measurements. These experiments were conducted as part of Utah FORGE Project 5-2615: Thermo-poromechanical Response of Fractured Rock.
15 GEOTHERMAL ENERGY↗
Experimental investigation of the influence of drainage condition on change in saturation of sheared sand
Here, this paper investigates the validity of the interpretation of results from testing saturated axisymmetric triaxial compression (ATC) sand specimens utilising three-dimensional (3D) synchrotron micro-computed tomography (SMT) to probe localised events that are completely missed or misinterpreted when analysing ATC measurements based on global standard measurements. Drained and undrained experiments were conducted at low and high back-pressures (BPs) coupled with multiple in situ 3D SMT to acquire high-resolution scans of the specimens at different axial strains. Specimens tested under low BP exhibited a large pore air volume change, which was not detected by the pump system that represents standard volume measurement. The increase in air volume caused a significant reduction in the degree of saturation leading to a possible transition from saturated to partially saturated constitutive behaviour. Undrained experiments exhibited a significant volume change contrary to the assumption of negligible volumetric strain for saturated undrained experiments. Air bubbles within the shear band for drained and undrained low-BP specimens showed opposite capillary pressure responses, increased for drained and decreased for undrained cases, due to the variation in the mechanism by which each of the two experiments predominantly counters the volume expansion within the shear band.
capillary pressure↗
High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning
Abstract. Wind turbine applications that leverage nacelle-mounted Doppler lidar are hampered by several sources of uncertainty in the lidar measurement, affecting both bias and random errors. Two problems encountered especially for nacelle-mounted lidar are solid interference due to intersection of the line of sight with solid objects behind, within, or in front of the measurement volume and spectral noise due primarily to limited photon capture. These two uncertainties, especially that due to solid interference, can be reduced with high-fidelity retrieval techniques (i.e., including both quality assurance/quality control and subsequent parameter estimation). Our work compares three such techniques, including conventional thresholding, advanced filtering, and a novel application of supervised machine learning with ensemble neural networks, based on their ability to reduce uncertainty introduced by the two observed nonideal spectral features while keeping data availability high. The approach leverages data from a field experiment involving a continuous-wave (CW) SpinnerLidar from the Technical University of Denmark (DTU) that provided scans of a wide range of flows both unwaked and waked by a field turbine. Independent measurements from an adjacent meteorological tower within the sampling volume permit experimental validation of the instantaneous velocity uncertainty remaining after retrieval that stems from solid interference and strong spectral noise, which is a validation that has not been performed previously. All three methods perform similarly for non-interfered returns, but the advanced filtering and machine learning techniques perform better when solid interference is present, which allows them to produce overall standard deviations of error between 0.2 and 0.3 m s−1, or a 1 %–22 % improvement versus the conventional thresholding technique, over the rotor height for the unwaked cases. Between the two improved techniques, the advanced filtering produces 3.5 % higher overall data availability, while the machine learning offers a faster runtime (i.e., ∼ 1 s to evaluate) that is therefore more commensurate with the requirements of real-time turbine control. The retrieval techniques are described in terms of application to CW lidar, though they are also relevant to pulsed lidar. Previous work by the authors (Brown and Herges, 2020) explored a novel attempt to quantify uncertainty in the output of a high-fidelity lidar retrieval technique using simulated lidar returns; this article provides true uncertainty quantification versus independent measurement and does so for three techniques rather than one.
47 OTHER INSTRUMENTATION↗
Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update
This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.
