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

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Extending Orbital-Optimized Density Functional Theory to L-Edge XPS and Beyond: Spin–Orbit Coupling via Nonorthogonal Quasi-Degenerate Perturbation Theory

Quantum mechanical calculations of core electron binding energies (CEBEs) are relevant to interpreting X-ray photoelectron spectroscopy (XPS). Orbital-optimized density functional theory (OO-DFT) accurately predicts K-edge CEBEs but is challenged by the presence of significant spin–orbit coupling (SOC) at L- and higher edges involving inner-shell orbitals with nonzero angular momentum. Here, to extend OO-DFT to L-edges and higher, our method utilizes scalar-relativistic, spin-restricted open-shell OO-DFT to construct a minimal, quasi-degenerate basis of core-hole states corresponding to a chosen inner-shell (e.g., ionizing all six possible 2p spin orbitals). Nonorthogonal configuration interaction (NOCI) is then used to obtain the matrix elements of the full Hamiltonian including SOC in this quasi-degenerate model space of determinants. Using a screened 1-electron SOC operator parametrized with the Dirac-Coulomb-Breit (DCB) Hamiltonian results in doublet splitting (DS) values for third row elements that are nearly in quantitative agreement with experiment. The resulting NOCI eigenvalues are shifted by the average of the (scalar) OO-DFT CEBEs to yield CEBEs (split by SOC) corrected for dynamic correlation. Comparing calculations on gas phase molecules with experimental results establishes that NO-QDPT with the SCAN functional (NO-QDPT/SCAN), using the DCB screened 1-electron SOC operator is accurate to about 0.2 eV for L-edge CEBEs of molecules containing third row atoms. However, this NO-QDPT approach becomes less accurate for fourth-row elements starting in the middle of the 3d transition metal series, with errors increasing as atomic number increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Predicting Selective Laser Printing Print Quality of Polymer Powders through Melt Flow Index

Selective Laser Sintering (SLS) uses a precisely controlled laser to fuse polymer powder to build complex 3D shapes. While SLS covers a wide application space, the processing knowledge of polymer powder is limited, restricting the number of commercial powders available. This study serves to expand the processing knowledge of polypropylene and polyethylene in parallel with a “mature” SLS feedstock, nylon, through melt flow index (MFI) characterization. Differential Scanning Calorimetry (DSC) was used to explore the sintering window of the polymers. Polyethylene and polypropylene exhibited a relatively narrow sintering window between 4 – 5 °C, whereas the sintering window of nylon was much wider, between 23 – 24 °C. This suggests that the print quality between polyethylene and polypropylene would be similar; however, X-ray computed tomography revealed a higher volume of print defects, voids, and de lamination in polyethylene than in polypropylene. MFI analysis provided additional insight into the difference in print quality, as the MFI of polyethylene was 7.16 g/10 min, 9.95 g/10 min for polypropylene, and 17.23 g/10 min for nylon. MFI is inversely correlated to melt viscosity, and a low melt viscosity is desired for proper coalescing between the layers and particles. These results suggest that MFI is a promising tool, in conjunction with traditional thermal analysis, for screening candidate powder feedstocks for SLS and optimization of print parameters for novel powders.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comparative Assessment of U-Net-Based Deep Learning Models for Segmenting Microfractures and Pore Spaces in Digital Rocks

