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At least 397 records · Page 22

The July climate and a comparison of the January and July climates simulated by the GISS general circulation model

Results are presented for a study directed to evaluate the ability of the global general circulation model of the Goddard Institute for Space Studies (GISS) in simulating seasonal differences as related to an experiment simulating the July climatology which parallels the January simulation presented by Somerville et al. (1974). The July and January simulations are compared with each other and with climatological data on seasonal changes, mainly for the Northern Hemisphere troposphere. The comparison shows that the model-generated energy cycle, distribution of winds, temperature, humidity and pressure, dynamical transports, diabatic heating, evaporation, precipitation and cloud cover are all realistic for the Northern Hemisphere troposphere in July. The model's simulation of seasonal differences is generally quite realistic since the systematic quantitative errors do not affect the simulation of relative changes, to first order. Defects that could seriously bias the model's performance in particular climate experiments are identified and discussed.

Stone, P. H.↗

Cluster dynamics modeling of irradiation growth in single crystal Zr

Irradiation growth of single-crystal Zr is modeled with a reduced set of cluster dynamics equations. Nucleation and growth of basal and prismatic dislocation loops are both accounted for in the model. Equations are developed for the time evolution of single point defects, a limited number of point defect clusters, interstitial and vacancy loop nucleation rates, as well as for the growth of vacancy loops on basal planes and interstitial loops on prismatic planes. Reduction of the usual infinite hierarchy of cluster dynamics equations to the simple set studied here is justified on the physical basis of the stability of small loops once nucleated. This simplified cluster dynamics model with a small number of adjustable parameters avoids the complexity of explicit representation of higher order point defect clusters. The model shows consistency with experimental observations of the following aspects: (1) the growth rates of Zr crystals along the a- and c-axes; (2) the onset dose for breakaway irradiation growth; (3) the saturation dislocation loop densities of vacancy and interstitial loops; (4) the effects of cold work and temperature on irradiation growth.

36 MATERIALS SCIENCE↗

Computational investigation of hydrogen-induced phonon changes in carbon fiber

Optical vibrational spectroscopy has shown promise as a noninvasive means of monitoring the mechanical properties of carbon fiber (CF), which is increasingly used for industrial and consumer purposes. However, interpretation of optical vibrational spectra for solid materials is inferential, particularly when defects are present. Because inelastic neutron scattering (INS) spectroscopy is not subject to selection rules, the full vibrational spectra can be measured. And, identifying correlations between INS features and tensile properties can assist in the interpretation of spectra from more commonly used optical vibrational spectroscopic techniques, such as Raman and infrared (IR) spectroscopy. Recent INS experiments on high-performance commercial carbon fibers showed features near 900 and 1100 cm –1 in addition to a broad feature near 3000 cm –1 that increased in intensity with decreasing tensile strength. These features were assigned to hydrogen defects. Here, we use density functional theory to simulate the INS spectra of several hydrogen defect geometries in graphite as a model for carbon fiber structure units, confirming the experimental assignment of these peaks to hydrogen modes and providing insights into the structure and lattice dynamics of the defects.

36 MATERIALS SCIENCE↗

An integrated statistical-thermodynamic model for fission gas release and swelling in nuclear fuels

Here, we propose a new model for burst fission gas release induced by microcracking in ceramic nuclear fuels such as uranium dioxide. The model stipulates that the densities of defects in the fuel material, such as microcracks and fission gas bubbles on grain boundaries, evolve in accordance with the second law of thermodynamics. Central to the model is the notion of an effective temperature, conjugate to the configurational entropy of the fuel material, and directly linked to the burnup. The model predicts that microcracking, driven by the internal stress state of the fuel material, reduces the bubble storage capacity of grain boundaries, and accounts for burst fission gas release during rapid temperature transients that simulate power transients, reactor startup, and loss-of-coolant accident conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling Carbon and Hydrocarbon Molecular Structures in EZTB

A software module that models the electronic and mechanical aspects of hydrocarbon molecules and carbon molecular structures on the basis of first principles has been written for incorporation into, and execution within, the Easy (Modular) Tight-Binding (EZTB) software infrastructure, which is summarized briefly in the immediately preceding article. Of particular interest, this module can model carbon crystals and nanotubes characterized by various coordinates and containing defects, without need to adjust parameters of the physical model. The module has been used to study the changes in electronic properties of carbon nanotubes, caused by bending of the nanotubes, for potential utility as the basis of a nonvolatile, electriccharge- free memory devices. For example, in one application of the module, it was found that an initially 50-nmlong carbon, (10,10)-chirality nanotube, which is a metallic conductor when straight, becomes a semiconductor with an energy gap of .3 meV when bent to a lateral displacement of 4 nm at the middle.

