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At least 181 records · Page 10

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗

Nonlinear dynamics, avalanches, and noise for driven Wigner crystals

Here we consider the driven dynamics of Wigner crystals interacting with random disorder. Using numerical simulations, we find a rich variety of transport phenomena as a function of charge density, drive, and pinning strength. For weak pinning, the system forms a defect-free crystal that depins elastically. When the pinning is stronger, a pinned glass phase appears that depins into a filamentary flow state, transitions at higher drives into a disordered flow phase, and finally forms a moving smectic. Within the filamentary flow phase, the conduction curves can show switching dynamics as well as negative differential conductivity in which switching events cause some flow channels to be blocked. The velocity noise in the filamentary flow regime exhibits narrow band characteristics due to the one-dimensional nature of the motion, while the moving smectic has narrow band velocity noise with a washboard frequency. In the disordered flow state, the noise power reaches a peak value and the noise has a 1/$\mathcal{f}$ character. Our transport results are consistent with recent experimental transport studies in systems where Wigner crystal states are believed to be occurring. Below the conduction threshold, we find that avalanches with a power-law size distribution appear when there are sudden local rearrangements of charges from one pinned configuration to another.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fatigue performance of laser powder bed fusion hydride-dehydride Ti-6Al-4V powder

We report hydride-dehydride (HDH) Ti-6Al-4V alloy with particle size distribution of 50–120 µm is laser powder bed fusion (L-PBF) processed using optimum processing parameters and a near-fully dense structure with a density of 99.9 % is achieved. Microstructural observations and phase analyses indicate formation of columnar β grains with acicular α/α' phases in as-built condition. The roughness of the as-fabricated samples is significant with an average roughness of R a = 15.71 ± 3.96 µm and a root mean square roughness of R rms = 108.4 ± 24.9 µm, however, both values are reduced to R a = 0.19 ± 0.04 µm and R rms = 4.9 ± 0.6 µm after mechanical grinding. Mechanical tests are carried out on as-fabricated specimens followed by stress relief treatment. All samples are tested to failure in fatigue, under fully-reversed tension-compression conditions of R = –1. The as-built samples failed from the surface with crack initiation mainly at micro-notches, whereas after mechanically grinding, crack initiation changed to subsurface defects such as pores. Minimizing surface roughness by mechanically grinding eliminates surface micro-notches which improves fatigue strength in the high cycle fatigue region. Fatigue notch factor calculations showed that the effect of surface roughness was significantly lower when HDH powder is used compared to standard spherical powder. X-ray diffraction analysis revealed an in-plane compressive stress, micro-strain and grain refinement on the surface of the mechanically ground samples. Fractography observations (macroscale) revealed a fully brittle fracture in the first stage of crack growth with a transition to a dominantly ductile fracture in the third stage of crack growth. On the other hand, at the micro scale, even the brittle fracture regions showed evidence of ductile fracture within the α' martensite laths.

36 MATERIALS SCIENCE↗

Predicting electrical conductivity in Cu/Nb composites: A combined model-experiment study

The generation of high magnetic fields requires materials with high electric conductivity and good strength properties. Cu/Nb composites are considered to be good candidates for this purpose. In this work, we aim to predict, from theory, the dependence of electric conductivity on the microstructure, most notably on the layer thickness and grain sizes. We also conducted experiments to calibrate and validate our simulations. Bimetal interfaces and grain boundaries are confirmed to have the largest impact on conductivity in this composite material. In this approach, a distribution of the layer thickness is accounted for in order to better model the experimentally observed microstructure. Because layer thicknesses below the mean free path of Cu significantly degrade the conductivity, an average layer thickness larger than expected may be needed to meet conductivity requirements in order to minimize these smaller layers in the distribution. We also investigate the effect of variations in volume fraction of Nb and temperature on the material’s conductivity.

