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At least 217 records · Page 12

Investigation of acoustic waves under subsurface conditions to improve the predictions of rock mechanical properties and natural fracture characteristics

Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.

Elkholy, Sherif↗

A theoretical study of solid solution strengthening in the refractory medium entropy alloy Nb 45 Ta 25 Ti 15 Hf 15

The refractory medium-entropy alloy (RMEA) Nb 45 Ta 25 Ti 15 Hf 15 exhibits exceptional tensile ductility and fracture toughness at ambient temperature, but its engineering applications are limited by a lack of high temperature strength. Using a machine-learning interatomic potential (MLIP) with near-density functional theory (DFT) accuracy, we conducted molecular dynamics (MD) and statics simulations of the behavior of dislocations with both screw and edge characters. We also analyze experimentally measured yield strengths using the Rao-Suzuki model and the Maresca-Curtin model modified to include a temperature-dependent shear modulus and a bulk modulus-dependent misfit volume, thereby uncovering the mechanisms underlying the yielding of this RMEA. Compared with the published experimental yield strength, the models parameterized by the MLIP effectively reproduce the experimental results over a wide temperature range. The models and MD simulations indicate that yielding is governed by screw dislocations, with dipole dragging as the dominant mechanism. In MD simulations, we observed a potential softening mechanism not considered by the Rao-Suzuki screw model: slow migration of interstitial jogs along the dislocation core, which could lead to the annihilation of vacancy and interstitial jog pairs by their combination.

BCC complex concentrated alloys↗

Facilitating Large‐Scale Snow Shedding from In‐Field Solar Arrays using Icephobic Surfaces with Low‐Interfacial Toughness

Abstract Large‐scale accrual of snow and ice on solar arrays in northern latitudes can cause significant power generation losses during winter. Depending on environmental conditions, snow can encompass a wide range in physical characteristics from dry snow (modulus ≈100 kPa and density ≈0.1 g cm −3 ) to bulk ice (modulus ≈8 GPa and density ≈0.9 g cm −3 ). This variation in snow morphology has made the development of a passive, broad‐spectrum, snow and ice‐shedding surface challenging. Here, the authors develop one of the first surfaces that simultaneously possesses both low‐interfacial strength ( τ˄ ice < 50 kPa) and toughness (Γ ice < 0.5 J m −2 ) with ice. These surfaces, fabricated via the addition of mobile polymer chains/oils to a thin polymeric coating, require extremely low detachment forces for ice, enabling its passive shedding at virtually any accretion length scale. Preliminary evidence that the new surfaces can shed different forms of snow and ice from field‐deployed solar arrays, over a range of subzero temperatures for several weeks, leading to significant increases in power generation is provided. The optically transparent surfaces are easily scalable and can be widely deployed by the solar industry in areas that see persistent snow. Other applications include automotive windshields, LIDAR covers for autonomous vehicles, and cold climate optical sensors.

Dhyani, Abhishek↗

High Pressure Brillouin Spectroscopy and X-ray Diffraction of Cerium Dioxide

Simultaneous high-pressure Brillouin spectroscopy and powder X-ray diffraction of cerium dioxide powders are presented at room temperature to a pressure of 45 GPa. Micro- and nanocrystalline powders are studied and the density, acoustic velocities and elastic moduli determined. In contrast to recent reports of anomalous compressibility and strength in nanocrystalline cerium dioxide, the acoustic velocities are found to be insensitive to grain size and enhanced strength is not observed in nanocrystalline CeO 2 . Discrepancies in the bulk moduli derived from Brillouin and powder X-ray diffraction studies suggest that the properties of CeO 2 are sensitive to the hydrostaticity of its environment. Our Brillouin data give the shear modulus, G 0 = 63 (3) GPa, and adiabatic bulk modulus, K S0 = 142 (9) GPa, which is considerably lower than the isothermal bulk modulus, K T0 ~ 230 GPa, determined by high-pressure X-ray diffraction experiments.

