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At least 1,333 records · Page 74

Toward quantum Monte Carlo forces on heavier ions: Scaling properties

Quantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here, we benchmark the accuracy and computational cost of QMC forces. The zero-variance zero-bias (ZVZB) force estimator is used in standard variational and diffusion Monte Carlo simulations with mean-field based trial wavefunctions and atomic pseudopotentials. Statistical force uncertainties are obtained with a recently developed regression technique for heavy tailed QMC data [P. Lopez Rios and G. J. Conduit, Phys. Rev. E 99, 063312 (2019)]. By considering selected atoms and dimers with elements ranging from H to Zn (1 ≤ Z eff ≤ 20), we assess the accuracy and the computational cost of ZVZB forces as the effective pseudopotential valence charge, Z eff , increases. We find that the costs of QMC energies and forces approximately follow simple power laws in Zeff. The force uncertainty grows more rapidly, leading to a best case cost scaling relationship of approximately Z e ff 6.5 ( 3 ) for diffusion Monte Carlo. We find that the accessible system size at fixed computational cost scales as Z e ff − 2 , insensitive to model assumptions or the use of the “space warp” variance-reduction technique. Our results predict the practical cost of obtaining forces for a range of materials, such as transition metal oxides where QMC forces have yet to be applied, and underscore the importance of further developing force variance-reduction techniques, particularly for atoms with high Z eff .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of poly[n]catenane melts

Inspired by advances in the chemical synthesis of interlocking polymer architectures, extensive molecular dynamics simulations have been conducted to study the dynamical properties of poly[n]catenanes-polymers composed entirely of interlocking rings-in the melt state. Both the degree of polymerization (number of links) and the number of beads per ring are systematically varied, and the results are compared to linear and ring polymers. Herein, a simple Rouse-like model is presented, and its analytical solution suggests a decomposition of the dynamics into "ring-like" and "linear-like" regimes at short and long times, respectively. In agreement with this picture, multiple sub-diffusive regimes are observed in the monomer mean-squared-displacements even though interchain entanglement is not prevalent in the system. However, the Rouse-type model does not account for the topological effects of the mechanical bonds, which significantly alter the dynamics at intermediate length scales both within the rings and at the chain segment scales. The stress relaxation in the system is extremely rapid and may be conveniently separated into ring-like and linear-like contributions, again in agreement with the Rouse picture. However, the viscosity has a non-monotonic dependence on the ring size for long chains, which disagrees strongly with theoretical predictions. This unexpected observation cannot be explained in terms of chain disentanglement and is inconsistent with other measures of polymer relaxation. Possible mechanisms for this behavior are proposed and implications for materials design are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composite fermion nonlinear sigma models

We study particle-hole symmetry at the integer quantum Hall plateau transition using composite fermion mean-field theory. Because this theory implicitly includes some electron-electron interactions, it also has applications to certain fractional quantum Hall plateau transitions. Previous work [P. Kumar et al., Phys. Rev. B 100, 235124 (2019)] using this approach showed that the diffusive quantum criticality of this transition is described by a nonlinear sigma model with topological θ = π term. This result, which holds for both the Dirac and Halperin, Lee, and Read composite fermion theories, signifies an emergent particle-hole (reflection) symmetry of the integer (fractional) quantum Hall transition. Here we consider the stability of this result to various particle-hole symmetry-violating perturbations. In the presence of quenched disorder that preserves particle-hole symmetry, we find that finite longitudinal conductivity at this transition requires the vanishing of a symmetry-violating composite fermion effective mass, which if present would generally lead to θ ≠ π and a corresponding violation of particle-hole symmetric electrical transport σ xy ≠ $\frac1{2}$$\frac{e^2}{h}$ . When the disorder does not preserve particle-hole symmetry, we find that θ can vary continuously within the diffusive regime. Our results call for further study of the universality of the quantum Hall plateau transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An extension of the localized artificial diffusivity method for immiscible and high density ratio flows

The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.

