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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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10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Coded-mask-based wavefront sensing technique for APS nanofocusing beamline diagnostics

Here, we extend our recently developed coded-mask wavefront sensing technique to enable single-shot measurements of nanofocused x-ray beams. This method accurately reconstructs the focal beam profile by backpropagating the wavefront measured downstream of the beam focus. To validate its performance, we benchmarked it against the conventional fluorescence wire scan method, successfully measuring ∼120 nm focal spots at the 28-ID-B beamline of the Advanced Photon Source using a polymeric compound refractive lens. The results highlight the effectiveness of coded-mask wavefront sensing for high-precision beam profiling and its application as a real-time wavefront monitoring tool.

Shi, Xianbo [Argonne National Laboratory (ANL), Ar↗
DOE OSTI2026

WFSUITE: A PYTHON SOFTWARE SUITE FOR X-RAY WAVEFRONT SENDING AND AT-WAVELENGTH METROLOGY

SF-26-025 WFSuite is a graphical and command-line toolkit for coded-mask-based X-ray wavefront sensing and phase reconstruction at synchrotron beamlines. It integrates analysis tools for both relative and absolute speckle-based measurements. In the relative metrology module, WFSuite implements Wavelet-transform-based X-ray Speckle Tracking (WXST) and Wavelet-transform-based Speckle Vector Tracking (WSVT) methods to retrieve differential phase and wavefront distortions by comparing speckle patterns recorded with and without the test sample. In the absolute phase module, WFSuite uses coded-mask speckle patterns and replaces the measured reference with a numerically simulated one, enablingsingle-shot wavefront reconstruction using either WXST or a neural-network-based method (SPINNet).

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗
DOE OSTI2025

AutoFocus: AI/ML-driven real-time wavefront diagnostics to autonomously align and optimize X-ray optics

We present an integrated system that combines advanced wavefront diagnostics with artificial intelligence (AI) to automate and optimize X-ray optics at synchrotron beamlines. This system couples real-time wavefront sensing with AI-driven control algorithms to achieve precise beam alignment, stabilization, and performance optimization. A key feature is the use of multi-fidelity transfer learning, which enables knowledge gained from both real-world beamline optimizations and ultra-realistic digital twin simulations to be effectively applied to in situ optimization. By leveraging multi-objective bayesian optimization, the system continuously refines its performance, reducing optimization time and minimizing the need for manual adjustments. Designed for seamless deployment, it operates with existing beamline hardware and provides an intuitive graphical interface. Initial deployments at the advanced photon source beamlines have demonstrated its ability to enhance beam stability, improve reproducibility, and significantly streamline alignment procedures. This AI-enhanced control framework represents a significant step toward fully autonomous beamline operation in next-generation synchrotron facilities.

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗
DOE OSTI2026

High-speed quantitative X-ray multi-contrast imaging with deep learning based modulated pattern analysis

The advent of X-ray multi-contrast imaging methods, providing absorption, phase, and dark-field images, holds tremendous promise for complementary and non-destructive visualization of inner structures within materials and bio-samples. However, the low efficiency in measuring and analyzing X-ray modulated patterns has hindered their application in high-resolution in situ imaging. In this work, the Enhanced Scanning Pattern-based Imaging Neural Network (ESPINNet) is introduced as a powerful tool for achieving high-speed, high-resolution quantitative imaging. ESPINNet is faster than correlation-based speckle tracking methods such as XSVT and UMPA, and provides a balanced performance in terms of resolution and speed for data collection by using fewer scanning images. In comparison with our previously developed neural network, ESPINNet introduces the capability to generate dark-field images, further enhancing its versatility. By leveraging scanning patterns, ESPINNet significantly improves resolution and measurement precision. Furthermore, its adaptability to various modulation patterns, including those produced by sandpaper, coded masks, or gratings, ensures broad applicability. These features enable real-time 2D and 3D multi-contrast imaging, positioning ESPINNet as a transformative solution for applications in materials science and biomedical research, particularly for high-speed and in situ measurements.

X-ray at-wavelength metrology↗
DOE OSTI2025

Programmable low-coherence wavefronts for enhanced localization

Engineering the properties of electromagnetic wavefronts has become essential to imaging, wireless security, sensing, and wireless communication. In particular, wavefronts that exhibit low spatial coherence can enable sensing functionalities with high accuracy and low latency. The typical use of such wavefronts cannot take advantage of these possibilities, as they require the ability to dynamically reconfigure the wavefront in a controllable and repeatable fashion, over a broad spectral bandwidth. Here, we propose a new approach for generating broadband reconfigurable wavefronts which not only exhibit low spatial coherence at a particular frequency, but are also decorrelated with the wavefronts simultaneously generated at other frequencies. We demonstrate that this frequency-domain decorrelation is a key feature that, in combination with dynamic reconfigurability, enables localization measurements with an order-of-magnitude improvement in accuracy compared to the state of the art.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fourier-based three-dimensional multistage transformer for aberration correction in multicellular specimens

High-resolution tissue imaging is often compromised by sample-induced optical aberrations that degrade resolution and contrast. Although wavefront sensor-based adaptive optics (AO) can measure these aberrations, such hardware solutions are typically complex, expensive to implement and slow when serially mapping spatially varying aberrations across large fields of view. Here we introduce AOViFT (adaptive optical vision Fourier transformer)—a machine learning-based aberration sensing framework built around a three-dimensional multistage vision transformer that operates on Fourier domain embeddings. AOViFT infers aberrations and restores diffraction-limited performance in puncta-labeled specimens with substantially reduced computational cost, training time and memory footprint compared to conventional architectures or real-space networks. We validated AOViFT on live gene-edited zebrafish embryos, demonstrating its ability to correct spatially varying aberrations using either a deformable mirror or postacquisition deconvolution. By eliminating the need for the guide star and wavefront sensing hardware and simplifying the experimental workflow, AOViFT lowers technical barriers for high-resolution volumetric microscopy across diverse biological samples.

Alshaabi, Thayer [Howard Hughes Medical Institute,↗
DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗
DOE OSTI2025

Statistical Analysis of Trans‐Ionospheric Pulse Pairs and Inferences on Their Characteristics

Trans-ionospheric pulse pairs (TIPPs), first observed in 1993, are signatures of in-cloud lightning discharges observed by satellite-based broadband very high frequency (VHF) receivers. It has been definitively shown that TIPPs are the space-based signatures of compact intracloud discharges (CIDs), and that the associated pair of pulses that comprise a TIPP result from the direct VHF pulse from the discharge, followed by a pulse reflected from the Earth's surface. However, the ratio of the peak amplitudes of these two pulses can vary widely, with the second pulse often having considerably higher peak amplitude than the first. This observation has not been satisfactorily explained. Using data collected from geostationary orbit by the Radio Frequency Sensor (RFS) and matched to locations reported by the Global Lightning Dataset (GLD360), we assemble the largest database to date of 76,348 TIPPs with associated location, altitude, and amplitude ratio of the two pulses in the TIPP. We show that the amplitude ratio of TIPPs is strongly correlated to the altitude of the associated discharges and the geometry of the source location with respect to the Earth's surface and the receiver. These observations strongly suggest that the difference in amplitude of the two pulses is driven by a nondipole radiated beam pattern that is dependent on the polarity of the CID, velocity of the current wavefront, and viewing angle.

58 GEOSCIENCES↗