36 MATERIALS SCIENCE↗

Hydrogen Bonding Stiffens Peptide Amphiphile Supramolecular Filaments by Aza-Glycine Residues

Peptide amphiphiles (PAs) are a class of molecules comprised of short amino acid sequences conjugated to hydrophobic moieties that may exhibit self-assembly in water into supramolecular structures. Here, we investigate here how mechanical properties of hydrogels formed by PA supramolecular nanofibers are affected by hydrogen bond densities within their internal structure by substituting glycine for aza-glycine (azaG) residues. We found that increasing the number of PA molecules that contain azaG up to 5 mol% in PA supramolecular nanofibers increases their persistence length fivefold and decreases their diffusion coefficients as measured by fluorescence recovery after photobleaching. When these PAs are used to create hydrogels, their bulk storage modulus (G') was found to increase as azaG PA content in the supramolecular assemblies increases up to a value of 10 mol% and beyond this value a decrease was observed, likely due to diminished levels of nanofiber entanglement in the hydrogels as a direct result of increased supramolecular rigidity. Interestingly, we found that the bioactivity of the scaffolds toward dopaminergic neurons derived from induced pluripotent stem cells can be enhanced directly by persistence length independently of storage modulus. We hypothesize that this is due to interactions between the cells and the extracellular environment across different size scales: from filopodia adhering to individual nanofiber bundles to cell adhesion sites that interact with the hydrogel as a bulk substrate. Fine tuning of hydrogen bond density in self-assembling peptide biomaterials such as PAs provides an approach to control nanoscale stiffness as part of an overall strategy to optimize bioactivity in these supramolecular systems. supramolecular biomaterials.

36 MATERIALS SCIENCE↗

Mechanical Characterization of Loblolly Pine

Biorefineries are faced with various material flow challenges during feeding and handling, due to inherent variability and inhomogeneity of biomass feedstocks. This impacts the efficiency of refinery processes and unit operations. Proper characterization of bulk properties allows for optimal process design and reduction of overall costs. This work is aimed at evaluating the physical and mechanical properties that impact bulk flow of loblolly pine. Cyclic axial compression tests are performed to elucidate consolidation behavior under different stress conditions. The results are then used to develop correlations between material parameters (particle size, tissue type, moisture content) and Elastic Modulus of bulk samples.

09 BIOMASS FUELS↗

Direct Observation of Interfacial Mechanical Failure in Thiophosphate Solid Electrolytes with Operando X-Ray Tomography

Herein, the mechanical behaviors of Li 10 GeP 2 S 12 (LGPS) solid electrolytes during electrochemical cycling using operando X-ray tomography are investigated. It is demonstrated that the bulk mechanical decomposition of LGPS when cycled against lithium is a direct result of electrochemical reduction of the solid electrolyte at the LGPS/Li 0 interface. The reductive decomposition of LGPS during lithium plating results in the formation of low-density domains at the electrode/electrolyte interface, which impose sufficient mechanical stress on the underlying LGPS to crack the SE pellet. The critical stress developed prior to pellet fracture is significantly lower than the bulk shear modulus of LGPS, suggesting that the electrochemical instability of LGPS dramatically worsens the mechanical stability of the material near the LGPS/Li 0 interface. It is also shown that the application of a highly concentrated liquid electrolyte to the LGPS surface suppresses the reductive decomposition of LGPS, improving both the electrochemical performance and mechanical stability of the bulk LGPS solid electrolyte.

36 MATERIALS SCIENCE↗

Experimental evaluation of shear modulus scaling of dynamic strength at extreme pressures

Recent progress in the development of dynamic strength experimental platforms is allowing for unprecedented insight into the assumptions used to construct constitutive models operating in extreme conditions. In this work, we make a quantitative assessment of how tantalum strength scales with its shear modulus to pressures of hundreds of gigapascals through a cross-platform examination of three dynamic strength experiments. Specifically, we make use of Split–Hopkinson pressure bar and Richtmyer–Meshkov instability experiments to assess the low-pressure strain and strain rate dependence. Concurrent examination of magnetically driven ramp-release experiments up to pressures of 350GPa allows us to examine the pressure dependence. In this work, using a modern description of the shear modulus, validated against both ab initio theory and experimental measurements, we then assess how the experimentally measured pressure dependence scales with shear modulus. Furthermore, we find that the common assumption of scaling strength linearly with the shear modulus is too soft at high pressures and offer discussion as to how descriptions of slip mediated plasticity could result in an alternative scaling that is consistent with the data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Elastic Properties of Plasma-Exposed Tungsten Predicted by Molecular-Dynamics Simulations

