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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Enhancement of Ni–(Y 2 O 3 ) 0.08 (ZrO 2 ) 0.92 fuel electrode performance by infiltration of Ce 0.8 Gd 0.2 O 2–δ nanoparticles

This paper addresses the use of Ce 0.8 Gd 0.2 O 2–δ (GDC) infiltration into the Ni–(Y 2 O 3 ) 0.08 (ZrO 2 ) 0.92 (YSZ) fuel electrode of solid oxide cells (SOCs) for improving their electrochemical performance in fuel cell and electrolysis operation. Although doped ceria infiltration into Ni–YSZ has recently been shown to improve the electrode performance and stability, the mechanisms defining how GDC impacts electrochemical characteristics are not fully delineated. Furthermore, the electrochemical characteristics have not yet been determined over the full range of conditions normally encountered in fuel cell and electrolysis operation. Here we present a study of both symmetric and full cells aimed at understanding the electrochemical mechanisms of GDC-modified Ni–YSZ over a wide range of fuel compositions and temperatures. Single-step GDC infiltration at an appropriate loading substantially reduced the polarization resistance of Ni–YSZ electrodes in electrolyte-supported cells, as measured using electrochemical impedance spectroscopy (EIS) at various temperatures (600–800 °C) in a range of H 2 O–H 2 mixtures (3–90 vol% H 2 O). Fuel-electrode-supported cells had significant concentration polarization due to the thick Ni–YSZ supports. Here, a distribution of relaxation times approach is used to develop a physically-based electrochemical model; the results show that GDC reduces the reaction resistance associated with three-phase boundaries, but also appears to improve oxygen transport in the electrode. Increasing the H 2 O fraction in the H 2 –H 2 O fuel mixture reduced both the three-phase boundary resistance and the gas diffusion resistance for Ni–YSZ; with GDC infiltration, the electrode resistance showed less variation with fuel composition. GDC infiltration improved the performance of fuel-electrode-supported full cells, which yielded a maximum power density of 2.28 W cm –2 in fuel cell mode and an electrolysis current density at 1.3 V of 2.22 A cm –2 , both at 800°C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-performance Ruddlesden–Popper perovskite oxide with in situ exsolved nanoparticles for direct CO 2 electrolysis

Carbon dioxide (CO 2 ) is one of the principal greenhouse gases accountable for global warming and extreme climate changes. Electrochemically converting CO 2 into carbon monoxide (CO) is a promising approach for CO 2 utilization in achieving industrial decarbonization. High-temperature CO 2 electrolysis via solid oxide electrolysis cells (SOECs) has great potential, including high-energy efficiency, fast electrode kinetics, and competitive cost; however, this technology still has challenges associated with developing highly active, robust CO 2 electrodes for SOECs. We report novel Ruddlesden–Popper structured Pr 1.2 Sr 0.8 Mn 0.4 Fe 0.6 O 4–δ (RP-PSMF) with in situ exsolved Fe nanoparticles as the CO 2 electrode in SOECs for direct CO 2 conversion to CO. The mechanism of CO 2 electrolysis is studied by using the distribution of relaxation times method from electrochemical impedance spectroscopy. La 0.8 Sr 0.2 Ga 0.8 Mg 0.2 O 3–δ (LSGM)-electrolyte supported SOECs with the RP-PSMF cathode have achieved exceptionally high current densities of 2.90, 1.61, 0.91, and 0.48 A·cm –2 at an applied voltage of 1.5 V at 800, 750, 700, and 650 °C, respectively. Moreover, SOECs with the RP-PSMF cathode have exhibited a stable electrolysis performance for 100 h under a current cycling operation. Here, these results suggest that RP-PSMF with exsolved Fe nanoparticles is a highly promising cathode for high-temperature direct CO 2 electrolysis cells.