36 MATERIALS SCIENCE↗

Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles

We here investigate how the synthesis method affects the crystallite size and atomic structure of cobalt iron oxide nanoparticles. By using a simple solvothermal method, we first synthesized cobalt ferrite nanoparticles of ca. 2 and 7 nm, characterized by Transmission Electron Microscopy (TEM), Small Angle X-ray scattering (SAXS), X-ray and neutron total scattering. The smallest particle size corresponds to only a few spinel unit cells. Nevertheless, Pair Distribution Function (PDF) analysis of X-ray and neutron total scattering data shows that the atomic structure, even in the smallest nanoparticles, is well described by the spinel structure, although with significant disorder and a contraction of the unit cell parameter. These effects can be explained by the surface oxidation of the small nanoparticles, which is confirmed by X-ray near edge absorption spectroscopy (XANES). Neutron total scattering data and PDF analysis reveal a higher degree of inversion in the spinel structure of the smallest nanoparticles. Neutron total scattering data also allow magnetic PDF (mPDF) analysis, which shows that the ferrimagnetic domains correspond to ca. 80% of the crystallite size in the larger particles. A similar but less well-defined magnetic ordering was observed for the smallest nanoparticles. Finally, we used a co-precipitation synthesis method at room temperature to synthesize ferrite nanoparticles similar in size to the smallest crystallites synthesized by the solvothermal method. Structural analysis with PDF demonstrates that the ferrite nanoparticles synthesized via this method exhibit a significantly more defective structure compared to those synthesized via a solvothermal method.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Atomistic study of silicon alloying in the spallation behavior of nanocrystalline aluminum systems

Here, the effect of concentration of the alloying element silicon (Si) on the shock and spall response of aluminum (Al) is studied using classical molecular dynamics (MD) simulations. Silicon is distributed as individual grains and as grain boundaries and the dynamic response under shock is studied for an impact velocity of 1000 m/s. A general trend observed here is that the spallation is almost exclusively intergranular and limited to Al-Si interfaces. The spall strengths are observed to a) decrease with an increase in alloying of Si as grains and b) show little increase for up to 50% grain boundary segregation. An increase in grain size of the whole system showed negligible differences in spall strength, highlighting the significance of concentration of the alloying species rather than its grain size. These results provide an atomistic understanding of light-weight metallic systems under shock compression and pave the way for designing multiphase metal matrix alloys and composites for defense/armor applications.

36 MATERIALS SCIENCE↗

Mechanical and Thermophysical Properties of 3D-Printed SiC before and after Neutron Irradiation – FY21

This report presents the mechanical and thermophysical properties of 3D-printed SiC before and after neutron irradiation that have been evaluated to assess the fuel matrix material for the Transformational Challenge Reactor (TCR). The TCR fuel form consists of an additively-manufactured silicon carbide (SiC) matrix and uranium nitride tristructural isotropic (UN TRISO) fuel particles, which is manufactured through a newly developed processing route combining binderjet 3D printing, TRISO fuel particle loading, and chemical vapor infiltration (CVI). Because the fuel matrix is a primary component of the TCR core and its response to mechanical and thermal loads during operation is one of the most influential factors on the integrity of TCR core, testing and evaluation have focused on producing mechanical and thermophysical properties data for the binderjet/CVI SiC. Baseline mechanical and thermophysical properties were measured from the disk specimens printed for different and sizes orientations, which included equibiaxial flexural failure strength, elastic constants, thermal diffusivity and conductivity, density, and the coefficient of thermal expansion. Flexural failure strength datasets showed similar Weibull distributions regardless of sample variants including different orientations. The mean failure strengths of the 3D-printed SiC variants were in the range of 280–310 MPa, which are slightly lower than that of the chemical vapor deposition (CVD) SiC. Thermophysical test results showed that specific heat and thermal expansion are not sensitive to the build direction of SiC samples, while thermal conductivity is highly dependent on the build direction and can be correlated to the anisotropic character of the 3D-printed SiC. Neutron irradiation tests were carried out on the 3D-printed 6-mm diameter SiC disk specimens. Irradiation was carried to 2.3 dpa over a temperature range of 360–880°C. No significant degradation in strength was observed in SiC after irradiations in various conditions and with different orientations. Anisotropy that had been observed in the thermal conductivity of 3D-printed SiC prior to irradiation vanished after irradiation as the irradiation defect thermal resistivity accumulated in the material. Electron microscopy of the microstructure after neutron irradiation showed distinct defect morphologies in the heterogenous material, but no evidence for irradiation-induced cracking or degradation in the microstructure was observed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Inefficient Growth of Refractory Grains: Implications for Grains in the Solar Nebula

