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At least 631 records · Page 35

A concurrent irradiation-mechanics multiscale coupling model

The vast majority of our current knowledge regarding the basic mechanisms controlling irradiation effect on mechanical properties is based almost entirely on the results of post-irradiation experiments or theoretical models. However, the concurrent effects of irradiation, mechanical stress, and thermal damage on the failure phenomena of materials and components remain largely unexplored due to its internal multiscale-multiphysics coupling nature. Here, we present here a concurrent irradiation-mechanics multiscale coupling model. The concurrent evolutions of nanoscale irradiation defect clusters, microscale dislocation configurations, and mechanical responses are well captured based on coupling cluster dynamics, discrete dislocation dynamics, and the finite element methods using an effective time marching scheme. Model predictions of defect densities and size are in general agreement with experimental observations. Irradiation hardening is shown to take place also in samples undergoing concurrent irradiation-mechanical loading, similar to samples tested post-irradiation. However, the occurrence of plastic flow localization and dislocation channel formation is not accompanied with apparent yield drop (softening) under concurrent irradiation-mechanical loading conditions, which is different from the post-irradiation case.

42 ENGINEERING↗

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗

Quantifying the effects of multiple land management practices, land cover change, and wildfire on the California landscape carbon budget with an empirical model

The effectiveness of land-based climate mitigation strategies is generally estimated on a case-by-case basis without considering interactions with other strategies or influencing factors. Here we evaluate a new, comprehensive approach that incorporates interactions among multiple management strategies, land use/cover change, wildfire, and climate, although the potential effects of climate change are not evaluated in this study. The California natural and working lands carbon and greenhouse gas model (CALAND) indicates that summing individual practice estimates of greenhouse gas impacts may underestimate emission reduction benefits in comparison with an integrated estimate. Annual per-area estimates of the potential impact of specific management practices on landscape emissions can vary based on the estimation period, which can be problematic for extrapolating such estimates over space and time. Furthermore, the actual area of implementation is a primary factor in determining potential impacts of management on landscape emissions. Nonetheless, less intensive forest management, avoided conversion to urban land, and urban forest expansion generally create the largest annual per-area reductions, while meadow restoration and forest fuel reduction and harvest practices generally create the largest increases with respect to no management. CALAND also shows that data uncertainty is too high to determine whether California land is a source or a sink of carbon emissions, but that estimating effects of management with respect to a baseline provides valid results. Important sources of this uncertainty are initial carbon density, net ecosystem carbon accumulation rates, and land use/cover change data. The appropriate choice of baseline is critical for generating valid results.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Effects of Inhomogeneities at the Back Interface of CdTe‐Based Solar Cells Using 2D Modeling

One-dimensional modeling cannot capture lateral inhomogeneities in CdTe-based devices. Here, we use 2D modeling to investigate the role of varying energetics at the back interface. We consider improvements in the back interface layer (BIL) through either reducing back surface recombination velocity (BSRV) or decreasing the downward band bending near the back interface. We show that when the BSRV is reduced, but strong downward band bending remains, there is no change in the device performance until the BSRV of 90% of the back interface is improved by the BIL. On the other hand, any coverage with a BIL that improves band bending results in device improvements. We use band bending, back interface recombination current densities, and voltage dependent current flow through the device to understand these improvements. The modeling shows that lateral flow of carriers greatly affects device performance, which is not captured in parallel diode modeling, and demonstrates improved understanding with 2D modeling.

2D modelling↗

Self-Assembly of Silica Nanoparticles at Water–Hydrocarbon Interfaces: Insights from In Operando Small-Angle X-ray Scattering Measurements and Molecular Dynamics Simulations

To achieve tunable controls on the interactions of siliceous materials in subsurface environments bearing water and hydrocarbons, it is essential to determine the influence of hydrocarbon–water interfaces on the self-assembly of the silica particles. The hydrophilic silica particle have a tendency to aggregate on the water front of the interface. Self-assembly of silica nanoparticles proceeds via the migration of these nanoparticles to the water–hydrocarbon interface followed by aggregation at the interface. Fractal-like morphologies of assembled silica nanoparticles at water–hydrocarbon interfaces are observed. Rapid assembly of the hydrophilic silica nanoparticles at water–hydrocarbon interfaces corresponds to an overall reduction in the surface tension of water–toluene and water–heptane systems. These studies demonstrate the silica aggregation that is the precursor of silica polymerization, or nucleation and growth is influenced by the presence of hydrocarbons in subsurface geologic environments. These insights were derived from in operando ultrasmall and small-angle X-ray scattering (USAXS/SAXS) measurements, cryo-scanning electron microscopy (Cryo-SEM) imaging, and classical molecular dynamics simulations. As a result, these studies are intended to inform current and future efforts aimed at tuning silica reactivity in subsurface geologic environments to enhance permeability, the design and use of silica-based proppants to enhance fractures, and the development of effective strategies to control silica-based scaling behavior in subsurface reservoirs.