Segmentation of high-resolution X-ray microcomputed tomography (µCT) images is crucial in digital rock physics (DRP), affecting the characterization and analysis of microscale phenomena in the porous media. The complexity of geological structures and nonideal scanning conditions pose significant challenges to conventional image segmentation approaches. Motivated by the recent increasing popularity of deep learning (DL) techniques in image processing, this work undertakes a comparative study of DL models, specifically U-Net and its variants, for segmenting multiple targets with distinguished features in digital rocks, including discrete fracture networks (DFNs), pore spaces, and solid rock. Particularly, DFNs have a smaller volumetric fraction over others, bringing in a substantial challenge of imbalanced segmentation. The primary focus is to evaluate the architecture and feature enhancement strategies of various DL models, including U-Net, attention U-Net, residual U-Net, U-Net++, and residual U-Net++. The models were designed as 2.5D, utilizing a central 2D image and its two adjacent upper and lower 2D images as input to provide a pseudo-3D context. In addition, because the ground truth of segmentation was unknown for real-world digital rocks, we created a benchmark data set following the inverse operations of segmentation. The data synthesis started from the label images (i.e., solid rock, pore spaces, and DFNs), followed by simulating partial volume blurring, adding random background noise, and introducing ring artifacts to mimic real raw X-ray µCT images. The data set, which included various rock types (i.e., sandstone and artificial data), scanning resolution, and magnitudes of noise and artifacts, was divided into training and testing data sets with a 90% and 10% ratio, respectively. Moreover, in addition to the conventional pixel-wise evaluation metrics, the physics-based metric of the lattice-Boltzmann method (LBM) simulated permeability provided more comprehensive assessments. The results demonstrated that the residual connections, nested architectures, and redesigned skip connections contribute to the model performance and give the residual U-Net++ the highest accuracy. The improvements were mainly on the boundaries and small targets, especially the DFNs, which dominate the interconnectivity and therefore affect the permeability greatly. This study also rigorously evaluated the efficiency and generalization of each model, demonstrating that the sophisticated architectures achieved excellent practicability and maintained robust performance on completely unseen data, ensuring their suitability for diverse and challenging DRP applications.

58 GEOSCIENCES↗
NASA NTRS2016

Generation of Fullspan Leading-Edge 3D Ice Shapes for Swept-Wing Aerodynamic Testing

The deleterious effect of ice accretion on aircraft is often assessed through dry-air flight and wind tunnel testing with artificial ice shapes. This paper describes a method to create fullspan swept-wing artificial ice shapes from partial span ice segments acquired in the NASA Glenn Icing Reserch Tunnel for aerodynamic wind-tunnel testing. Full-scale ice accretion segments were laser scanned from the Inboard, Midspan, and Outboard wing station models of the 65% scale Common Research Model (CRM65) aircraft configuration. These were interpolated and extrapolated using a weighted averaging method to generate fullspan ice shapes from the root to the tip of the CRM65 wing. The results showed that this interpolation method was able to preserve many of the highly three dimensional features typically found on swept-wing ice accretions. The interpolated fullspan ice shapes were then scaled to fit the leading edge of a 8.9% scale version of the CRM65 wing for aerodynamic wind-tunnel testing. Reduced fidelity versions of the fullspan ice shapes were also created where most of the local three-dimensional features were removed. The fullspan artificial ice shapes and the reduced fidelity versions were manufactured using stereolithography.

Icing↗
DOE OSTI2024

3D‐Printed Carbon Nanoneedle Electrodes for Dopamine Detection in Drosophila

In vivo electrochemistry in small brain regions or synapses requires nanoelectrodes with long straight tips for submicron scale measurements. Nanoelectrodes can be fabricated using a Nanoscribe two-photon printer, but annealed tips curl if they are long and thin. We propose a new pulling-force strategy to fabricate a straight carbon nanoneedle structure. A micron-width bridge is printed between two blocks. The annealed structure shrinks during pyrolysis, and the blocks create a pulling force to form a long, thin, and straight carbon bridge. Parameterization study and COMSOL modeling indicate changes in the block size, bridge size and length affect the pulling force and bridge shrinkage. Electrodes were printed on niobium wires, insulated with aluminum oxide, and the bridge cut with focused ion beam (FIB) to expose the nanoneedle tip. Annealed needle diameters ranged from 400 nm to 5.25 μm and length varied from 50.5 μm to 146 μm. The electrochemical properties are similar to glassy carbon, with good performance for dopamine detection with fast-scan cyclic voltammetry. Nanoelectrodes enable biological applications, such as dopamine detection in a specific Drosophila brain region. Long and thin nanoneedles are generally useful for other applications such as cellular sensing, drug delivery, or gas sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