Introduction: We report the results of a sounding rocket experiment in which SiO nucleation and growth in an argon atmosphere was observed in microgravity starting from a vapor generated by evaporation of waterglass deposited on a heated Ta wire. The temperature and pressure at the point of nucleation was determined using a double wavelength Mach–Zehnder-type interferometer. The particle composition and grain size distribution were measured after payload recovery using a Transmission Electron Microscope (TEM; JEM-2100F. JEOL Ltd., Tokyo). The results were analyzed using Modified Classical Nucleation Theory (MCNT)[1]. We report a measurement of the SiO-silicate grain sticking coefficient of 0.016, indicating very inefficient grain growth from the vapor. In other words, for every 100 SiO molecules that collide with a growing grain only one to two are captured. In the only two previous studies of the growth of solid particles from the gas phase the calculated sticking coefficients were much lower. For zinc atoms colliding with zinc crystals only three out of 100,000 collisions resulted in grain growth [2]. Iron atoms colliding with growing iron particles similarly showed an efficiency of ~0.00002 [3]. For zinc, we can explain inefficient growth due to the difficulty of the colliding atom coming upon a vacancy in the growing crystal lattice before it evaporates from the grain surface. The much higher sticking coefficient of SiO molecules on silica grains is reasonable because the silica grains are highly amorphous or glassy and therefore provide a much higher defect density where SiO molecules can be captured into the grains. In the case of similar Fe experiment, the critical cluster was the dimer. In this case the forming dimer returns to the vapor phase by dissociation due to the excess energy from the formation of the Fe-Fe bond.

Joseph A Nuth↗

Influence of Cooling Channel Geometry on the Thermal Response in Silicon Nitride Plates Studied

Engine manufacturers are continually attempting to improve the performance and efficiency of internal combustion engines. Usually they raise the operating temperature or reduce the cooling air requirement for the hot section turbine components. However, the success of these attempts depends on finding materials that are lightweight, are strong, and can withstand high temperatures. Ceramics are among the top candidate materials considered for such harsh applications. They hold low-density, high-temperature strength, and thermal conductivity, and they are undergoing investigation as potential materials for replacing nickel-base alloys and superalloys that are currently used for engine hot-section components. Ceramic structures can withstand higher operating temperatures and a harsh combustion environment. In addition, their low densities relative to metals help reduce component mass. The long-term objectives of the High Temperature Propulsion Components (HOTPC) Project are to develop manufacturing technology, thermal and environmental barrier coatings (TBC/EBC), and the analytical modeling capability to predict thermomechanical stresses in minimally cooled silicon nitride turbine nozzle vanes under simulated engine conditions. Two- and three-dimensional finite element analyses with TBC were conducted at the NASA Glenn Research Center. Nondestructive evaluation was used to determine processing defects. The study included conducting preliminary parametric analytical runs of heat transfer and stress analyses under steady-state conditions to demonstrate the feasibility of using cooled Si3N4 parts for turbine applications. The influence of cooling-channel shapes (such as circular, square, and ascending-order cooling channels) on cooling efficiency and thermal stresses was investigated. Temperature distributions were generated for all cases considered under both cooling and no-cooling conditions, with air being the cooling medium. The table shows the magnitude of the maximum and minimum temperature obtained for the plates under air cooling. Each channel's cross-sectional shape delivered a different temperature; however, the two-dimensional analyses for circular and square or equal-side rectangular holes produced close results. Moreover, the model of the panel with ascending order cooling channels experienced the lowest temperature. A difference of near 260 C was found among the three cooling-hole configurations investigated. The ascending-order cooling channels arrangement showed superior performance by attaining the lowest temperature (1077 C) in comparison to the circular (1379 C) and square (1343 C) channels for the same cooling-hole size. This indicates that the panel with ascending-order cooling channels is the most suitable configuration regardless of the complexity involved in its manufacture. More details pertaining to this study are reported.