Artificial diffusivity↗

Buffer-layer effect on the ferromagnetism of manganite heterojunctions

Identifying and understanding interfacial magnetic structures of transition-metal oxides are of great importance not only for fundamental physics but also for potential device applications. Among them, manganite and ruthenate heterostructures have attracted considerable interest due to their intriguing interfacial properties induced by complex magnetic interactions. Here, we report the observation of dramatic buffer-layer dependence of ferromagnetism in ultrathin (L⁢a 2/3 ⁢C⁢a 1/3 )⁢Mn⁢O 3 (LCMO)-based heterostructures. Though all trilayers are nonmetallic, the SrRu⁢O 3 -buffered LCMO trilayer exhibits enhanced ferromagnetism with the Curie temperature (𝑇 C ∼ 198K) much higher than for CaRu⁢O 3 (𝑇 C ∼ 99K)- and SrTi⁢O 3 (𝑇 C ∼ 42K)-buffered counterparts, as well as the monolithic LCMO films with similar thickness. Combining atomically resolved scanning transmission electron microscopy imaging with electron energy loss spectroscopy mapping, we reveal that asymmetric interfaces exist in the SrRu⁢O 3 buffered trilayer, with one exhibiting 1 unit-cell Sr diffusion into LCMO, which is responsible for the 𝑇 C enhancement. In contrast, charge transfer, which has been proposed previously as a possible mechanism, is excluded in this study. In conclusion, our results may pave a promising road toward effective atomic control of interfacial magnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effect of Pressure and Thermal Cycling on Long-Term Oxidation in CO 2 and Supercritical CO 2

Concentrating solar power plant designers are interested in supercritical CO 2 (sCO 2 ) for the power block to achieve > 50% electrical efficiency at > 700 °C. The goal of this project was to develop a long-term (> 100 kh) lifetime model for sCO 2 compatibility using 10–15 kh laboratory exposures. Three Ni-based alloys (625, 282 and 740H) and an advanced austenitic stainless steel were evaluated here in long-term exposures at 700–800 °C using 500-h cycles in laboratory air, 0.1 MPa industrial grade (IG) CO 2 and 30 MPa supercritical IG CO 2 and using 10-h cycles in 0.1 MPa IG CO 2 and O 2 . Mass change data and quantification of the oxide scale thickness and depth of internal attack after 1000–10,000 h exposures at 750 °C indicate that these materials are compatible with the sCO 2 environments with modeling used to predict long-term behavior. Comparison of the 0.1 and 30 MPa 500-h cycle results did not show a significant effect of pressure on the reaction, and no significant internal carburization was observed under these conditions, even for the stainless steel, suggesting that chromia scales may be better C diffusion barriers than expected. For the Ni-based alloys, thermal cycling to simulate the solar duty cycle did not result in scale spallation after 15 kh in 10-h cycles or 4 kh in 1-h cycles at 750 °C. However, the stainless steel specimens formed an Fe-rich oxide after ~ 1500-h cumulative exposure time in both 1- and 10-h cycles.

36 MATERIALS SCIENCE↗

Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes

Abstract The risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.

Chang, K. W.↗

(S)TEM-EELS as an advanced characterization technique for lithium-ion batteries

Although the lithium-ion battery (LIB) has acquired commercial success as a sustainable power source, it still suffers from multiple challenges for the future applications. In order to further develop next-generation batteries, the dynamics of structure change, charge transfer, and ion diffusion occurring inside the battery need to be deeply understood by advanced characterization techniques. (Scanning) transmission electron microscopy-electron energy loss spectroscopy ((S)TEM-EELS) is an effective method for the nano-scale detection of structural and chemical information in materials. Herein, this review systematically introduces the advantages and fundamentals of (S)TEM-EELS and its unique applications in LIBs.

25 ENERGY STORAGE↗

Using convolutional neural networks to accelerate three-dimensional coherent synchrotron radiation computations

Calculating the effects of coherent synchrotron radiation (CSR) is one of the most computationally expensive tasks in accelerator physics. Here, we use convolutional neural networks (CNNs), along with a latent conditional diffusion (LCD) model, trained on physics-based simulations to speed up calculations. Specifically, we produce the 3D CSR wakefields generated by electron bunches in circular orbit in the steady-state condition. Two datasets are used for training and testing the models: wakefields generated by three-dimensional Gaussian electron distributions and wakefields from a sum of up to 25 three-dimensional Gaussian distributions. The CNNs are able to accurately produce the 3D wakefields ∼250–1000 times faster than the numerical calculations, while the LCD achieves a gain of a factor of ∼34. We also test the extrapolation and out-of-distribution generalization ability of the models. They generalize well on distributions with larger spreads than what they were trained on but struggle with smaller spreads.