03 NATURAL GAS↗
DOE OSTI2024

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗
DOE OSTI2025

Amorphous zinc–molybdenum–sulfide chalcogel as a long-cycle, high-capacity electrode for lithium-ion batteries

The inherent limitations of intercalation-based electrodes in lithium-ion batteries have prompted the search for alternative materials with higher specific capacities and robust electrochemical stability. Sulfur-based electrodes, despite their high theoretical capacities (1672 mAh g −1 ), typically suffer from poor cycling performance. In this work, zinc molybdenum polysulfide (Zn x Mo 3 S 13 , 0.5 ≤ x), an amorphous semiconductor chalcogel, exhibits high specific capacity and excellent cycling stability. Synchrotron X-ray pair distribution function and extended X-ray absorption fine structure analyses reveal a short-range atomic structure comprising Mo–Mo, M–S (M = Mo, Zn), and S–S bonding motifs. The coordination environment of Mo and S closely resembles that of Mo 3 S 13 clusters, interconnected via S–S bridges and Zn 2+ cations. The Li/Zn x Mo 3 S 13 cell delivers an initial discharge capacity of 844 mAh g −1 at C/3, and retains 386.2 mAh g −1 after 1000 cycles with an average coulombic efficiency of 99.99%. The distribution of relaxation times analysis confirms the formation of a stable solid electrolyte interphase, which underpins the cell's long-term stability. In conclusion, this outstanding performance is attributed to the synergistic effects of the chalcogel's unique amorphous framework, semiconductive character, Zn-mediated polysulfide anchoring, and structural resilience, positioning Zn x Mo 3 S 13 chalcogel among the most durable pure metal sulfide cathodes reported for next-generation LIBs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigating the Impact of Temporal and Directional Traffic Distribution on Crash Frequencies

Safety Performance Functions (SPFs) are mathematical models that establish relationships between the frequency of various crash types and site-specific characteristics, serving as essential tools for traffic safety analysis and roadway design. Traditional SPFs, however, often overlook the temporal fluctuations in traffic flow (such as peak-hour surges) and directional imbalances between opposing traffic streams. These traffic patterns can exacerbate congestion, disrupt driver behavior, and create unexpected conflict points, potentially leading to increased crash frequencies and more severe accidents. In light of this gap, this study aims to explore the potential of incorporating K-factors (representing peak-hour traffic proportions) and D-factors (reflecting the imbalance of directional traffic) into the development of SPFs to assess whether these factors can effectively represent the impact of temporal and spatial traffic distribution on roadway safety. Using crash data from Pennsylvania urban-suburban collector roadways, it is found that the D-factor plays a significant role in predicting the frequency of total crashes, fatal + injury crashes, and angle crashes, with positive coefficient signs indicating that higher directional imbalances correspond to increased crash risks. Similarly, the K-factor emerges as a critical predictor for fatal + injury crashes and rear-end crashes, with negative coefficients suggesting that a more pronounced traffic peak is associated with a reduction in expected crash frequencies. These results highlight the importance of accounting for uneven traffic distribution in both time and direction when developing SPFs, offering deeper insights into crash patterns and supporting more effective safety interventions and roadway designs.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗
DOE OSTI2022

Microscopic dynamics underlying the stress relaxation of arrested soft materials

Arrested soft materials such as gels and glasses exhibit a slow stress relaxation with a broad distribution of relaxation times in response to linear mechanical perturbations. Although this macroscopic stress relaxation is an essential feature in the application of arrested systems as structural materials, consumer products, foods, and biological materials, the microscopic origins of this relaxation remain poorly understood. Here, we elucidate the microscopic dynamics underlying the stress relaxation of such arrested soft materials under both quiescent and mechanically perturbed conditions through X-ray photon correlation spectroscopy. By studying the dynamics of a model associative gel system that undergoes dynamical arrest in the absence of aging effects, we show that the mean stress relaxation time measured from linear rheometry is directly correlated to the quiescent superdiffusive dynamics of the microscopic clusters, which are governed by a buildup of internal stresses during arrest. We also show that perturbing the system via small mechanical deformations can result in large intermittent fluctuations in the form of avalanches, which give rise to a broad non-Gaussian spectrum of relaxation modes at short times that is observed in stress relaxation measurements. These findings suggest that the linear viscoelastic stress relaxation in arrested soft materials may be governed by nonlinear phenomena involving an interplay of internal stress relaxations and perturbation-induced intermittent avalanches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nonstationarity in the global terrestrial water cycle and its interlinkages in the Anthropocene