Aminifar, Farrokh↗
Nitrogen thermometry in an inductively coupled plasma torch using broadband nanosecond coherent anti-Stokes Raman scattering
The development of atmospheric hypersonic flight and re-entry capabilities requires the characterization of the thermo-chemical state of representative test environments. This study demonstrates the usage of multiplex nanosecond N 2 coherent anti-Stokes Raman scattering (CARS) to measure temperatures in an atmospheric, high-temperature (>6000K), air plasma plume, generated by an inductively coupled plasma torch. These are some of the highest temperatures ever accessed via gas-phase CARS, to our knowledge. Temperatures of N 2 in the equilibrium plasma plume are determined via theoretical fits to measured CARS spectra. We discuss the practical implementation of CARS at very high temperatures, including the scaling of the N 2 CARS signal strength from 300 to 6700 K, where the expected peak signal from the high-temperature plasma torch gases is two orders of magnitude less than commonly encountered in combustion environments. An intensified CCD camera enables single-laser-shot detection at temperatures as high as 6200 K, by increasing sensitivity and providing a time gate against intense background luminosity. We also discuss the impacts of unwanted two-beam CARS contributions from outside the nominal three-beam measurement volume. We present mean axial and radial temperature profiles, as well as time-series data derived from both single-laser-shot and accumulated CARS spectra. The single-laser-shot precision is 1.7%–2.6% at temperatures of 3500 to 6200 K. The presented results pave the way for the use of CARS at very high temperatures and the measurement of spatially resolved interface processes in high-enthalpy flows.
Fries, Dan (ORCID:0000000229513294)↗
Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium
Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
60 APPLIED LIFE SCIENCES↗
Simulation of a TRISO MiniFuel irradiation experiment with data-informed uncertainty quantification
An irradiation experiment using tristructural isotropic (TRISO) fuel particles and the miniature fuel (MiniFuel) irradiation vehicle was performed in Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) to support development of the Kairos Power fluoride salt–cooled, high-temperature reactor (KP-FHR). Here, this paper describes modeling predictions of temperatures and fuel burnup for the as-built experiment. An uncertainty quantification (UQ) analysis was performed to determine the effect of TRISO particle volume and position on the temperature predictions at various fuel heat generation rates (HGRs). This UQ study utilized fuel kernel position and volume measurements previously collected using X-ray computed tomography (XCT) techniques and Monte Carlo sampling methods to generate fuel compact cases that were then analyzed using a finite element thermal model. The UQ analysis indicated that uncertainty in calculated temperatures caused by varying TRISO particle arrangement is relatively small, even at high fuel HGR. Final predictions of particle temperatures throughout the irradiation are shown to be relevant to KP-FHR normal and off-normal operating conditions and to previous TRISO irradiation experiments. The combination of XCT with UQ analyses will inform post-irradiation examination (PIE) of the irradiated fuel compacts, and these analyses can be used to develop fuel performance models for coated particle fuel forms. Both PIE of separate-effects irradiation data and enhanced fuel performance modeling support accelerated qualification of TRISO fuels for a broad range of advanced reactor applications. The novel approach demonstrated here of measuring TRISO particle configurations with XCT methods and generating representative fuel compacts for finite element modeling and UQ analysis could be leveraged by the broader particle fuel community in the development of other TRISO fuel experiments in which these variables may have a significant impact on key outcomes.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Probing the role of solids loading and mix procedure on the properties of acoustically mixed materials for additive manufacturing
We report resonant acoustic mixing has been of particular interest for use in additive manufacturing since viscous, solids-loaded materials can be difficult to mix and inhomogeneity has adverse effects on print quality. In this study, we detail a method to iterate through different formulations and mix procedures and assess mixture quality. The approach utilizes a constant pressure-driven flow test to collect statistics on flow rate through a standard geometry. This test is first applied to well mixed formulations containing particulate solids and find that the results are sensitive to viscosity produced by solids content. We then consider the formulations at various stages of mixing and find that the spread in the volume measurements is indicative of the mixing quality; poorly mixed material yields measurements with wide distributions. We believe this testing approach can be useful when screening new formulations, developing mixing processes, or for quality control.
