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At least 55 records · Page 3

Interactions in misaligned layered materials

The deliberate introduction of stacking faults has been found to induce properties markedly distinct from those of perfectly stacked particles or sheets, with even minute deviations leading to significant alterations in material characteristics. In this review article, we discuss the effects of stacking faults – both linear and rotational – on surface structures influencing ion adsorption, particle–particle affinity governing crystal growth, friction, and electronic properties. In conclusion, our comprehensive overview sheds light on the multifaceted impact of stacking faults on these phenomena, offering insights that bridge multiple disciplines, and provides numerous interdisciplinary research questions, paving the way for future innovations.

36 MATERIALS SCIENCE↗

Seismic Tomography 2024

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. Finally, it remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

58 GEOSCIENCES↗

Three-dimensional seismic characterization and imaging of the Soda Lake geothermal field

Accurate characterization of subsurface geophysical properties and detection of the fault system are essential for geothermal energy exploration and production. The Soda Lake geothermal field is in western Nevada with a complex fault system. Previous seismic characterization only produced a low-resolution, smooth velocity model along with a simple, conceptual fault model. Using optimized correlation-based full-waveform inversion, wavefield-separation-based reverse-time migration, and automatic fault detection techniques, we present 3D seismic characterization for the Soda Lake geothermal field using 3D surface seismic data acquired with Vibroseis sources. Here, we obtain 3D high-resolution velocity, density, and acoustic impedance models, 3D seismic images with different grid spacings, and a high-resolution fault system. Consistency check between the constructed faults and currently active injection and production geothermal wells verifies that our seismic inversion and imaging results and detected faults are reliable. These results can provide valuable information for optimizing well placement and geothermal energy production at the Soda Lake geothermal field.

15 GEOTHERMAL ENERGY↗

Enhanced Microseismicity During Production Pumping Cessation at the San Emidio Geothermal Field (Nevada, USA) in December 2016

Abstract Tectonic activity, geothermal fluids, and microseismic events (MSEs) tend to occur in similar locations as a result of spatiotemporal changes in the subsurface stress state. To quantify this association, we analyze data from a dense seismic array deployed at the San Emidio geothermal field, Nevada for 1 week in December 2016 to coincide with a 19.45‐hr shutdown of all injection and production pumping operations. 123 MSEs were detected, of which 101 occurred during the shutdown. The spatial association of the MSEs with the production wells suggests a causal relationship between the production cessation and the MSEs. Here we performed a detailed analysis to investigate reservoir material properties, distribution of seismically activated faults, and local stress state. We determined the hypocenters, magnitudes, and focal mechanisms for the MSEs, P‐wave tomographic velocity model, and local stress tensor. The results show that most MSEs occurred near the production wells. Magnitudes fall between −2.2 and 0.0 with larger events located closer to the production wells. Most MSEs occurred within a westward‐dipping normal fault zone in the reservoir associated with anomalously low P‐wave velocity values. The focal mechanism and stress inversion results show predominantly normal faulting with the maximum horizontal stress oriented north‐south. We suggest that the MSEs during shutdown were triggered on pre‐existing, small‐scale, critically stressed fault patches in the reservoir as the pore pressure increased around the production wells when the production pumping ceased. We interpret the larger MSE magnitudes closer to the production wells as a result of higher pore pressure increase.

15 GEOTHERMAL ENERGY↗

Modulation of seismic noise near the San Jacinto fault in southern California: origin and observations of the cyclical time dependence and associated crustal properties