Climate change and human activities alter the global freshwater cycle, causing nonstationary processes as its distribution shifting over time, yet a comprehensive understanding of these changes remains elusive. Here, we develop a remote sensing–informed terrestrial reanalysis and assess the nonstationarity of and interconnections among global water cycle components from 2003 to 2020. We highlight 20 hotspot regions where terrestrial water storage exhibits strong nonstationarity, impacting 35% of the global population and 45% of the area covered by irrigated agriculture. Emerging long-term trends dominate the most often (48.2%), followed by seasonal shifts (32.8%) and changes in extremes (19%). Notably, in mid-latitudes, this encompasses 34% of Asia and 27% of North America. The patterns of nonstationarity and their dominant types differ across other water cycle components, including precipitation, evapotranspiration, runoff, and gross primary production. These differences also manifest uniquely across hotspot regions, illustrating the intricate ways in which each component responds to climate change and human water management. Our findings emphasize the importance of considering nonstationarity when assessing water cycle information toward the development of strategies for sustainable water resource usage, enhancing resilience to extreme events, and effectively addressing other challenges associated with climate change.

Science & Technology - Other Topics↗
DOE OSTI2021

Accelerating boundary analog of a Kerr black hole

An accelerated boundary correspondence (i.e. a flat spacetime accelerating mirror trajectory) is derived for the Kerr spacetime, with a general formula that ranges from the Schwarzschild limit (zero angular momentum) to the extreme maximal spin case (yielding asymptotic uniform acceleration). Here, the beta Bogoliubov coefficients reveal the particle spectrum is a Planck distribution at late times with temperature cooler than a Schwarzschild black hole, due to the 'spring constant' analog of angular momentum. The quantum stress tensor indicates a constant emission of energy flux at late times consistent with eternal thermal equilibrium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Don't cross the streams: caustics from fuzzy dark matter

Here we study how tidal streams from globular clusters may be used to constrain the mass of ultra-light dark matter particles, called `fuzzy' dark matter (FDM). A general feature of FDM models is the presence of ubiquitous density fluctuations in bound, virialized dark matter structures, on the scale of the de Broglie wavelength, arising from wave interference in the evolving dark matter distribution. These time-varying fluctuations can disturb the motions of stars, leading to potentially observable signatures in cold thin tidal streams in our own Galaxy. The study of this effect has been hindered by the difficulty in simulating the FDM wavefunction in Milky Way-sized systems. We present a simple method to evolve realistic wavefunctions in nearly static potentials, that should provide an accurate estimate of this granulation effect. We quantify the impact of FDM perturbations on tidal streams, and show that initially, while stream perturbations are small in amplitude, their power spectra exhibit a sharp cutoff corresponding to the de Broglie wavelength of the FDM potential fluctuations. Eventually, when stream perturbations become nonlinear, fold caustics generically arise that lead to density fluctuations with universal behavior. This erases the signature of the de Broglie wavelength in the stream density power spectrum, but we show that it will still be possible to determine the FDM mass in this regime, by considering the fluctuations in quantities like angular momenta or actions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Neoclassical toroidal viscosity torque prediction via deep learning