42 ENGINEERING↗

An in situ ambient and cryogenic transmission electron microscopy study of the effects of temperature on dislocation behavior in CrCoNi-based high-entropy alloys with low stacking-fault energy

Temperature is known to affect deformation mechanisms in metallic alloys. As temperature decreases, the stacking-fault energy in many face-centered cubic (fcc) alloys decreases, resulting in a change of deformation mode from dislocation slip to deformation twinning. Such an impact of temperature can be more complex in compositionally heterogeneous microstructures that exhibit, for example, local concentration fluctuation such as that in multi-principal element alloys. In this work, we compare the dislocation behavior and mechanical properties of a fcc Cr 20 Mn 10 Fe 30 Co 30 Ni 10 high-entropy alloy at ambient and liquid-nitrogen temperatures. We find that a network of stacking faults is formed by uniformly extended dislocations at ambient temperatures with low stacking-fault energy, whereas at lower temperatures, uneven dissociation of dislocations becomes significant, which results in severe dislocation pile-ups together with their pronounced entanglement. Our findings indicate that as the stacking-fault energy decreases with decreasing temperature, the heterogeneity of the distribution of elements becomes more dominant in tuning the local variation of lattice resistance. As a result, the change in dislocation behavior at low temperatures strongly affects microstructural evolution and consequently leads to significantly more pronounced work hardening.

36 MATERIALS SCIENCE↗

Constraining color-charge effects of partonic energy loss with jet-axis-based inclusive jet substructure measurement

This study investigates the color-charge dependence of parton energy loss in the quark-gluon plasma (QGP) medium and the associated relative modifications of quark and gluon jet fractions compared to vacuum, using jet axis decorrelation observables. Recent CMS jet axis decorrelation measurements in PbPb collisions at 5.02 TeV are interpreted using Pythia simulations with varied quark/gluon jet compositions and emulated color-charge dependent energy loss. A template-fit procedure is employed to estimate the limits on gluon jet fractions in the published CMS data and average shift in jet momentum due to quenching for quark- and gluon-initiated jets traversing the QGP. The extracted gluon jet fractions and the estimated quark and gluon energy losses based on this study of jet axis decorrelations are found to be consistent with other model calculations based on inclusive observables. This work illustrates the use of jet substructure measurements for providing constraints on the color-charge dependence of parton energy loss and offers valuable insights for jet quenching models.

jet quenching↗

Iso-cost-performance of thermal energy storage

As thermal energy storage (TES) systems gain increasing recognition as next-generation energy storage solutions, evaluating their techno-economic performance is crucial. This perspective analyzes the cost-performance of latent heat-based TES systems and introduces the concept of iso-cost-performance—maintaining a constant cost per unit energy ($\$$/kWh) despite material degradation. Using an empirical degradation model, we show that after 1200 thermal cycles, the thermal conductivity and volumetric energy density of a paraffin-based phase change material (PCM) decreased by 36.0% and 26.1%, respectively, resulting in a 31.2% reduction in the figure of merit (FOM) and, consequently, the system cost-performance. However, by introducing thermally conductive additives to enhance effective thermal conductivity, the TES system can recover its initial FOM, achieving iso-cost-performance operation. This framework quantitatively demonstrates how degradation-mitigation strategies—such as improving thermal conductivity—can offset material degradations and maintain long-term cost-effectiveness. Beyond PCM-based TES, the proposed FOM-based approach provides a generalized pathway for cost-performance optimization across various TES technologies.