SUMMARY We examine the cyclic amplitude variation of seismic noise recorded by continuous three-component broad-band seismic data with durations spanning 91–713 d (2008–2011) from three different networks: Anza seismic network, IDA network and the transportable seismic array. These stations surround the San Jacinto Fault Zone (SJFZ) in southern California. We find the seismic noise amplitudes exhibit a cyclical variation between 0.3 and 7.2 Hz. The high-frequency (≥0.9 Hz) noise variations can be linked to human activity and are not a concern. Our primary interest is signals in the low frequencies (0.3–0.9 Hz), where the seismic noise is modulated by semi-diurnal tidal mode M2. These long-period (low-frequency) variations of seismic noise can be attributed to a temporal change of the ocean waves breaking at the shoreline, driven by ocean tidal loading. We focus on the M2 variation of seismic noise at f = 0.6 Hz, travelling distances of ∼92 km through the crust from offshore California to the inland Anza, California, region. Relative to the shoreline station, data from the inland stations show a phase lag of ∼ –12°, which we attribute to the cyclic change in M2 that can alter crustal seismic attenuation. We also find that for mode M2 at 0.6 Hz, the amplitude variations of the seismic quality factor (Q) depend on azimuth and varies from 0.22 per cent (southeast to northwest) to 1.28 per cent (northeast to southwest) with Q = 25 for Rayleigh waves. We propose the direction dependence of the Q variation at 0.6 Hz reflects the preferred orientation of subfaults parallel to the main faulting defined by the primarily N45°W strike of the SJFZ.

Geochemistry & Geophysics↗

Analysis of Fault Zone Resonance Modes Recorded by a Dense Seismic Array Across the San Jacinto Fault Zone at Blackburn Saddle

We present observations and modeling of spatial eigen-functions of resonating waves within fault zone waveguide, using data recorded on a dense seismic array across the San Jacinto Fault Zone (SJFZ) in southern California. The array consists of 5-Hz geophones that cross the SJFZ with ~10-30 m spacing at the Blackburn Saddle near the Hemet Stepover. Wavefield snapshots after the S wave arrival are consistent for more than 50 near-fault events, suggesting that this pattern is controlled by the fault zone structure rather than source properties. Data from example event with high signal to noise ratio shows three main frequency peaks at ~1.3 Hz, ~2.0 Hz, and ~2.8 Hz in the amplitude spectra of resonance waves averaged over stations near the fault. The data are modeled with analytical expressions for eigen-functions of resonance waves in a low-velocity layer (fault zone) between two quarter-spaces. Using a grid search-based method, we investigate the possible width of the waveguide, location within the array, and shear wave velocities of the media that fit well the resonance signal at ~1.3 Hz. The results indicate a ~300 m wide damaged fault zone layer with ~65% S wave velocity reduction compared to the host rock. The SW edge of the low-velocity zone is near the mapped fault surface trace, indicating that the damage zone is asymmetrically located at the regionally faster NE crustal block. The imaging resolution of the fault zone structure can be improved by modeling fault zone resonance modes and trapped waves together.

58 GEOSCIENCES↗

Improved creep performance of CoCrFeNi high entropy alloys by Mo addition

The CoCrFeNi family of high entropy alloys has good mechanical and corrosion properties, performing like stainless steels with low yield stresses. They could, however, benefit from hardening methods for structural and high temperature applications. Here, this work investigates the potential for the CoCrFeNi alloy to be hardened with the addition of Mo. A series of CoCrFeNiMo alloys and their CoCrFeNi counterparts were subsequently manufactured at NETL and then mechanically creep tested at 650°C. The alloys were designed to possess a range of stacking fault energies which influence the mechanical properties of the alloys via the motion of their dislocations under stress. Results show that Mo-containing variants have creep rupture lives ranging from 4000 to 8000 hours, i.e., about two orders of magnitude longer than those for Mo-free variants. The significantly improved creep performance of the Mo-containing alloys is due to a combination of solid solution strengthening and precipitation strengthening from µ-phase and carbides.

36 MATERIALS SCIENCE↗

Electronic descriptors for dislocation deformation behavior and intrinsic ductility in bcc high-entropy alloys

Controlling the balance between strength and damage tolerance in high-entropy alloys (HEAs) is central to their application as structural materials. Materials discovery efforts for HEAs are therefore impeded by an incomplete understanding of the chemical factors governing this balance. Through first-principles calculations, this study explores factors governing intrinsic ductility of a crucial subset of HEAs—those with a body-centered cubic (bcc) crystal structure. Analyses of three sets of bcc HEAs comprising nine different compositions reveal that alloy chemistry profoundly influences screw dislocation core structure, dislocation vibrational properties, and intrinsic ductility parameters derived from unstable stacking fault and surface energies. Key features in the electronic structure are identified that correlate with these properties: the fraction of occupied bonding states and bimodality of the d-orbital density of states. The findings enhance the fundamental understanding of the origins of intrinsic ductility and establish an electronic structure–based framework for computationally accelerated materials discovery and design.