We report results of systematic molecular-dynamics computations of the elastic properties of single-crystalline tungsten containing structural defects, voids and overpressurized He nanobubbles, related to plasma exposure of tungsten serving as a plasma- facing component (PFC) in nuclear fusion devices. Our computations reveal that the empty voids are centers of dilatation resulting in development of tensile stress in the tungsten matrix, whereas He-filled voids (nanobubbles) introduce compressive stress in the plasma-exposed tungsten. We find that the dependence of the elastic moduli of plasma-exposed tungsten, namely, the bulk, Young, and shear modulus, on its void fraction follows a universal exponential scaling relation. We also find that the elastic moduli of plasma-exposed tungsten soften substantially as a function of He content in the tungsten matrix, following an exponential scaling relation; this He-induced exponential softening is in addition to the softening caused in the matrix with increasing temperature. A systematic characterization of the dependence of the elastic moduli on the He bubble size reveals that He bubble growth affects significantly both the bulk modulus and the Poisson ratio of plasma-exposed tungsten, while its effect on the Young and shear moduli of the plasma-exposed material is weak. Our findings contribute directly to the development of a structure-properties database that is required for the predictive modeling of the dynamical response of PFCs in nuclear fusion devices.

36 MATERIALS SCIENCE↗

On the elastic anisotropy of the entropy-stabilized oxide (Mg, Co, Ni, Cu, Zn)O compound

Herein, we study the elastic properties of the entropy-stabilized oxide (Mg, Co, Ni, Cu, Zn)O using experimental and first principles techniques. Our measurements of the indentation modulus on grains with a wide range of crystallographic orientations of the entropy-stabilized oxide revealed a high degree of elastic isotropy at ambient conditions. First principles calculations predict mild elastic anisotropy for the paramagnetic structure, which decreases when the system is considered to be non-magnetic. When the antiferromagnetic state of CoO, CuO, and NiO is accounted for in the calculations, a slight increase in elastic anisotropy is observed, suggesting a coupling between magnetic ordering and the orientation dependent elastic properties. Furthermore, an examination of the local structure reveals that the isotropy is favored through local ionic distortions of Cu and Zn—due to their tendencies to form tenorite and wurtzite phases. The relationships between the elastic properties of the multicomponent oxide and those of its constituent binary oxides are reviewed. These insights open up new avenues for controlling isotropy for technological applications through tuning composition and structure in the entropy-stabilized oxide or the high-entropy compounds in general.

Entropy↗

Molecular dynamics simulation of the effect of cooling rate on the structure and properties of lithium disilicate glass

The effects of cooling rate on the structure and properties of lithium disilicate (LS2) glass are investigated using molecular dynamics (MD) computer simulations. The evolution of structural features such as pair distribution function, bond angle distribution, and Li coordination distribution are determined, and correlated with dynamic and static properties to elucidate the effects of cooling rate. The density, elastic moduli, and diffusion coefficient are found to be highly sensitive to cooling rate, whereas the Si pair distribution function and bond angle distribution are weakly affected by the cooling rate. Additionally, the changes of Si-O-Si bond angle and Li coordination number suggest the formation of Li cluster at lower cooling rates. Furthermore, by comparing results from other simulations and reported experiments, we confirm that the increase of cooling rate leads to an increase of conductivity and a decrease of density. Finally, at very high cooling rates, we find that all the atoms in LS2-glass do not relax simultaneously, but do so in two distinct configurations.

36 MATERIALS SCIENCE↗

Contribution of cryogenic thermal cycling to the atomic dynamics in a La-based bulk metallic glass with different initial states

Structural rejuvenation in metallic glasses (MGs) induced by cryogenic thermal cycling has been intensively studied. However, the effect of thermal cycling on the atomic dynamics in MGs is still missing. In this work, we present a systematic study on the atomic dynamics in a La-based MG affected by sub-Tg annealing and thermal cycling. We find that the thermal cycling has little effect on the atomic dynamics in both as-cast and annealed MGs although it could significantly increase the free volume and change mechanical properties of the as-cast MG sample. In contrast, both the structure and mechanical properties of the well-relaxed sample are almost unchanged by thermal cycling. Further, the increased open volume, mainly in the form of atomic vacancies, does not greatly promote the atomic dynamics in the as-cast MG sample, indicating that the free volume induced by thermal cycling is not the key factor in stimulating the β-relaxation and the boson peak in the studied MG.