GPECnet is a densely connected neural network that has been trained on GPEC data, to predict the plasma stability, neoclassical toroidal viscosity (NTV) torque, and optimized 3D coil current distributions for desired NTV torque profiles. Using NTV torque, driven by non-axisymmetric field perturbations in a tokamak, can be vital in optimizing pedestal performance by controlling the rotation profile in both the core, to ensure tearing stability, and the edge, to avoid edge localized modes (ELMs). The generalized perturbed equilibrium code (GPEC) software package can be used to calculate the plasma stability to 3D perturbations and the NTV torque profile generated by applied 3D magnetic fields. These calculations, however, involve complex integrations over space and energy distributions, which takes time to compute. Initially, GPECnet has been trained solely on data representative of the quiescent H-mode (QH) scenario, in which neutral beams are often balanced and toroidal rotation is low across the plasma profile. Lastly, this work provides the foundation for active control of the rotation shear using a combination of beams and 3D fields for robust and high performance QH mode operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Improving protonic ceramic electrochemical cell performance via a dual-phase reaction-sintered bilayer electrolyte

Protonic ceramic electrochemical cells (PCCs) are promising energy conversion devices, but their fabrication remains challenging. In particular, the typical electrolytes for PCCs such as BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3−δ (7111) and BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3−δ (4411) suffer from intrinsic barium evaporation issues during high-temperature sintering. This tendency towards barium loss, combined with their highly refractory nature, leads to a tradeoff between sinterability and chemical stability. To address this tradeoff, we propose a bilayer electrolyte combining layers of 4411 and 7111 materials that is designed to enhance sinterability and conductivity through dual-phase reactive sintering. Our findings demonstrate that the bilayer structure exhibits shrinkage behavior closely matched to that of the fuel electrode substrate, with a higher shrinkage compared to a single-layer 4411 electrolyte. Utilizing this bilayer electrolyte structure, our PCCs achieve a peak power density of 637 mW∙cm −2 in fuel-cell mode and a current density of 1060 mA∙cm −2 at 1.3 V in electrolysis mode at 600 °C. Our PCCs demonstrate high Faradaic efficiency of 83% at 1.3 V and 500 °C. Hybrid distribution of relaxation times (DRT) polarization mapping further reveals that the bilayer structure reduces Ohmic and polarization resistance in both fuel-cell and electrolysis modes.

ceramic processing↗
DOE OSTI2022

Characterization of the Emissions and Crystalline Silica Content of Airborne Dust Generated from Grinding Natural and Engineered Stones

Abstract In this study, we systematically characterized the airborne dust generated from grinding engineered and natural stone products using a laboratory testing system designed and operated to collect representative respirable dust samples. Four stone samples tested included two engineered stones consisting of crystalline silica in a polyester resin matrix (formulations differed with Stones A having up to 90wt% crystalline silica and Stone B up to 50wt% crystalline silica), an engineered stone consisting of recycled glass in a cement matrix (Stone C), and a granite. Aerosol samples were collected by respirable dust samplers, total dust samplers, and a Micro-Orifice Uniform Deposit Impactor. Aerosol samples were analyzed by gravimetric analysis and x-ray diffraction to determine dust generation rates, crystalline silica generation rates, and crystalline silica content. Additionally, bulk dust settled on the floor of the testing system was analyzed for crystalline silica content. Real-time particle size distributions were measured using an Aerodynamic Particle Sizer. All stone types generated similar trimodal lognormal number-weighted particle size distributions during grinding with the most prominent mode at an aerodynamic diameter of about 2.0-2.3 μm, suggesting dust formation from grinding different stones is similar. Bulk dust from Stone C contained no crystalline silica. Bulk dust from Stone A, Stone B, and granite contained 60, 23, and 30wt% crystalline silica, respectively. In Stones A and B, the cristobalite form of crystalline silica was more plentiful than the quartz form. Only the quartz form was detected in granite. The bulk dust, respirable dust, and total dust for each stone had comparable amounts of crystalline silica, suggesting that crystalline silica content in the bulk dust could be representative of that in respirable dust generated during grinding. Granite generated more dust per unit volume of material removed than the engineered stones, which all had similar normalized dust generation rates. Stone A had the highest normalized generation rates of crystalline silica, followed by granite, Stone B, and Stone C (no crystalline silica), which likely leads to the same trend of respirable crystalline silica (RCS) exposure when working with these different stones. Manufacturing and adoption of engineered stone products with formulations such as Stone B or Stone C could potentially lower or eliminate RCS exposure risks. Combining all the effects of dust generation rate, size-dependent silica content, and respirable fraction, the highest normalized generation rate of RCS consistently occurs at 3.2-5.6 µm for all the stones containing crystalline silica. Therefore, removing particles in this size range near the generation sources should be prioritized when developing engineering control measures.