Lee, Seungwon↗

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

Simulating noise on a quantum processor: interactions between a qubit and resonant two-level system bath

Material defects fundamentally limit the coherence times of superconducting qubits, and manufacturing completely defect-free devices is not yet possible. Therefore, understanding the interactions between defects and a qubit in a real quantum processor design is essential. We build a model that incorporates the standard tunneling model, the electric field distributions in the qubit, and open quantum system dynamics, and draws from the current understanding of two-level system (TLS) theory. Specifically, we start with one million TLSs distributed on the surface of a qubit and pick the 200 systems that are most strongly coupled to the qubit. We then perform a full Lindbladian simulation that explicitly includes the coherent coupling between the qubit and the TLS bath to model the time dependent density matrix of resonant TLS defects and the qubit. We find that the 200 most strongly coupled TLSs can accurately describe the qubit energy relaxation time. This work confirms that resonant TLSs located in areas where the electric field is strong can significantly affect the qubit relaxation time, even if they are located far from the Josephson junction (JJ). Similarly, a strongly-coupled resonant TLS located in the JJ does not guarantee a reduced qubit relaxation time if a more strongly coupled TLS is far from the JJ. In addition to the coupling strengths between TLSs and the qubit, the model predicts that the geometry of the device and the TLS relaxation time play a significant role in qubit dynamics. Our work can provide guidance for future quantum processor designs with improved qubit coherence times.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Skyrmions Near Defects

We study the impact of an exchange-reducing defect on a skyrmion for a thin film of finite thickness. Attraction of the skyrmion to a defect is demonstrated in a lattice model by computing the micromagnetic energy accounting for the exchange, Dzyaloshinskii-Moriya interaction, magnetic anisotropy, and dipole-dipole coupling. The spiraling dynamics of the skyrmion towards the defect is illustrated by solving numerically the full Landau-Lifshitz-Gilbert equations on a lattice and, independently, the Thiele equation, with the two methods in agreement with each other. We find that the skyrmion deforms when approaching the defect. Here, deformation is small in the parameter space far from the phase boundary that determines stability of skyrmions. It increases dramatically near the phase boundary, leading to the transformation of the skyrmion by the defect into a snake-like magnetic domain.

36 MATERIALS SCIENCE↗

Development of an Advanced Computational Model for OMCVD of Indium Nitride

An advanced computational model is being developed to predict the formation of indium nitride (InN) film from the reaction of trimethylindium (In(CH3)3) with ammonia (NH3). The components are introduced into the reactor in the gas phase within a background of molecular nitrogen (N2). Organometallic chemical vapor deposition occurs on a heated sapphire surface. The model simulates heat and mass transport with gas and surface chemistry under steady state and pulsed conditions. The development and validation of an accurate model for the interactions between the diffusion of gas phase species and surface kinetics is essential to enable the regulation of the process in order to produce a low defect material. The validation of the model will be performed in concert with a NASA-North Carolina State University project.

Cardelino, Carlos A.↗

A mechanism-based quantitative multi-scale framework for investigating irradiation hardening of tungsten at low temperature

We present the development and validation of a mechanism-based multi-scale modeling framework to quantitatively link the irradiation defect evolution kinetics at the microscopic scale to the macroscopic yield strength and flow stress evolution of tungsten irradiated at low temperature (0.08 < T/T m < 0.18, where T m is the melting point and is equal to 3673 K). The mechanism-based strength model, proposed as the superposition of thermal softening and modified dispersed barrier hardening, is developed to understand the underlying strengthening mechanisms. The thermal softening exponent as defined in the Johnson-Cook model is obtained by fitting unirradiated yield strength at different temperatures. A set of irradiation-induced defect kinetics equations with the thermodynamics parameters derived from the atomic calculations reported in the literature is used to determine the densities and sizes of defect clusters at the meso-scale, and the predicted irradiation damage characteristics are in reasonable quantitative agreement with experimental data from literature. The effects of irradiation condition (temperature and irradiation dose) and test temperature on yield strength are quantitatively predicted and compared with experimental measurements from the literature. Here, the predicted irradiation hardening and strain hardening are compared with experimental data as model validation.