NASA Tech Briefs, July 2012

Topics covered include: Instrument Suite for Vertical Characterization of the Ionosphere-Thermosphere System; Terahertz Radiation Heterodyne Detector Using Two-Dimensional Electron Gas in a GaN Heterostructure; Pattern Recognition Algorithm for High-Sensitivity Odorant Detection in Unknown Environments; Determining Performance Acceptability of Electrochemical Oxygen Sensors; Versatile Controller for Infrared Lamp and Heater Arrays; High-Speed Scanning Interferometer Using CMOS Image Sensor and FPGA Based on Multifrequency Phase-Tracking Detection; Ultra-Low-Power MEMS Selective Gas Sensors; Compact Receiver Front Ends for Submillimeter-Wave Applications; Dynamically Reconfigurable Systolic Array Accelerator; Blocking Losses With a Photon Counter; Motion-Capture-Enabled Software for Gestural Control of 3D Mod; Orbit Software Suite; CoNNeCT Baseband Processor Module Boot Code SoftWare (BCSW); Trajectory Software With Upper Atmosphere Model; ALSSAT Version 6.0; Employing a Grinding Technology to Assess the Microbial Density for Encapsulated Organisms; Demonstration of Minimally Machined Honeycomb Silicon Carbide Mirrors; Polyimide Aerogel Thin Films; Nanoengineered Thermal Materials Based on Carbon Nanotube Array Composites; Composite Laminate With Coefficient of Thermal Expansion Matching D263 Glass; Robust Tensioned Kevlar Suspension Design; Focal Plane Alignment Utilizing Optical CMM; Purifying, Separating, and Concentrating Cells From a Sample Low in Biomass; Virtual Ultrasound Guidance for Inexperienced Operators; Beat-to-Beat Blood Pressure Monitor; Non-Contact Conductivity Measurement for Automated Sample Processing Systems; An MSK Radar Waveform; Telescope Alignment From Sparsely Sampled Wavefront Measurements Over Pupil Subapertures; Method to Remove Particulate Matter from Dusty Gases at Low Pressures; Terahertz Quantum Cascade Laser With Efficient Coupling and Beam Profile; Measurement Via Optical Near-Nulling and Subaperture Stitching; 885-nm Pumped Ceramic Nd:YAG Master Oscillator Power Amplifier Laser System; Airborne Hyperspectral Imaging System; Heat Shield Employing Cured Thermal Protection Material Blocks Bonded in a Large-Cell Honeycomb Matrix; and Asymmetric Supercapacitor for Long-Duration Power Storage.

Source record↗
DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Harnessing on-machine metrology data for prints with a surrogate model for laser powder directed energy deposition

In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive surrogate model of the 3D printing process. By employing Dynamic Mode Decomposition with Control (DMDc), a data-driven technique, we capture the complex physics inherent in this extensive dataset. This physics-based surrogate model emphasizes thermodynamically significant quantities, enabling us to accurately predict key process outcomes. The model ingests 21 process parameters, including laser power, scan rate, and position, while providing outputs such as melt pool temperature, melt pool size, and other essential observables. Furthermore, it incorporates uncertainty quantification to provide bounds on these predictions, enhancing reliability and confidence in the results. We then deploy the surrogate model on a new, unseen part and monitor the printing process as validation of the method. Our experimental results demonstrate that the predictions align with actual measurements with high accuracy, confirming the effectiveness of our approach. Furthermore, this methodology not only facilitates real-time predictions but also operates at process-relevant speeds, establishing a basis for implementing feedback control in LP-DED.

Digital twins↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2013

Wind Retrieval Algorithms for the IWRAP and HIWRAP Airborne Doppler Radars with Applications to Hurricanes

Algorithms for the retrieval of atmospheric winds in precipitating systems from downward-pointing, conically-scanning airborne Doppler radars are presented. The focus in the paper is on two radars: the Imaging Wind and Rain Airborne Profiler(IWRAP) and the High-altitude IWRAP (HIWRAP). The IWRAP is a dual-frequency (Cand Ku band), multi-beam (incidence angles of 30 50) system that flies on the NOAAWP-3D aircraft at altitudes of 2-4 km. The HIWRAP is a dual-frequency (Ku and Kaband), dual-beam (incidence angles of 30 and 40) system that flies on the NASA Global Hawk aircraft at altitudes of 18-20 km. Retrievals of the three Cartesian wind components over the entire radar sampling volume are described, which can be determined using either a traditional least squares or variational solution procedure. The random errors in the retrievals are evaluated using both an error propagation analysis and a numerical simulation of a hurricane. These analyses show that the vertical and along-track wind errors have strong across-track dependence with values of 0.25 m s-1 at nadir to 2.0 m s-1 and 1.0 m s-1 at the swath edges, respectively. The across-track wind errors also have across-track structure and are on average, 3.0 3.5 m s-1 or 10 of the hurricane wind speed. For typical rotated figure four flight patterns through hurricanes, the zonal and meridional wind speed errors are 2 3 m s-1.Examples of measured data retrievals from IWRAP during an eyewall replacement cycle in Hurricane Isabel (2003) and from HIWRAP during the development of Tropical Storm Matthew (2010) are shown.