Abdul-Aziz, Ali↗

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗

Analysis of Composite Panel-Stiffener Debonding Using a Shell/3D Modeling Technique

Interlaminar fracture mechanics has proven useful for characterizing the onset of delaminations in composites and has been used successfully primarily to investigate onset in fracture toughness specimens and laboratory size coupon type specimens. Future acceptance of the methodology by industry and certification authorities, however, requires the successful demonstration of the methodology on the structural level. For this purpose, a panel was selected that is reinforced with stiffeners. Shear loading causes the panel to buckle, and the resulting out-of-plane deformations initiate skin/stiffener separation at the location of an embedded defect. A small section of the stiffener foot, web and noodle as well as the panel skin in the vicinity of the delamination front were modeled with a local 3D solid model. Across the width of the stiffener foot, the mixedmode strain energy release rates were calculated using the virtual crack closure technique. A failure index was calculated by correlating the results with a mixed-mode failure criterion of the graphite/epoxy material. Computed failure indices were compared to corresponding results where the entire web was modeled with shell elements and only a small section of the stiffener foot and panel were modeled locally with solid elements. Including the stiffener web in the local 3D solid model increased the computed failure index. Further including the noodle and transition radius in the local 3D solid model changed the local distribution across the width. The magnitude of the failure index decreased with increasing transition radius and noodle area. For the transition radii modeled, the material properties used for the noodle area had a negligible effect on the results. The results of this study are intended to be used as a guide for conducting finite element and fracture mechanics analyses of delamination and debonding in complex structures such as integrally stiffened panels.

Krueger, Ronald↗

Effects of temperature and dose rate on ion-irradiated γ-LiAlO 2 pellets

Defect accumulation and microstructural evolution during ion irradiation at elevated temperatures are governed by competing processes of defect production, driven by the dose rate, and defect recovery, controlled by diffusion, interaction, and annihilation. Here, this study investigates the effects of irradiation temperature and the dose rate on microstructural evolution, deuterium retention, and lithium volatilization in γ-LiAlO 2 pellets subjected to sequential He + and D + ion irradiation. Experiments were performed to a total fluence of 3 × 10 17 (He + + D + )/cm 2 at 623, 673, 723, and 773 K with an average He + dose rate of 7.7 × 10 −4 dpa/s, and to 2 × 10 17 (He + + D + )/cm 2 at 773 K with dose rates of 6.8 × 10 −5 , 2.9 × 10 −4 , and 7.3 × 10 −4 dpa/s. At 623 K, the microstructure was dominated by cavities and fractures with no observable precipitate formation, while small precipitates emerged at 673 K. Increasing the irradiation temperature to 723–773 K promoted the formation of larger, faceted LiAl 5 O 8 precipitates, and surface amorphization, accompanied by pronounced lithium depletion and H–D isotopic exchange. At 773 K, medium and high dose rates produced an amorphized surface layer over a crystalline subsurface containing LiAl 5 O 8 precipitates and blisters at the crystalline–amorphous interface, whereas low-dose-rate irradiation preserved surface crystallinity with cavities distributed in the matrix, around precipitates, and along grain boundaries. Precipitate morphology was anisotropic with limited size dependence on the dose rate. These results elucidate the coupled effects of temperature and the dose rate and demonstrate that sequential He + and D 2 + irradiation at 773 K reproduces key microstructural features and H isotope behavior observed in neutron-irradiated γ-LiAlO 2 at 573 K.