36 MATERIALS SCIENCE↗

LASSO for CALPHAD Model Selection Enables Data-Efficient Thermodynamic Modeling: An Application in Thermochemical Hydrogen Production Materials

Phenomenological CALPHAD (CALculation of PHAse Diagrams) models, widely used for multicomponent materials, often contain a considerable number of parameters and require fitting using data from a relatively small number of experimental measurements or theoretical calculations. Sometimes these parameters are introduced for the purpose of improving model fits but without clear physical justification, which leads to overparametrized models with poor generalization performance. Automated approaches for optimal model selection based on the available data therefore become critical. Here, in this work, a least absolute shrinkage and selection operator (LASSO)-based approach is developed for model selection by leveraging the linearity of the CALPHAD model with respect to its parameters to convert the model selection and fitting to a LASSO minimization problem. We demonstrate its utility for thermodynamic modeling of thermochemical hydrogen (TCH) production materials using lanthanum strontium manganite (LSM) as an example. Various TCH-relevant properties, including oxygen stoichiometry as a function of oxygen partial pressure, enthalpy of reduction, and entropy of reduction, are successfully predicted with reasonable accuracy using a minimal set of model parameters. Importantly, the model selection and fitting involve minimal human decision; it can therefore be applied to high-throughput DFT defect calculations and yield efficient workflows for TCH material modeling and optimization.

CALPHAD↗

High performance high-power textured Mn/Cu-doped PIN-PMN-PT ceramics

Piezoelectric ceramics with combinatory soft and hard characteristics are highly desired for high-power applications. However, it remains grand challenge to achieve simultaneous presence of hard (e.g. high coercive field, E c ; high mechanical quality factor, Q m ) and soft (e.g. high piezoelectric constant, d; high electromechanical coupling factor, k) piezoelectric properties in piezoelectric ceramics since the mechanism controlling the hard behavior (pinned domain walls) will significantly reduce the soft behavior. Here, we address this grand challenge and demonstrate <001> textured MnO 2 and CuO co-doped Pb(In 1/2 Nb 1/2 )O 3- Pb(Mg 1/3 Nb 2/3 )O 3- PbTiO 3 (PIN-PMN-PT) ceramics exhibiting ultrahigh combined soft and hard piezoelectric properties (d 33 = 713 pC N –1 , k 31 = 0.52, Q m ≈950, E c = 9.6 kV cm –1 , tan δ = 0.45%). The outstanding electromechanical properties are explained by considering composition/phase selection, crystallographic anisotropy and defect engineering. Phase-field model in conjunction with high resolution electron microscopy and diffraction techniques is utilized to delineate the contributions arising from intrinsic piezoelectric response, domain dynamics, and local structural heterogeneity. Furthermore, these results will have significant impact in the development of high-power transducers and actuators.

36 MATERIALS SCIENCE↗

Scale Invariance of Hot Spot Formation in TATB High Explosives

Shock-induced detonation of insensitive high explosives based on 1,3,5-triamino-2,4,6-trinitrobenzene starts with formation of hot spots at microstructural defects but has eluded atomistic modeling treatment at micron length scales. To this end, we performed multimicron scale all-atom molecular dynamics (MD) simulations of hot spots that form during the collapse of cylindrical pores with diameters between 10 and 300 nm. Our MD simulations show that hot spots formed at pores larger than 20 nm exhibit temperature fields with scale-invariant features for sizes up to at least 300 nm. Through a continuum-based grain-scale modeling framework, we span and extend beyond the size scales currently accessible to MD and find that hot spot scale invariance is a general feature that arises when the mechanical strength is insensitive to strain rate. Finally, our results demonstrate the applicability of all-atom MD to simulate the complicated dynamical evolution of micron-sized systems and bolster confidence in insights from MD simulations of materials that exhibit strength with negligible rate dependence over the relevant intervals.