25 ENERGY STORAGE↗

Toward Stable Cycling of a Cost-Effective Cation-Disordered Rocksalt Cathode via Fluorination

The recently developed Li-excess cation-disordered rock salts (DRXs) exhibit an excellent chemical diversity for the development of alternative Co/Ni-free high-energy cathodes. Herein, the synthesis of a highly fluorinated DRX cathode, Li 1.2 Mn 0.6 Ti 0.2 O 1.8 F 0.2 , based on cost-effective and earth-abundant transition metals, via a solid-state reaction, is reported. The fluorinated DRX cathode using ammonium fluoride precursor exhibits more uniform particle size and delivers a specific discharge capacity of 233 mAh g -1 and specific energy of 754 Wh kg -1 , with 206 mAh g -1 retained after 200 cycles. Further, the combined synchrotron X-ray absorption spectroscopy and resonant inelastic X-ray scattering spectroscopy analysis reveals that the remarkable cycling performance is attributed to the high fluorination and thus enhanced Mn content, enabling the utilization of more Mn redox than the oxide analog. This study demonstrates a great promise to develop next-generation cost-effective DRX cathodes with enhanced capacity retention for high-energy Li-ion batteries.

25 ENERGY STORAGE↗

Persistence and potential of soil organic carbon in nature‐based climate solutions: A review of managed disturbances

Societal Impact Statement Implementing nature-based climate solutions is important for mitigating climate change, which is a global issue, but requires local adjustments in management practices. Using the association between soil carbon and minerals as a proxy for carbon persistence, we evaluated the effect of different management regimes on soil carbon sequestration and loss. We identified areas where management practices that increase carbon inputs should be prioritized and areas where management should focus on avoiding severe disturbances. Using this storage-potential-and-persistence framework to identify how to increase or maintain soil organic carbon storage locally will increase the effectiveness of nature-based climate solutions globally. Summary Increasing soil organic carbon storage could reduce the pace of climate change, but the longevity of this nature-based climate solution depends on the persistence of carbon in soils, not just the input rates into soils. We apply a framework for considering how soil carbon persistence—namely, via the association with minerals—sheds light on soil carbon sequestration. We review how management of disturbances, such as prescribed burning, forestry, and grazing, can change soil carbon storage, persistence, and potential. Past work demonstrated that management of disturbances can sequester soil carbon, but it remains unclear how the potential stabilization of that accrual and vulnerability to loss varies across disturbance types and geographies. We found that there is substantial geographical heterogeneity in the overlap among estimates of carbon accrual, disturbance occurrence, and potential stabilization: Fire-prone grasslands and intensively grazed rangelands occur in areas estimated to have high potential to store mineral-associated organic carbon, and studies also find that adjusted fire and grazing can promote mineral-associated organic carbon. Plantation forestry and burned area span large regions where particulate organic matter is the dominant form, and studies find that particulate organic carbon is disproportionately lost following intense wildfires and forest harvests. Thus, areas with high mineral-associated organic carbon deficits should be prioritized for practices that increase carbon inputs; whereas areas with high proportions of particulate organic carbon should be prioritized for practices that help to avoid severe disturbances. Taken together, the distribution of and changes in persistence mechanisms shed light on the durability of nature-based climate solutions.

fire↗

Persistent flat band splitting and strong selective band renormalization in a kagome magnet thin film

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary Fe m X n (X = Sn, Ge; m:n = 3:1, 3:2, 1:1) family and the rare earth RMn 6 Sn 6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the para magnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the mag netic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe d xy + d x 2 -y 2 spin majority channel reminiscent of the orbital selective correlation effects in the iron based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems.

36 MATERIALS SCIENCE↗

Machine-learning-based, online estimation of ceramic’s microstructure upon the laser spot brightness during laser sintering

The ceramic microstructure strongly influences its properties. During manufacturing, the online monitoring of microstructure is critical to ensure the desired material properties. So far, the microstructure on the relevant scale is usually characterized offline using scanning electron microscopy (SEM), which is time and cost-consuming. In this work, we demonstrate a cost-effective, machine learning (ML)-based approach to simulate the SEM micrographs in real-time from the laser spot brightness. We experimentally observed a strong correlation between the laser spot brightness and the corresponding microstructure at the exact locations. The brightness values obtained from thermal emission images and the corresponding SEM micrographs were used in the training datasets. The ML algorithm was a style-based conditional generative adversarial network (CGAN). After training, the ML model could generate high-fidelity microstructure images within 0.1 seconds based on in-situ captured brightness at the laser sintering spot. We used the average grain sizes as the metric to evaluate the accuracy of the ML-predicted micrographs. Here, the ML-predicted microstructures were in good agreement, with less than 5% in difference from the real SEM images. In conclusion, we demonstrate the cost-effective, online microstructure estimation during laser sintering with a simple setup (a camera, a regular computer, and the ML model).

08 HYDROGEN↗