36 MATERIALS SCIENCE↗

Determination of single-crystal elastic moduli of Li RE F 4 ( RE =Y, Gd, and Tb) by resonant ultrasound spectroscopy

The tetragonal fluoro-scheelite Li RE F 4 compounds (RE = rare earth) have been shown to exhibit a variety of useful optical and magnetic properties. While LiYF 4 has been widely studied, many of the fundamental thermodynamic properties of other members of this family remain unknown. Here, we report the complete elastic tensors (C ij ) of single-crystalline LiYF 4 , LiTbF 4 , and LiGdF 4 using resonant ultrasound spectroscopy and density functional theory (DFT). Here we compare the results for LiYF 4 with prior experimental results using time-of-flight ultrasound methods. This is the first report, however, of the experimental elastic tensors of LiTbF 4 and LiGdF 4 . The present results point to a softening of the elastic moduli of the Li RE F 4 system when Y is replaced by the larger ionic radius of Tb or Gd. Furthermore, we find that just 0.3% doping with Nd on the Y site also leads to a slight softening of the moduli. The variation of the elastic moduli as a function of temperature up to 216°C was also measured. A nearly linear softening of all seven independent elastic moduli was observed with increasing temperature. Phonon dispersions and phonon density of states obtained by DFT support the experimental finding of a significantly higher sound velocity due to lighter Y atoms in LiYF 4 , as compared to heavier LiTbF 4 and LiGdF 4 .

36 MATERIALS SCIENCE↗

Exploring the hardness and high-pressure behavior of osmium and ruthenium-doped rhenium diboride solid solutions

Rhenium diboride (ReB 2 ) exhibits high differential strain due to its puckered boron sheets that impede shear deformation. Here, we demonstrate the use of solid solution formation to enhance the Vickers hardness and differential strain of ReB 2 . ReB 2 -structured solid solutions (Re 0.98 Os 0.02 B 2 and Re 0.98 Ru 0.02 B 2 , noted as “ReOsB 2 ” and “ReRuB 2 ”) were synthesized via arc-melting from the pure elements. In-situ high-pressure radial x-ray diffraction was performed in the diamond anvil cell to study the incompressibility and lattice strain of ReOsB 2 and ReRuB 2 up to ~56 GPa. Both solid solutions exhibit higher incompressibility and differential strain than pure ReB 2 . However, while all lattice planes are strengthened by doping osmium (Os) into the ReB 2 structure, only the weakest ReB 2 lattice plane is enhanced with ruthenium (Ru). These results are in agreement with the Vickers hardness measurements of the two systems, where higher hardness was observed in ReOsB 2 . The combination of high-pressure studies with experimentally observed hardness data provides lattice specific information about the strengthening mechanisms behind the intrinsic hardness enhancement of the ReB 2 system.

36 MATERIALS SCIENCE↗

Nanolamellar phase transition in an additively manufactured eutectic high-entropy alloy under high pressures

Much is unknown about how phase transitions link to micro-/nano-structures in high-entropy systems, especially under extreme pressure and temperature conditions. This work studies the evolution of dual-phase nanolamellar eutectic high-entropy alloy phases of AlCoCrFeNi 2.1 generated by laser powder-bed fusion (L-PBF) for pressures up to 42 GPa. We compare quasi-hydrostatic high pressure synchrotron x-ray diffraction studies on L-PBF printed cylindrical samples up to 5.5 GPa (large-volume Paris–Edinburgh cell) to those carried out on an L-PBF printed foil in a diamond anvil cell where the pressure reached 42 GPa. Our results show that the initially alternating face-centered cubic (FCC) and body-centered cubic (BCC) nanolamellar structure of AlCoCrFeNi 2.1 transformed into single-phase FCC nanolamellae under high pressure with BCC–FCC phase transformation completion at 21 ± 3 GPa. Our results indicate a diffusionless BCC–FCC transformation in this additively manufactured far-from-equilibrium microstructure and demonstrate that the FCC phase is stable up to very high pressures. The measured equation of state for the FCC phase of AlCoCrFeNi 2.1 is presented up to 42 GPa and shows excellent agreement between the data obtained in large-volume press and diamond anvil cell experiments.

36 MATERIALS SCIENCE↗

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗

Using deep machine learning to interpret proton radiography data from a pulsed power experiment

Deep machine learning is used to analyze a proton radiograph from a tin pulsed power experiment and determine density values for each pixel in the image. Two promising convolutional neural network architectures that have proven to be effective for image analysis in other applications are applied to analyze a proton radiograph and find density values. The process of creating a suitable training dataset is described, involving the Lagrangian hydrodynamic model used for simulations of the experiment, the proton radiography forward model to make synthetic images for training, and the manner in which data augmentation is used to expand the resulting image dataset. It is shown that machine learning not only produces a reasonable density field but is also able to predict features in the density field that are suggested by the proton radiograph but not captured by simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