atmospheric winds↗
DOE OSTI2025

Extending Interfaces in 3D to Achieve Superior Nanoscale Strength in Ti/Nb Nanolaminates

Tuning the atomic-level structure of nanolaminates enables high strength, increased deformability, and the ability to absorb and mitigate damage due to varied crystalline defects, including dislocations. Here, we present the enhanced strength of Ti/Nb nanolaminates containing thick 3D interfaces (3DIs), relative to their chemically abrupt 2D counterparts. We examine the effects of crystallographic alignment and compositional gradients on mechanical behavior via experiments and phase-field-dislocation dynamics (PFDD) modeling. Mechanical testing reveals that nanolaminates containing thicker 3DIs demonstrate a 28% hardness enhancement compared with sharp-interface nanolaminates. PFDD modeling shows that the critical resolved shear stress (CRSS) increases with the 3DI thickness. Gradual compositional transitions in 3DIs were confirmed via scanning transmission electron microscopy and high-resolution transmission electron microscopy, showing sharp crystallographic transitions and a heightened interface topography. The findings establish a positive function between the 3DI thickness and mechanical robustness for hexagonal-closest-packed-containing composites, emphasizing the role of defect–interface interactions in tailoring the mechanical performance and providing a foundation for future interfacial engineering.

36 MATERIALS SCIENCE↗
NASA NTRS2012

NASA Tech Briefs, May 2012

Topics covered include: An "Inefficient Fin" Non-Dimensional Parameter to Measure Gas Temperatures Efficiently; On-Wafer Measurement of a Multi-Stage MMIC Amplifier with 10 dB of Gain at 475 GHz; Software to Control and Monitor Gas Streams; Miniaturized Laser Heterodyne Radiometer (LHR) for Measurements of Greenhouse Gases in the Atmospheric Column; Anomaly Detection in Test Equipment via Sliding Mode Observers; Absolute Position of Targets Measured Through a Chamber Window Using Lidar Metrology Systems; Goldstone Solar System Radar Waveform Generator; Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System; Iridium Interfacial Stack - IrIS; Downsampling Photodetector Array with Windowing; Optical Phase Recovery and Locking in a PPM Laser Communication Link; High-Speed Edge-Detecting Line Scan Smart Camera; Optical Communications Channel Combiner; Development of Thermal Infrared Sensor to Supplement Operational Land Imager; Amplitude-Stabilized Oscillator for a Capacitance-Probe Electrometer; Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data; Histogrammatic Method for Determining Relative Abundance of Input Gas Pulse; Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH; LEGION: Lightweight Expandable Group of Independently Operating Nodes; Real-Time Projection to Verify Plan Success During Execution; Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data; Web-Based Customizable Viewer for Mars Network Overflight Opportunities; Fabrication of a Cryogenic Terahertz Emitter for Bolometer Focal Plane Calibrations; Fabrication of an Absorber-Coupled MKID Detector; Graphene Transparent Conductive Electrodes for Next- Generation Microshutter Arrays; Method of Bonding Optical Elements with Near-Zero Displacement; Free-Mass and Interface Configurations of Hammering Mechanisms; Wavefront Compensation Segmented Mirror Sensing and Control; Long-Life, Lightweight, Multi-Roller Traction Drives for Planetary Vehicle Surface Exploration; Reliable Optical Pump Architecture for Highly Coherent Lasers Used in Space Metrology Applications; Electrochemical Ultracapacitors Using Graphitic Nanostacks; Improved Whole-Blood-Staining Device; Monitoring Location and Angular Orientation of a Pill; Molecular Technique to Reduce PCR Bias for Deeper Understanding of Microbial Diversity; Laser Ablation Electrodynamic Ion Funnel for In Situ Mass Spectrometry on Mars; High-Altitude MMIC Sounding Radiometer for the Global Hawk Unmanned Aerial Vehicle; PRTs and Their Bonding for Long-Duration, Extreme-Temperature Environments; Mid- and Long-IR Broadband Quantum Well Photodetector; 3D Display Using Conjugated Multiband Bandpass Filters; Real-Time, Non-Intrusive Detection of Liquid Nitrogen in Liquid Oxygen at High Pressure and High Flow; Method to Enhance the Operation of an Optical Inspection Instrument Using Spatial Light Modulators; Dual-Compartment Inflatable Suitlock; Large-Strain Transparent Magnetoactive Polymer Nanocomposites; Thermodynamic Vent System for an On-Orbit Cryogenic Reaction Control Engine; Time Distribution Using SpaceWire in the SCaN Testbed on ISS; and Techniques for Solution- Assisted Optical Contacting.