dose rate effects↗

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗

Silicon Carbide High-Temperature Power Rectifiers Fabricated and Characterized

The High Temperature Integrated Electronics and Sensors (HTIES) team at the NASA Lewis Research Center is developing silicon carbide (SiC) for use in harsh conditions where silicon, the semiconductor used in nearly all of today's electronics, cannot function. Silicon carbide's demonstrated ability to function under extreme high-temperature, high power, and/or high-radiation conditions will enable significant improvements to a far ranging variety of applications and systems. These improvements range from improved high-voltage switching for energy savings in public electric power distribution and electric vehicles, to more powerful microwave electronics for radar and cellular communications, to sensors and controls for cleaner-burning, more fuel-efficient jet aircraft and automobile engines. In the case of jet engines, uncooled operation of 300 to 600 C SiC power actuator electronics mounted in key high-temperature areas would greatly enhance system performance and reliability. Because silicon cannot function at these elevated temperatures, the semiconductor device circuit components must be made of SiC. Lewis' HTIES group recently fabricated and characterized high-temperature SiC rectifier diodes whose record-breaking characteristics represent significant progress toward the realization of advanced high-temperature actuator control circuits. The first figure illustrates the 600 C probe-testing of a Lewis SiC pn-junction rectifier diode sitting on top of a glowing red-hot heating element. The second figure shows the current-versus voltage rectifying characteristics recorded at 600 C. At this high temperature, the diodes were able to "turn-on" to conduct 4 A of current when forward biased, and yet block the flow of current ($quot;turn-off") when reverse biases as high as 150 V were applied. This device represents a new record for semiconductor device operation, in that no previous semiconductor electronic device has ever simultaneously demonstrated 600 C functionality, and 4-A turn-on and 150-V rectification. The high operating current was achieved despite severe device size limitations imposed by present-day SiC wafer defect densities. Further substantial increases in device performance can be expected when SiC wafer defect densities decrease as SiC wafer production technology matures.

Source record↗

NASA GPM Status and Future Activities

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission is approaching a decade of operations, and continues to pursue research, dataset production, and outreach related to precipitation. Key activities over the last year were the release of an improved “Version 07” of all GPM precipitation and latent heating products, boosting the orbit of the GPM Core Observatory (GPM CO) to 435 km, and improving quality control on precipitation retrievals from the GPM constellation of passive microwave satellites. This presentation summarizes key improvements to the GPM products and provides some examples of the changes between Versions 06 and 07 in algorithm performance. One important operational change that affected Version 07 is that the scanning strategy for the Ka-band radar channel changed in May 2018; all products that depend on Ka were revised to accommodate this change. For example, in Version 07 the Goddard Profiling (GPROF) algorithm has implemented improvements in regions where orographic enhancement and suppression take place and where the surface is snowy/icy, and again covers radiometers reaching back to 1987. The Combined Radar Radiometer Algorithm (CORRA) now incorporates modified drop-size distribution constraints that substantially reduce bias. Revisions to the Convective-Stratiform Heating (CSH) algorithm employ new radiative transfer retrievals as well as accounting for terrain in the vertical coordinates. Each algorithm was adjusted to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM CO. The U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) was upgraded to account for distortions in the probability density function of regional precipitation rates due to weighted averaging in the Kalman filter used for “morphing” the passive microwave data. Maintaining the GPM CO orbital altitude in the the current very active solar cycle has been forcing the use of more fuel than planned and consequently shortening the forecasted life of the mission from the early 2030's to the late 2020's. It was considered vital to regain some of this lifetime to ensure overlap with the upcoming Atmosphere Observing System mission to provide crosscalibration of instruments. To accomplish this, the orbital altitude was raised from 400 to 435 km on 7-8 November 2023. Thereafter, the primary GPM CO algorithms had to be revised to account for the change in observing parameters. By meeting time this action should be complete. Recently, a screening algorithm based on auto-encoding was developed that uncovered 162 orbits (out of the many thousands of orbits across all years and all satellites) of passive microwave retrievals that had highly anomalous values. Removing these defective retrievals has improved the integrity of both the GPROF and IMERG records. However, the nature of the IMERG processing interacted sufficiently badly with the now-discovered anomalous orbits that it was necessary to completely reprocess the IMERG Final Run record, now labeled Version 07B. The presentation also considers major issues that require continued attention, including the use of machine learning algorithms and the operational challenge of swarms of “small”, perhaps short-lived satellites.