Public, Environmental & Occupational Health↗
DOE OSTI2025

Habitat-specific seasonal densities of sympatric raccoons and opossums in the southeastern United States

Raccoon and opossum densities have implications for rabies management, but estimates of seasonal densities of both species are lacking for rural nonagricultural habitats of the southeastern United States, a core portion of their geographic range. Consequently, it remains unclear whether the densities of 1 species limit the other, which is possible considering their substantial niche overlap. We carried out a mark–recapture study of raccoons and opossums in 4 rural nonagricultural habitats (bottomland hardwood forest, riparian forest, upland pine forest, and isolated wetlands) in South Carolina, United States (2020 to 2022), and combined this with previous data from the same habitats (2017 to 2019) to estimate habitat-specific spring and fall densities. Raccoon densities ranged from 5.17 ± 0.96 animals/km 2 (bottomland hardwood fall) to 1.63 ± 0.83 animals/km 2 (upland pine spring) and were on average 19% higher in fall compared to spring. Opossum densities ranged from 10.35 ± 1.98 animals/km 2 (bottomland hardwood fall) to 1.11 ± 1.55 animals/km 2 (upland pine spring) with divergent seasonal patterns among habitats. These low densities across all habitats compared to other studies are likely the result of low resource availability, consistent with other habitats that have minimal anthropogenic influence. We observed a positive association between raccoon and opossum densities across trapping grids, suggesting that raccoons do not suppress opossum densities, but that densities of both species increase with increasing resource availability. Furthermore, our results can be used to inform oral rabies vaccination efforts such as refining bait densities and timing of bait distribution in these habitats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Long-term 3D MHD simulations of black hole accretion discs formed in neutron star mergers

ABSTRACT We examine the long-term evolution of accretion tori around black hole (BH) remnants of compact object mergers involving at least one neutron star, to better understand their contribution to kilonovae and the synthesis of r-process elements. To this end, we modify the unsplit magnetohydrodynamic (MHD) solver in flash 4.5 to work in non-uniform three-dimensional spherical coordinates, enabling more efficient coverage of a large dynamic range in length scales while exploiting symmetries in the system. This modified code is used to perform BH accretion disc simulations that vary the initial magnetic field geometry and disc compactness, utilizing a physical equation of state, a neutrino leakage scheme for emission and absorption, and modelling the BH’s gravity with a pseudo-Newtonian potential. Simulations run for long enough to achieve a radiatively inefficient state in the disc. We find robust mass ejection with both poloidal and toroidal initial field geometries, and suppressed outflow at high disc compactness. With the included physics, we obtain bimodal velocity distributions that trace back to mass ejection by magnetic stresses at early times, and to thermal processes in the radiatively inefficient state at late times. The electron fraction distribution of the disc outflow is broad in all models, and the ejecta geometry follows a characteristic hourglass shape. We test the effect of removing neutrino absorption or nuclear recombination with axisymmetric models, finding ${\sim} 50{{\ \rm per\ cent}}$ less mass ejection and more neutron-rich composition without neutrino absorption, and a subdominant contribution from nuclear recombination. Tests of the MHD and neutrino leakage implementations are included.