Source record↗
DOE OSTI2026

Small Molecule Inhibitor-Modulated Al 2 O 3 Atomic Layer Deposition on Monolayer MoS 2 for Controlled Nucleation

The integration of ultrathin dielectrics on two-dimensional (2D) semiconductors is essential for advancing beyond-Si electronics. However, the intrinsic inertness of van der Waals 2D basal planes remains a primary bottleneck to achieving uniform dielectric nucleation and growth. Here, in this study, we introduce a small molecule inhibitor (SMI)-modulated thermal atomic layer deposition (ALD) strategy, exemplified by aluminum oxide (Al 2 O 3 ) ALD on monolayer molybdenum disulfide (1L MoS 2 ) with acetic acid (HAc) SMI. The ABC-type sequence comprises HAc inhibitor (A), trimethylaluminum (TMA) precursor (B), and deionized H 2 O coreactant (C). In situ quartz crystal microbalance (QCM) studies reveal robust HAc adsorption on Al 2 O 3 and suppression of subsequent oxide growth on HAc-passivated surfaces. When applied to 1L MoS 2 , this inhibitory pathway enables HAc to selectively passivate nascent Al 2 O 3 nuclei formed on the MoS 2 surface, limiting their three-dimensional (3D) island coarsening and redirecting precursor adsorption toward the uncovered basal plane. Consequently, nearly continuous ultrathin (∼1.5 nm) Al 2 O 3 films are achieved on 1L MoS 2 with markedly improved uniformity compared to standard Al 2 O 3 ALD using TMA and H 2 O, as validated by atomic force microscopy (AFM), cross-sectional scanning transmission electron microscopy (STEM), and energy-dispersive X-ray spectroscopy (EDS). Density functional theory (DFT) calculations further provide atomistic insight into HAc-modulated Al 2 O 3 nucleation, corroborating the energetic preference of HAc for Al 2 O 3 over MoS 2 and attenuated TMA adsorption on HAc-passivated surfaces. Spatially resolved Raman spectroscopy also confirms that the HAc-modulated process preserves the structural integrity of 1L MoS 2 , with only minimal strain and doping perturbations observed after dielectric deposition. This SMI-modulated approach offers a broadly applicable framework for controlling ALD nucleation across various inhibitors, ALD chemistries, and 2D materials, opening opportunities for reliable dielectric integration in next-generation nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adaptive Scalpel Scanning Probe Microscopy for Enhanced Volumetric Sensing in Tomographic Analysis

