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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗
DOE OSTI2026

Spectral Similarity Masks Structural Diversity at Hydrophobic Water Interfaces

The air-water and graphene-water interfaces represent quintessential examples of the liquid-gas and liquid-solid boundaries, respectively. While the sum-frequency generation (SFG) spectra of these interfaces show similarities, a consensus on their signals and interpretations has yet to be reached. Leveraging deep learning, we computed first-principles SFG spectra for both systems, addressing experimental discrepancies. Here, our findings reveal that similarities in SFG signals do not translate into comparable interfacial microscopic properties. Instead, graphene-water and air-water interfaces exhibit fundamental differences in SFG-active thicknesses, hydrogen-bonding networks, and surface dynamics. These distinctions underscore roughness suppression and electronic interactions present at the solid-liquid interface but absent at the gas-liquid interface.

Wang, Yong [Princeton Univ., NJ (United States)] (↗
DOE OSTI2025

COnfirmation using Gamma-ray Non-Imaging Zero-knowledge ANti-mask Time-encoding (COGNIZANT) Final Summary Report

In potential future arms reduction treaties in which the numbers of nuclear warheads may approach small numbers, using delivery systems as a proxy for the warheads themselves may be insufficient. Therefore, a technical means of verifying the presence of a nuclear warhead may become necessary. Verifying that a declared item actually is a warhead is technically challenging within a verification regime: providing assurance to the monitoring party that a presented item is a warhead while protecting sensitive information about that warhead may be required. It is generally believed that strong assurance will require the confirmation of key attributes that may reveal closely-guarded critical design information. This provides high confidence to the monitoring party, but presents a risk of information loss to the host. A verification system must overcome this hurdle. Over the last several decades, systems have been developed that balance host and monitoring partner needs by using sensitive information to confirm treaty accountable items (TAI) as warheads while sequestering that information behind an information barrier (1). These are designed to meet the needs of the host but places the onus on the monitor to authenticate the hardware, firmware, and software. Authentication requires that the monitor confirm that all components of the system have not been modified and work as intended. In 2014, Glaser et al. proposed applying the concept of “zero knowledge protocols” (ZKP) from the field of cryptography to the problem of warhead verification (2). In mathematical cryptography, ZKP is accomplished by challenging one party to solve a problem that is only possible if that party possesses the information being authenticated. After repeated challenges, the party provides confidence that it possesses this information without revealing any details about the information itself. Systems have been in development based on this idea at both Princeton and MIT (2) (3) (4). The final measurement results produced by these systems can be viewed by both the host and the monitoring party without the worry of revealing sensitive information. However, in both of these physical implementations, there remains an information barrier within the system. The need for a digital information barrier to protect a measurement result is eliminated, but it has been replaced with the need to sequester physical components of the system, potentially obfuscating the measurement process itself. Both implementations physically insert information into the system that requires protection to prevent undesired disclosure of sensitive information: in the Princeton method, one must physically load the complement of the expected image of a true warhead into the system, and in the MIT technique, one loads a collection of spectator foils whose thicknesses physically encrypt a measured spectrum. This complicates authentication of the hardware and measurement process. The CONFIDANTE/COGNIZANT concept developed in this project do not load sensitive information into the system at any time, and could therefore open the possibility of allowing the inspector to not only view the final data but also the measurement as it is being performed and all associated equipment.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

FastrSHWFS Analysis

This code analyzes the reflection geometry of modified Shack-Hartmann Wavefront Sensor (SHWFS) masks, with a focus on the fastrSHWFS designs. It takes a height map of a reflective mask, divides it into sub apertures, removes the global focus term by referencing a central block, and fits local surface planes to each sub aperture. From these fits it computes reflection angles and propagates the corresponding rays downstream to determine spot positions and the overall reflected beam footprint as a function of distance. The implementation is parameterized in sub aperture size, number of sub apertures, focal length, and mask dimensions, so it can be adapted to different mask designs beyond the two current fastrSHWFS masks. The code: Converts mask bitmaps into physical height in microns and reconstructs a focus subtracted mask, divides the mask into a grid of sub apertures and assigns pixel and micron coordinates to each block, excludes user specified unused sub apertures from the analysis, fits a plane to each sub aperture to obtain local surface normals, propagates reflected rays to a range of z positions to compute ray spots and the full reflected beam width, computes the effective mask tilt angle with respect to the incoming beam as a function of propagation distance, and provides helper routines for plotting the grid over the mask and for visualizing the beam geometry. These tools are intended for iterating on fastrSHWFS mask designs and for planning downstream optical layouts, for example choosing lens positions and apertures that capture the reflected beam given known focal plane distances and beam widths.