36 MATERIALS SCIENCE↗

Size and Structural Control of Mechanoluminescent ZnS:Mn 2+ Nanocrystals for Optogenetic Neuromodulation

Mechanoluminescent materials hold immense potential for various transformative applications, from medical imaging and diagnostics to health monitoring and wearable displays. Conventionally produced as bulk powders or microparticles, they face significant size limitations for advanced applications, particularly in biological systems and microscale devices. Here, this work presents an approach to ZnS:Mn 2+ nanocrystal synthesis that involves self-assembly and subsequent calcination. In addition to effective size control within the nanoscale, this approach promotes the formation of abundant stacking faults, significantly enhancing piezoelectric and mechanoluminescent properties by increasing trap density and reducing trap depth. Unlike mechanoluminescent materials produced using conventional methods, these nanocrystals demonstrate strong mechanoluminescence without requiring UV pre-excitation, and the light emission persists even after mechanical stress is removed. These advantageous properties make them promising candidates for optogenetic neuromodulation, as they can effectively trigger electrical signals in neurons upon ultrasound stimulation both with and without UV pre-excitation. The persistent mechanoluminescence prolongs the duration of neuronal electrical activity, providing an extended temporal window for neuromodulation compared to conventional mechanoluminescent materials. This study provides a scalable method for producing efficient mechanoluminescent nanoparticles and reveals the crucial role of particle size and defect structures in determining their mechanoluminescent behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Damage Zone at Parkfield

Rocks are heterogeneous materials that exhibit nonlinear elastic (anelastic) behavior at scales ranging from the laboratory to Earth. In the laboratory, typical, complex relationships exist between stress and strain that include hysteresis, finite relaxation times, strain rate, and history dependence. These behaviors are linked to important characteristics such as stress, porosity, permeability, material integrity, and material failure. In this work, we adopted a “pump-probe” type experiment common in laboratory studies, using solid earth tides as the low-frequency pump and empirical Green's function as the high-frequency probe. By probing the velocity at different points in the pump cycle, we constrained important information about the strain-modulus relationship. Near the San Andreas Fault, we observed strongly nonlinear elastic behavior that characterizes the damage zone. We also constrained important aspects of hysteretic behavior that are related to damage properties and possibly pore pressure. Away from the fault, the nonlinear behavior is diminished.

58 GEOSCIENCES↗

High Throughput Computational Framework of Materials Properties for Extreme Environments

This project aims to establish a framework capable of efficiently predicting the properties of structural materials for service in harsh environments over a wide range of temperatures and over long periods of time. The approach is to develop and integrate high throughput first-principles calculations in combination with machine learning (ML) methods, perform high throughput CALPHAD (calculations of phase diagrams) modeling, and carry out finite element method (FEM) simulations. Relevant to high temperature service in fossil power system, nickel-based superalloys such as Inconel 740 and Haynes 282 as well as the associated (Ni-Cr-Co)-Al-C-Fe-Mn-Mo-Nb-Si-Ti system, were investigated. The present framework was built on the concept of phase-based property data, in which properties of individual phases are modeled as a function of internal and external independent variables. This project established an open-source infrastructure with the following capabilities: (1) High throughput implementation of first-principles calculations at finite temperatures and variable compositions using both accurate phonon calculations and the efficient Debye model for thermodynamic properties, elastic constants, diffusion coefficients, vacancy formation, stacking and twin faults, and dislocation mobility; i.e., using the developed code DFTTK; (2) Machine learning capabilities to predict the above properties so that the number of first-principles calculations can be significantly reduced; e.g., using the developed code SIPFENN; (3) High throughput CALPHAD modeling of the above properties as a function of temperature and composition using our unique capability based on ESPEI and PyCalphad; (4) New capabilities to predict the stress-strain behavior of individual phases; and (5) New models for tensile strength prediction in common FEM software with the crystal plasticity finite element simulations (CPFEM).