Fahlman, Steven (ORCID:0000000348759940)↗
DOE OSTI2025

Measurement of the liquid argon scintillation pulse shape using differentiable simulation in the coherent CAPTAIN-Mills experiment

The coherent CAPTAIN-Mills (CCM) experiment is a liquid argon (LAr) light collection detector searching for MeV-scale neutrino and beyond Standard Model physics signatures. Two hundred eight-inch photomultiplier tubes instrument the seven-ton fiducial volume with 50% photocathode coverage to detect light produced by charged particles. CCM’s light-based approach reduces requirements of LAr purity, compared to other detection technologies, such that sub-MeV particles can be reliably detected without additional LAr filtration and with 𝒪⁡(1) parts per million of common contaminants. We present a measurement of LAr light production and propagation parameters, with uncertainties, obtained from a sample of MeV-scale electromagnetic events. The optimization of this high-dimensional parameter space was facilitated by a differentiable optical photon Monte Carlo simulation and detailed photomultiplier tube response characterization. This result accurately predicts the timing and spatial distribution of light due to scintillation and Cherenkov emission in the detector. This is the first description of photon propagation in LAr to include several effects, including anomalous dispersion of the index of refraction near the ultraviolet resonance, Mie scattering from impurities, and Cherenkov light production.

Cherenkov detectors↗
DOE OSTI2021

Level structure of the T z = –1 nucleus 34 Ar and its relevance for nucleosynthesis in ONe novae

The 24 Mg+ 12 C fusion reaction was used to perform a detailed γ-ray spectroscopy study of the astrophysically important nucleus 34 Ar. In particular, an experimental setup, coupling the advanced γ-ray tracking array GRETINA with the well-established Argonne fragment mass analyzer (FMA), was employed to obtain excitation energies and spin-parity assignments for excited states in 34 Ar, both above and below the proton separation energy. For the first time, an angular distribution analysis of in-beam γ rays from fusion-evaporation reactions, using a tracking array, has been performed and Coulomb energy differences of analog states in the T = 1, A = 34 mirror system, explored from 0 to 6 MeV. Lastly, we present a comprehensive discussion of the astrophysical 33 Cl(p,γ) stellar reaction rate, together with implications for the identification of nova presolar grains from sulfur isotopic abundances.

20 ≤ A ≤ 38↗
DOE OSTI2023

Adaptive autoencoder latent space tuning for more robust machine learning beyond the training set for six-dimensional phase space diagnostics of a time-varying ultrafast electron-diffraction compact accelerator

In this work, we present a general adaptive latent space tuning approach for improving the robustness of machine learning tools with respect to time variation and distribution shift. We demonstrate our approach by developing an encoder-decoder convolutional neural network-based virtual 6D phase space diagnostic of charged particle beams in the HiRES ultrafast electron diffraction (UED) compact particle accelerator with uncertainty quantification. Our method utilizes model-independent adaptive feedback to tune a low dimensional 2D latent space representation of ~1 million dimensional objects which are the 15 unique 2D projections (x, y),...,(z, p z ) of the 6D phase space (x, y, z, p x , p y , p z ) of the charged particle beams. We demonstrate our method with numerical studies of short electron bunches utilizing experimentally measured UED input beam distributions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Role of Local Structure in the Enhanced Dynamics of Deformed Glasses

External stress can accelerate molecular mobility of amorphous solids by several orders of magnitude. The changes in mobility are commonly interpreted through the Eyring model, which invokes an empirical activation volume. Here, we analyze constant-stress molecular dynamics simulations and propose a structure-dependent Eyring model, connecting activation volume to a machine-learned field, softness. We show that stress has a heterogeneous effect on the mobility that depends on local structure through softness. The barrier impeding relaxation reduces more for well-packed particles, which explains the narrower distribution of relaxation time observed under stress.

74 ATOMIC AND MOLECULAR PHYSICS↗