36 MATERIALS SCIENCE↗

From Femtoseconds to Gigaseconds: The SolDeg Platform for the Performance Degradation Analysis of Silicon Heterojunction Solar Cells

Heterojunction Si solar cells exhibit notable performance degradation. Here, we modeled this degradation by electronic defects getting generated by thermal activation across energy barriers over time. To analyze the physics of this degradation, we developed the SolDeg platform to simulate the dynamics of electronic defect generation. First, femtosecond molecular dynamics simulations were performed to create a-Si/c-Si stacks, using the machine learning-based Gaussian approximation potential. Second, we created shocked clusters by a cluster blaster method. Third, the shocked clusters were analyzed to identify which of them supported electronic defects. Fourth, the distribution of energy barriers that control the generation of these electronic defects was determined. Fifth, an accelerated Monte Carlo method was developed to simulate the thermally activated time-dependent defect generation across the barriers. Our main conclusions are as follows. (1) The degradation of a-Si/c-Si heterojunction solar cells via defect generation is controlled by a broad distribution of energy barriers. (2) We developed the SolDeg platform to track the microscopic dynamics of defect generation across this wide barrier distribution and determined the time-dependent defect density N(t) from femtoseconds to gigaseconds, over 24 orders of magnitude in time. (3) We have shown that a stretched exponential analytical form can successfully describe the defect generation N(t) over at least 10 orders of magnitude in time. (4) We found that in relative terms, Voc degrades at a rate of 0.2%/year over the first year, slowing with advancing time. (5) We developed the time correspondence curve to calibrate and validate the accelerated testing of solar cells. We found a compellingly simple scaling relationship between accelerated and normal times t normal ∝ t accel T(accel)/T(normal) . (6) We also carried out experimental studies of defect generation in a-Si:H/c-Si stacks. We found a relatively high degradation rate at early times that slowed considerably at longer time scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-scale investigation of heterogeneous swift heavy ion tracks in stannate pyrochlore

Er 2 Sn 2 O 7 pyrochlore was irradiated with swift heavy Au ions (2.2 GeV), and the induced structural modifications were systematically examined using complementary characterization techniques including transmission electron microscopy (TEM), X-ray diffraction (XRD), and neutron total scattering with pair distribution function (PDF) analysis. Each technique probes different aspects and length scales of the transformed material regions. TEM revealed a core–shell ion track structure—an amorphous core surrounded by a disordered, anion-deficient fluorite shell—which was confirmed by XRD. Neutron total scattering, with sensitivity to the oxygen sublattice, provided relative fractions of amorphous and disordered fluorite phases and confirmed the presence of a defective pyrochlore phase, which largely maintains its structural ordering but is clearly distinct from the pristine pyrochlore matrix. This defect-rich pyrochlore phase forms a halo extending radially beyond the well-characterized core–shell track morphology observed in electron micrographs. Despite their differing long-range periodicity, the short-range structures of the amorphous, disordered, and defective pyrochlore phases are all modeled well with a weberite-type configuration. Evolution of the phase fractions with increasing ion fluence was examined to ascertain the phase-to-phase pathways that occur during primary and secondary ion impact. Furthermore, this approach extends knowledge about the multi-scale response of stannate pyrochlores to swift heavy ion irradiation in the electronic energy loss regime and improves existing track-overlap models.

36 MATERIALS SCIENCE↗

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗

The Gaussian nature of the band-edge of ZnO microcrystalline thin films

A straightforward analytical approach based on the derivative of the absorption coefficient is presented, which enables probing the nature of the band edge (BE) of ZnO microcrystalline films. The study was conducted via transmission experiments at temperatures of 77–532 K and repeated for samples annealed up to 1073 K. It was found that the derivative of the natural log of the BE absorption coefficient resulted in a Gaussian function. The Gaussian linewidth is used in the electron–phonon (e–p) interaction model to characterize the defect-state of the films. The BE of the as-grown film was found to exhibit no thermal dependence and no e–p coupling, indicative of a disordered crystal. Upon annealing and improvement of the film quality, the thermal phonons became more activated, but only above room temperature with a phonon energy of ~75 meV, while up to room temperature, the impact of phonons on the BE is insignificant. A disorder–order transition was determined to take place at an annealing temperature of ~673 K. X-ray diffraction concurs with these results. The study indicates that the prevalent defects are of structural nature due to the inherent granular morphology of the films. This defect was found to dominate the behavior of the BE even at the elevated temperature regime rather than thermal phonons.

36 MATERIALS SCIENCE↗