, Ni-based superalloys↗

Microscopic model for the stacking-fault potential and the exciton wave function in GaAs

Two-dimensional stacking fault defects embedded in a bulk crystal can provide a homogeneous trapping potential for carriers and excitons. Here we utilize state-of-the-art structural imaging cou- pled with density functional and effective-mass theory to build a microscopic model of the stacking- fault exciton. The diamagnetic shift and exciton dipole moment at different magnetic fields are calculated and compared with the experimental photoluminescence of excitons bound to a single stacking fault in GaAs. The model is used to further provide insight into the properties of excitons bound to the double-well potential formed by stacking fault pairs. This microscopic exciton model can be used as an input into models which include exciton-exciton interactions to determine the excitonic phases accessible in this system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Limits to the strain engineering of layered square-planar nickelate thin films

The layered square-planar nickelates, Nd n+1 Ni n O 2n+2 , are an appealing system to tune the electronic properties of square-planar nickelates via dimensionality; indeed, superconductivity was recently observed in Nd 6 Ni 5 O 12 thin films. Here, we investigate the role of epitaxial strain in the competing requirements for the synthesis of the n = 3 Ruddlesden-Popper compound, Nd 4 Ni 3 O 10 , and subsequent reduction to the square-planar phase, Nd 4 Ni 3 O 8 . We synthesize our highest quality Nd 4 Ni 3 O 10 films under compressive strain on LaAlO 3 (001), while Nd 4 Ni 3 O 10 on NdGaO 3 (110) exhibits tensile strain-induced rock salt faults but retains bulk-like transport properties. A high density of extended defects forms in Nd 4 Ni 3 O 10 on SrTiO 3 (001). Films reduced on LaAlO 3 become insulating and form compressive strain-induced c-axis canting defects, while Nd 4 Ni 3 O 8 films on NdGaO 3 are metallic. This work provides a pathway to the synthesis of Nd n+1 Ni n O 2n+2 thin films and sets limits on the ability to strain engineer these compounds via epitaxy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. Finally, this efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

36 MATERIALS SCIENCE↗

Active‐Source Seismic Imaging of Fault Re‐Activation and Leakage: An Injection Experiment at the Mt Terri Rock Laboratory, Switzerland

Abstract We conducted a time‐lapse seismic experiment utilizing automated active seismic source and sensor arrays to monitor a reactivated fault within the Opalinus clay formation at the Mont Terri Rock Laboratory (Switzerland), an analog caprock for geologic carbon storage. A series of six brine injections were conducted into the so‐called Main Fault to reactivate it. Seismic instrumentation in five monitoring boreholes on either side of the fault was used to continuously probe changes in P‐wave travel‐times associated with fault displacement and leakage. We performed time‐lapse travel‐time tomography on five hundred sequential data sets; this revealed a zone of decreased P‐wave velocity, up to 16 m/s, during each injection cycle, followed by a velocity increase during shut‐in. These results demonstrate varying elastic property perturbations, both spatially and temporally, along the fault plane during reactivation. We then interpreted these velocity changes in terms of fault dilation induced by pressurized fluids along the fault.

58 GEOSCIENCES↗

The influence of stacking faults on mechanical behavior of advanced materials

We report there are abundant studies on deformation mechanisms in metallic materials dominated by grain boundaries and twin boundaries. In comparison, the influence of stacking faults on deformation mechanisms of materials remains less well understood. Recent studies have shown that when the density of stacking faults increases sharply, their influence on mechanical behavior of metallic or ceramic materials becomes prominent, and in fact, dominates in some cases. This article reviews recent research progress on how nanoscale stacking faults impact the mechanical behavior of metallic and ceramic materials. We primarily focus on studies that reveal the formation of pre-existing stacking faults, their interactions with dislocations, and phase transformations during plastic deformation as evidenced by experiments and simulations. The aim of this review is to highlight the potential opportunities in using stacking faults to tailor the deformation mechanisms of advanced materials.

36 MATERIALS SCIENCE↗

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