Controlling nanoscale tip‐induced material removal is crucial for achieving atomic‐level precision in tomographic sensing with atomic force microscopy (AFM). While advances have enabled volumetric probing of conductive features with nanometer accuracy in solid‐state devices, materials, and photovoltaics, limitations in spatial resolution and volumetric sensitivity persist. This work identifies and addresses in‐plane and vertical tip‐sample junction leakage as sources of parasitic contrast in tomographic AFM, hindering real‐space 3D reconstructions. Novel strategies are proposed to overcome these limitations. First, the contrast mechanisms analyzing nanosized conductive features are explored when confining current collection purely to in‐plane transport, thus allowing reconstruction with a reduction in the overestimation of the lateral dimensions. Furthermore, an adaptive tip‐sample biasing scheme is demonstrated for the mitigation of a class of artefacts induced by the high electric field inside the thin oxide when volumetrically reduced. This significantly enhances vertical sensitivity by approaching the intrinsic limits set by quantum tunneling processes, allowing detailed depth analysis in thin dielectrics. The effectiveness of these methods is showcased in tomographic reconstructions of conductive filaments in valence change memory, highlighting the potential for application in nanoelectronics devices and bulk materials and unlocking new limits for tomographic AFM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SaS4D Home Team UI (SaS4D-HT-UI) v1.0

The SaS4D Home Team UI (python) is a software to view and interact with different layers of 3D geometries and generate usable MCNP-style input file. It is used by the remote Home Team in providing guidance and building models of environments they have never seen in order to investigate threat object discovered at the Working Point. The UI visualizes a colorized mesh, a semantic labelled mesh, and a semantic labelled probability mesh of the scanned environment as well as individual water-tight material-labeled objects. It allows for manipulation and re-processing of these objects. The UI also contains measurement tools to facilitate better MCNP input file generation in the manipulation workflow. The software is a key component in ensuring the Home Team has prompt awareness of the Working Point.

Chen, Xin↗
NASA NTRS1990

Space shuttle main engine computed tomography applications

For the past two years the potential applications of computed tomography to the fabrication and overhaul of the Space Shuttle Main Engine were evaluated. Application tests were performed at various government and manufacturer facilities with equipment produced by four different manufacturers. The hardware scanned varied in size and complexity from a small temperature sensor and turbine blades to an assembled heat exchanger and main injector oxidizer inlet manifold. The evaluation of capabilities included the ability to identify and locate internal flaws, measure the depth of surface cracks, measure wall thickness, compare manifold design contours to actual part contours, perform automatic dimensional inspections, generate 3D computer models of actual parts, and image the relationship of the details in a complex assembly. The capabilities evaluated, with the exception of measuring the depth of surface flaws, demonstrated the existing and potential ability to perform many beneficial Space Shuttle Main Engine applications.

Sporny, Richard F.↗
NASA NTRS2021

Origins Survey Spectrometer: revealing the hearts of distant galaxies and forming planetary systems with far-IR spectroscopy

The Origins Survey Spectrometer (OSS) is a multi-purpose far-IR spectrograph for Origins. Operating at the photon background limit, OSS covers the 25- to 588-μm wavelength range instantaneously at a resolving power (R) of 300 using six logarithmically spaced grating modules. Each module couples at least 30 and up to 100 spatial beams simultaneously, enabling true [three-dimensional (3D)] spectral mapping. In addition, OSS provides two high-resolution modes. The first inserts a long-path Fourier-transform spectrometer (FTS) into a portion of the incoming light in advance of the grating backends, enabling R up to 43,000 × [λ/112 μm] , while preserving the grating-based sensitivity for line detection. The second incorporates a scanning etalon in series with the FTS to provide R up to 300,000 for the 100-to 200-μm range.

Charles M. Bradford↗
DOE OSTI2024

Location-Specific Microstructure Characterization Within AM Bench 2022 Nickel Alloy 718 3D Builds

Abstract The Additive Manufacturing Benchmark Test Series (AM Bench) is a broad effort to produce rigorous measurement datasets for validating AM computer simulations across the range of processing, structure, and properties, for many additive manufacturing (AM) build methods and material classes. Here, the microstructures of nickel alloy 718 AM Bench 2022 test artifacts produced using laser-based powder bed fusion (PBF-LB), in both as-built and fully heat-treated conditions, are examined. Cross sections are primarily characterized using large area scanning electron microscopy (SEM) electron backscatter diffraction (EBSD) and example analyses of the crystallographic textures are described. These data are part of a large set of in situ and ex situ measurements from both three-dimensional builds and laser tracks on bare plates. All the measurement data are available online with download links at www.nist.gov/ambench .

Levine, L. E. (ORCID:0000000334484229)↗