Gerard, BenjaminL [Lawrence Livermore National Lab↗
DOE OSTI2025

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗
DOE OSTI2024

SAM-I-Am: Semantic boosting for zero-shot atomic-scale electron micrograph segmentation

Image segmentation is a critical enabler for tasks ranging from medical diagnostics to autonomous driving. However, the correct segmentation semantics — where are boundaries located? what segments are logically similar? — change depending on the domain, such that state-of-the-art foundation models can generate meaningless and incorrect results. Moreover, in certain domains, fine-tuning and retraining techniques are infeasible: obtaining labels is costly and time-consuming; domain images (micrographs) can be exponentially diverse; and data sharing (for third-party retraining) is restricted. To enable rapid adaptation of the best segmentation technology, we propose the concept of semantic boosting: given a zero-shot foundation model, guide its segmentation and adjust results to match domain expectations. Here, we apply semantic boosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron microscopy. Our booster, SAM-I-Am, serves as a post-processing engine that extracts geometric and textural features of various intermediate masks to perform mask removal and mask merging operations. We demonstrate a zero-shot performance increase of (absolute) +21.35%, +12.6%, +5.27% in mean IoU, and a -9.91%, -18.42%, -4.06% drop in mean false positive masks across images of three difficulty classes over vanilla SAM (ViT-L).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mechanisms of Three-Dimensional Solid-Phase Epitaxial Crystallization of Strontium Titanate

Strontium titanate (SrTiO 3 , STO) is a complex metal oxide with a cubic perovskite crystal structure. Due to its easily described and understood crystal structure in the cubic phase, STO is an ideal model system for exploring the mechanistic details of solid-phase epitaxy (SPE) in complex oxides. SPE is a crystallization approach that aims to guide crystal growth at low homologous temperatures to achieve targeted microstructures. Beyond planar thin films, SPE can also exploit the addition of a chemically inert, noncrystallizing, amorphous obstacle in the path of crystallization to generate complex three-dimensional structures. The introduction of this mask fundamentally alters the SPE process, inducing a transition from two- to three-dimensional geometries and from vertical to lateral crystal growth under the influence of the crystal/mask/amorphous boundary. Using a combination of molecular dynamics simulations and experiments, we identify several unique phenomena in the nanoscale growth behaviors in both conventional (unmasked) and masked SPE. Examining conventional SPE of STO, we find that crystallization at the interface is strongly correlated to, and potentially driven by, density fluctuations in the region of the amorphous STO near the crystalline/amorphous interface with a strong facet dependence. In the masked case, we find that the crystalline growth front becomes nonplanar near contact with the mask. We also observe a minimum vertical growth requirement prior to lateral crystallization. Both phenomena depend on the relative bulk and interfacial free energies of the three-phase (crystal/mask/amorphous) system.

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

Patchy nanoparticles by atomic stencilling

Stencilling, in which patterns are created by painting over masks, has ubiquitous applications in art, architecture and manufacturing. Modern, top-down microfabrication methods have succeeded in reducing mask sizes to under 10 nm, enabling ever smaller microdevices as today’s fastest computer chips. Meanwhile, bottom-up masking using chemical bonds or physical interactions has remained largely unexplored, despite its advantages of low cost, solution-processability, scalability and high compatibility with complex, curved and three-dimensional (3D) surfaces. Here we report atomic stencilling to make patchy nanoparticles (NPs), using surface-adsorbed iodide submonolayers to create the mask and ligand-mediated grafted polymers onto unmasked regions as ‘paint’. We use this approach to synthesize more than 20 different types of NP coated with polymer patches in high yield. Polymer scaling theory and molecular dynamics (MD) simulation show that stencilling, along with the interplay of enthalpic and entropic effects of polymers, generates patchy particle morphologies not reported previously. These polymer-patched NPs self-assemble into extended crystals owing to highly uniform patches, including different non-closely packed superlattices. We propose that atomic stencilling opens new avenues in patterning NPs and other substrates at the nanometre length scale, leading to precise control of their chemistry, reactivity and interactions for a wide range of applications, such as targeted delivery, catalysis, microelectronics, integrated metamaterials and tissue engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The FastrSHWFS Project Development Motivation, Analysis, & Test Results

The recent 2020 Decadal Survey of Astronomy and Astrophysics listed habitable exoplanet imaging with future extreme adaptive optics (AO) on 30m-class telescopes as a key priority in the coming decade. However, there is a current 100x contrast gap between the best systems today and what is needed to enable this goal. Astronomical AO is a required approach to enable ground-based diffraction-limited imaging of exoplanets on future extremely large telescopes. Time lag between the end of an exposure and the application of deformable mirror commands is a major contributor to the error budget in many AO systems, and detector read time is often a large component of this lag. We present two designs for a modified Shack Hartmann wavefront sensor (SHWFS), named Focal plane Actualized Shifted Technique Realized for a SHWFS (fastrSHWFS), to reduce the time lag component. This design steers the spot pattern at the focal plane into a rectangular or linear array with a custom aspect ratio, reducing readout time. The mask with focus yields aberrated results while the mask with tip/tilt only yields some defined spots. This essay outlines the current SHWFS concept, our fastrSHWFS theoretical solution to addressing time lag, reflection and quality analysis of printed mask designs, and results from testing both masks on the High Contrast Testbed at Lawrence Livermore National Lab. This work follows the test of a previous fastrSHWFS design.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Birefringent Glass‐Engraved Quasi‐Linear Nanograting Metasurface Based on Self‐Organizing Process for Large Aperture High Power Laser Applications