GPM↗

Effect of Helium Flux on Near-surface Helium Accumulation in Plasma-Exposed Tungsten

We report results of object kinetic Monte Carlo (OKMC) simulations aimed at understanding the effect of helium flux on the near-surface helium accumulation in plasma-facing tungsten, which is initially defect-free and has a W(100) surface orientation. These OKMC simulations are performed at 933 K for fluxes ranging from 10 22 to 4 × 10 25 He/m 2 s, with 100 eV helium atoms impinging on a W(100) surface up to a maximum fluence of 4×10 19 He/m 2 . In the near-surface region, helium clusters interact elastically with the free surface. The interaction is attractive and results in the drift of mobile helium clusters towards the surface as well as increased trap mutation rates. The associated kinetics and energetics of the above-mentioned processes obtained from molecular dynamics simulations are also considered. The OKMC simulations indicate that as the flux decreases, the retention of implanted helium decreases, and its depth distribution shifts to deeper below the surface in initially pristine tungsten. Furthermore, the fraction of retained helium diffusing into the bulk increases as well, so much so that for 10 22 He/m 2 s, almost all of the retained helium diffused into the bulk with minimal/negligible near-surface helium accumulation. At a given flux, with increasing fluence, the fraction of retained helium initially decreases and then starts to increase after reaching a minimum. The occurrence of the retention minimum shifts to higher fluences as the flux decreases. Although the near-surface helium accumulation spreads deeper into the material with decreasing flux and increasing fluence, the spread appears to saturate at depths between 80 and 100 nm. Finally, we present a detailed analysis of the influence of helium flux on the size and depth distribution of total helium and helium bubbles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Gaussian approximation potential for amorphous Si : H

Hydrogenation of amorphous silicon (a–Si : H) is critical for reducing defect densities, passivating midgap states and surfaces, and improving photoconductivity in silicon-based electro-optical devices. Modeling the atomic-scale structure of this material is critical to understanding these processes, which in turn is needed to describe c–Si/a–Si : H heterojunctions that are at the heart of modern solar cells with world-record efficiency. Density functional theory (DFT) studies achieve the required high accuracy but are limited to moderate system sizes of 100 atoms or so by their high computational cost. Simulations of amorphous materials have been hindered by this high cost because large structural models are required to capture the medium-range order that is characteristic of such materials. Empirical potential models are much faster, but their accuracy is not sufficient to correctly describe the frustrated local structure. Data-driven, machine-learned interatomic potentials have broken this impasse and have been highly successful in describing a variety of amorphous materials in their elemental phase. Here, we extend the Gaussian approximation potential (GAP) for silicon by incorporating the interaction with hydrogen, thereby significantly improving the degree of realism with which amorphous silicon can be modeled. We show that our Si : H GAP enables the simulation of hydrogenated silicon with an accuracy very close to DFT but with computational expense and run times reduced by several orders of magnitude for large structures. Here, we demonstrate the capabilities of the Si : H GAP by creating models of hydrogenated liquid and amorphous silicon and showing that their energies, forces, and stresses are in excellent agreement with DFT results, and their structure as captured by bond and angle distributions are in agreement with both DFT and experiments.

36 MATERIALS SCIENCE↗