43 PARTICLE ACCELERATORS↗

Multiple origins of extra electron diffractions in fcc metals

Diffuse intensities in the electron diffraction patterns of concentrated face-centered cubic solid solutions have been widely attributed to chemical short-range order, although this connection has been recently questioned. This article explores the many nonordering origins of commonly reported features using a combination of experimental electron microscopy and multislice diffraction simulations, which suggest that diffuse intensities largely represent thermal and static displacement scattering. A number of observations may reflect additional contributions from planar defects, surface terminations incommensurate with bulk periodicity, or weaker dynamical effects.

36 MATERIALS SCIENCE↗

Fast-Charging Li 4 Ti 5 O 12 Anode Driven by Light

Lithium-ion batteries with fast charging capabilities are crucial for widespread adoption of electric vehicles, as they will increase acceptance of the technology and reduce range anxiety for drivers. To achieve this, advanced fast charging technologies and alternative methods to enhance the slow electrochemical processes are desperately required. This study applied light-emitting diode (LED) photo-assisted fast charging to Li 4 Ti 5 O 12 (LTO), a large bandgap cubic spinel material, to enhance charging speed through electronic-structure coupling. UV LED-generated light irradiation on to the electrode interface boosted the ion diffusion and lithium cation addition by a factor of 1.3 during electrochemical lithiation, resulting in a 30% decrease in charging time under ambient conditions. Red LED light was not effective in accelerating the reaction as it does not provide sufficient energy. The first-principles calculations support the concept that UV illumination generates charges by overcoming the material’s bandgap and effectively reducing it through the introduction of additional titanium defect states.

25 ENERGY STORAGE↗

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

High Dose and Dose Rate 60 Co γ-Irradiation of High-Density Polyethylene

We have irradiated high-density polyethylene ribbons and cylinders to ~200 kGy at a dose rate of ~5 kGy day -1 , using a 60 Co source. The radiolytically-generated gas consists almost entirely of H 2 . Based on the time- and dose-dependence of the outgassing, we have determined the radiation- chemical yield for the evolved H 2 , as well as the diffusion coefficient of H 2 in HDPE. We find that the evolved gas yield G evolved depends on the interplay of sample geometry, experimental timescale, and the diffusion coefficient of H 2 in HDPE. When these factors facilitate completion of diffusion prior to gas quantification, such as for sub-mm-thickness ribbons, we measure a time- and dose-invariant value of G evolved = 0.0076 cm 3 std. H 2 J -1 that is in agreement with literature reports. When sample geometry and experiment timescale do not permit completion of diffusion, we measure a time- and dose-dependent value of G evolved . We have developed a model for the transient outgassing behavior of the cylinders, and fitted it to the experimental data. Based on these fits, we estimate a room-temperature diffusivity of D H 2 /HDPE ≈ 1.67 ± 0.12 x 10 -6 cm 2 s -1 for H 2 in HDPE, in good agreement with literature values. At present, the effects of dose rate and γ-photon energy on HDPE gas yield are not known and require further investigation.

36 MATERIALS SCIENCE↗

MODELLING FIBER ORIENTATION DURING ADDITIVE MANUFACTURING COMPRESSION MOLDING PROCESSES

The production of high-performance thermoplastic composites reinforced with short carbon fibers can be achieved by a novel “additive manufacturing-compression molding” technique. An advantage of such combination is two-fold: controlled fiber orientation in additive manufacturing and less void content by compression molding. In this study, a computational fluid dynamics model has been developed to predict the behavior of printed layers during fiber-reinforced thermoplastic extrusion and subsequent compression molding. The fiber orientation was modelled with a simple quadratic closure model. The interaction between the fibers is included using a rotary diffusion coefficient which becomes significant in concentrated regimes. Finally, the second order orientation tensor is coupled with the momentum equation as an anisotropic part of the stress term. The effect of processing parameters on the behavior of printed layers was investigated to determine the favorable printing scenarios. The developed numerical model enables design of high-performance composites with tunable mechanical properties.