All-glass metasurface “nanograting” structures that exhibit birefringence in the formed layer are reported. The key enabler of this work is ion beam processing at an angle sufficiently off-normal incidence, inducing self-assembly of a deposited metal layer into quasi-linear metallic features that can function as an etching mask. As a result, a fused silica metasurface, monolithic to the underlying substrate, is demonstrated at 375 nm wavelength to exhibit a phase delay angle of 30° between the principal axes. The capability of an angled etch mask replenishment process is also demonstrated for achieving deeper etch depth and for increasing the grating period, another first – to the best of the knowledge. This is the first display of a technology capable of fabricating glass-engraved near-linear grating structure with a feature-to-feature period as small as 118.6 nm. Furthermore, this technology has the potential to generate grating-like structures with periods as small as 12.4 nm, as demonstrated here with reactive ion beam processing assisted mask assembly. Furthermore, these structures are shown to have reflectivity < 0.4% across the wavelength band 350 nm – 1000 nm. Such a technology can enable laser-durable grating structures for the deep-UV and even down to soft X-ray wavelengths.

Ray, Nathan J. [Lawrence Livermore National Labora↗
DOE OSTI2024

Engineering a tumor-selective prodrug T-cell engager bispecific antibody for safer immunotherapy

T-cell engaging (TCE) bispecific antibodies are potent drugs that trigger the immune system to eliminate cancer cells, but administration can be accompanied by toxic side effects that limit dosing. TCEs function by binding to cell surface receptors on T cells, frequently CD3, with one arm of the bispecific antibody while the other arm binds to cell surface antigens on cancer cells. On-target, off-tumor toxicity can arise when the target antigen is also present on healthy cells. The toxicity of TCEs may be ameliorated through the use of pro-drug forms of the TCE, which are not fully functional until recruited to the tumor microenvironment. This can be accomplished by masking the anti-CD3 arm of the TCE with an autoinhibitory motif that is released by tumor-enriched proteases. Here, we solve the crystal structure of the antigen-binding fragment of a novel anti-CD3 antibody, E10, in complex with its epitope from CD3 and use this information to engineer a masked form of the antibody that can activate by the tumor-enriched protease matrix metalloproteinase 2 (MMP-2). We demonstrate with binding experiments and in vitro T-cell activation and killing assays that our designed prodrug TCE is capable of tumor-selective T-cell activity that is dependent upon MMP-2. Furthermore, we demonstrate that a similar masking strategy can be used to create a pro-drug form of the frequently used anti-CD3 antibody SP34. This study showcases an approach to developing immune-modulating therapeutics that prioritizes safety and has the potential to advance cancer immunotherapy treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Weighted FFT estimators for 1D and 3D correlations of the Lyman- α forest

Correlations in the Lyman-α (Lyα) forest, both as a function of line of sight separation (1D) and 3D separation, provide a unique window to the distribution of matter at redshifts not accessible by current galaxy surveys. While optimal quadratic estimators have been used to measure 1D correlations, they are computationally expensive and difficult to extend to 3D analyses. On the other hand, estimators based on the Fast Fourier Transform (FFT) are significantly faster, but are affected by missing data in the spectra (masked pixels) and so far have not used pixel weights to reduce the uncertainties in the measurement. In this publication we describe how to compute the window matrix that enables forward-modelling the impact of masked pixels and weights on the FFT-based estimators. Here, we use Gaussian and hydrodynamical simulations with artificially masked pixels to validate the method on the measurement of 1D correlations. Finally, we show that the formalism can be extended to model the impact on 3D correlations, in particular on the cross-spectrum, the correlation of 1D Fourier modes as a function of transverse separation. This work will enable more precise clustering measurements with the Lyα forest dataset recently collected by the Dark Energy Spectroscopic Instrument (DESI).

Lokken, Martine [Univ. Autonoma de Barcelona (Spai↗
DOE OSTI2025

First Direct-Detection Results on Sub-GeV Dark Matter Using the SENSEI Detector at SNOLAB

Here, we present the first results from a dark matter search using six Skipper-CCDs in the SENSEI detector operating at SNOLAB. We employ a bias-mitigation technique of hiding approximately 46% of our total data and aggressively mask images to remove backgrounds. Given a total exposure after masking of 100.72 gram-days from well-performing sensors, we observe 55 two-electron events, 4 three-electron events, and no events containing 4–10 electrons. The two-electron events are consistent with pileup from one-electron events. Among the 4 three-electron events, 2 appear in pixels that are likely impacted by detector defects, although not strongly enough to trigger our “hot-pixel” mask. We use these data to set world-leading constraints on sub-GeV dark matter interacting with electrons and nuclei.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