36 MATERIALS SCIENCE↗
Compatibility of Fuel System Elastomers and Plastics with a Fast-Pyrolysis Oil (Bio-oil) at Room Temperature
Herein the compatibility of a fast-pyrolysis bio-oil with 17 elastomer and 21 plastic materials common to fuel storage, dispensing, and delivery systems was assessed by measuring volume and hardness. Diesel was used as the baseline for comparison. The elastomer and plastic specimens were exposed to the test fuels at 23 °C. The exposure times were 4 and 16 weeks for the elastomers and plastics, respectively. The elastomers (except for silicone and styrene butadiene) exhibited pronounced swelling in the bio-oil. This was especially true for the fluorocarbons and acrylonitrile rubbers. For the elastomers, a strong correlation between polarity and volume swell was observed. Compositional and structural analysis on one of the fluorocarbon materials showed that the bio-oil was less effective at extracting phthalate additives than the diesel. However, the crystallinity of a fluorocarbon was altered by the bio-oil. Unlike the elastomers, the plastic materials were less impacted by exposure to the bio-oil. This finding is attributed to their denser and more rigid molecular structures (compared to the elastomers). Notable swelling did occur in the nylons, but this swelling was attributed to water absorption rather than polarity. Comparison with previous studies showed that the observed swelling was lower for both the elastomers and the plastics. Solubility (and hence swell) increases with temperature, and because this study was conducted at 23 °C rather than 50 °C, the reduced temperature is responsible for the lower swell levels.
09 BIOMASS FUELS↗
Elucidating Gas Reduction Effects of Organosilicon Additives in Lithium-Ion Batteries
Lithium-ion batteries (LIBs) with nonaqueous liquid electrolytes are prone to gas generation at elevated voltages and temperatures, degrading battery performance and posing serious safety risks. Organosilicon (OS) additives are an emerging candidate solution for gassing problems in LIBs, but a detailed understanding of their functional mechanisms remains elusive. In this work, we present a combined computational and experimental study to elucidate the gasreducing effects of OS additives. Cell volume measurements and gas chromatography–mass spectrometry reveal that OS additives can substantially reduce gas evolution in LIBs, particularly CO 2 regardless of source. Through density functional theory calculations, we identify multiple plausible pathways for CO 2 evolution, including (1) nucleophile-induced ring-opening of ethylene carbonate (EC) and the subsequent electro-oxidation and (2) direct electro-oxidation of lithium carbonate (Li 2 CO 3 ). Correspondingly, we find that OS additives function via two primary mechanisms: (1) scavenging of nucleophiles such as superoxide (O 2 •– ), peroxide (O 2 2– ), and carbonate ion (CO 3 2– ); (2) oligomerization with ethylene carbonate oxide ion and ethylene dicarbonate ion. Moreover, we discover that OS additives possess strong lithium coordination affinity, which helps further reduce the nucleophilic reaction energies and hence increases their nucleophile-scavenging efficiency. Finally, we provide a mechanistic interpretation for the enhanced gasreduction effects observed with fluorinated OS compounds, corroborated by surface analysis results from X-ray photoelectron spectroscopy. Our study offers the first molecular-level insights into how OS additives contribute to reduced gas formation in LIBs, paving the way for improved safety and performance of LIBs.
25 ENERGY STORAGE↗
Grain size dependent high-pressure elastic properties of ultrafine micro/nanocrystalline grossular
We have performed sound velocity and unit cell volume measurements of three synthetic, ultrafine micro/nanocrystalline grossular samples up to 50 GPa using Brillouin spectroscopy and synchrotron X-ray diffraction. The samples are characterized by average grain sizes of 90 nm, 93 nm and 179 nm (hereinafter referred to as samples Gr90, Gr93, and Gr179, respectively). The experimentally determined sound velocities and elastic properties of Gr179 sample are comparable with previous measurements, but slightly higher than those of Gr90 and Gr93 under ambient conditions. However, the differences diminish with increasing pressure, and the velocity crossover eventually takes place at approximately 20–30 GPa. The X-ray diffraction peaks of the ultrafine micro/nanocrystalline grossular samples significantly broaden between 15–40 GPa, especially for Gr179. The velocity or elasticity crossover observed at pressures over 30 GPa might be explained by different grain size reduction and/or inhomogeneous strain within the individual grains for the three grossular samples, which is supported by both the pressure-induced peak broadening observed in the X-ray diffraction experiments and transmission electron microscopy observations. The elastic behavior of ultrafine micro/nanocrystalline silicates, in this case, grossular, is both grain size and pressure dependent.
36 MATERIALS SCIENCE↗