Seta, Berin↗

Mesoscale Modeling of the Effects of Accelerated Burnup on UO2 Microstructural Evolution

Accelerating the nuclear fuel qualification process will rely on some combination of advanced modeling and simulation techniques with accelerated irradiation testing and separate effects experiments to enable the development of new fuel concepts in a shorter time frame. One of the key challenges to successfully leveraging accelerated irradiation tests will be understanding the artifacts that may be introduced with accelerated accumulation of dose and/or burnup. This work presents phase field (MARMOT) simulations of the evolution of representative 2D UO2 microstructures up to 40 MWd/kgU. Simulations were performed under both commercial light water reactor fuel conditions as well as those that would be expected for highly accelerated (~10x) burnup conditions similar to those used in the MiniFuel irradiations in Oak Ridge National Laboratory’s High Flux Isotope Reactor. The phase field model was coupled with a discrete nucleation algorithm to model re- structuring at high burnup. The effect of the different fission rates in both microstructures was investigated at two temperatures: 650?C and 800?C. The lower temperature simulations both showed an onset of restructuring at nearly 60 MWd/kgU. More extensive restructuring was obtained in the MiniFuel microstructure compared with that of the PWR fuel. At 800?C, no restructuring was obtained as a result of the thermally activated diffusion of Xe atoms and U vacancies to fission gas bubbles, which reduces the nucleation driving force. These results highlight the importance of using modeling and simulation tools to inform the environmental conditions during targeted accelerated irradiation tests to extract the most useful fuel performance data.

accelerated fuel qualification, Phase Field, Restr↗

Effects of EMIC Wave-Driven Proton Precipitation on the Ionosphere

In this report we investigate the proton precipitation caused by electromagnetic ion cyclotron (EMIC) waves and its impact on the ionosphere with the self-consistent ring current-atmosphere interactions model (RAM-SCBE) coupled with an ionospheric particle transport model Global Airglow (GLOW). The EMIC wave diffusion process causes significant precipitation of tens of keV protons, particularly in the afternoon to midnight sector. These precipitating energetic protons further impact the ionosphere-thermosphere and contribute to the ionization in the E/F regions. The integrated auroral conductance is significantly enhanced in the dusk-to-midnight sector. Although the EMIC waves do not directly interact with the ring current electrons, after the EMIC wave scattering included in the model, remarkable changes are found in the global distribution of precipitating electron flux. This means that the addition of proton precipitation driven by EMIC waves results in feedback effects on the ring current electron dynamics through the circulation system. Validation is also conducted by comparing the simulated precipitation flux and ionospheric electron density with observations.

79 ASTRONOMY AND ASTROPHYSICS↗

Self-supervised and multi-fidelity learning for extended predictive soil spectroscopy

Infrared spectroscopy is a cost-effective, non-destructive, and environmentally benign technology that is increasingly recognized as an important solution for meeting the global demand for soil data. While both near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy enable rapid estimation of soil properties, they present a significant trade-off: NIR offers superior scalability and lower operational costs, whereas MIR provides higher analytical fidelity by capturing fundamental molecular vibrations. In this study, we propose a self-supervised, multi-fidelity learning framework designed to bridge this gap. Our approach leverages large-scale MIR spectral libraries to learn a compact, transferable latent representation, into which NIR spectra are subsequently aligned for downstream prediction. The workflow consists of pretraining a latent model on a large MIR library, adapting the representation using a smaller paired NIR–MIR dataset, and evaluating generalization on an independent external test set. Across a range of chemical and physical soil properties, we found that MIR-derived embeddings improved prediction accuracy relative to baseline models that used raw MIR inputs. Predictions derived from the spectrum conversion (NIR to MIR) task did not match the performance of the original MIR spectra but were similar or superior to predictive performance of NIR-only models, suggesting the unified spectral latent space can effectively leverage the larger and more diverse MIR dataset for prediction of soil properties not well represented in current NIR libraries.

54 ENVIRONMENTAL SCIENCES↗