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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hubble WFC3 Spectroscopy of the Habitable-zone Super-Earth LHS 1140 b

Atmospheric characterization of temperate, rocky planets is the holy grail of exoplanet studies. These worlds are at the limits of our capabilities with current instrumentation in transmission spectroscopy and challenge our state-of-the-art statistical techniques. Here we present the transmission spectrum of the temperate super-Earth LHS 1140b using the Hubble Space Telescope (HST). The Wide Field Camera 3 (WFC3) G141 grism data of this habitable-zone (T {sub eq} = 235 K) super-Earth (R = 1.7 R {sub ⊕}) shows tentative evidence of water. However, the signal-to-noise ratio, and thus the significance of the detection, is low and stellar contamination models can cause modulation over the spectral band probed. We attempt to correct for contamination using these models and find that, while many still lead to evidence for water, some could provide reasonable fits to the data without the need for molecular absorption although most of these cause features in the visible ground-based data which are nonphysical. Future observations with the James Webb Space Telescope would be capable of confirming, or refuting, this atmospheric detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗
DOE OSTI2021

Dark energy survey year 3 results: weak lensing shape catalogue

ABSTRACT We present and characterize the galaxy shape catalogue from the first 3 yr of Dark Energy Survey (DES) observations, over an effective area of 4143 deg2 of the southern sky. We describe our data analysis process and our self-calibrating shear measurement pipeline metacalibration, which builds and improves upon the pipeline used in the DES Year 1 analysis in several aspects. The DES Year 3 weak-lensing shape catalogue consists of 100 204 026 galaxies, measured in the riz bands, resulting in a weighted source number density of neff = 5.59 gal arcmin−2 and corresponding shape noise σe = 0.261. We perform a battery of internal null tests on the catalogue, including tests on systematics related to the point spread function (PSF) modelling, spurious catalogue B-mode signals, catalogue contamination, and galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗
DOE OSTI2025

Approaching the Lower Temporal Limit of Laser‐Produced Plasma Sources for Table‐Top Soft X‐Ray NEXAFS Measurements

Abstract The increasing popularity of time‐resolved X‐ray absorption measurements for understanding dynamics in molecular and material systems has led to many advances in table‐top sources for pulsed X‐rays. We report on a table‐top laser‐produced plasma (LPP) source that can perform soft X‐ray (SXR), near‐edge X‐ray absorption fine structure (NEXAFS) measurements using a laser source with 23 ps pulse duration. The spectrometer's key specifications, such as brilliance, resolution, and stability, are characterized against the more commonly used longer‐pulse‐duration LPP sources. The 23 ps laser produced approximately an order of magnitude weaker SXR flux than the 8 ns laser for a higher power density due to the smaller total energy absorbed by the plasma. The increased repetition rate, as well as the use of a high line‐density X‐grating, and a self‐referencing scheme still allowed for NEXAFS measurements of Si 3 N 4 and TiO 2 thin films with 2.5 minute acquisition times, a resolving power of E/ΔE=424, and a signal‐to‐noise ratio of 100. It was observed that degradation of the gas jet nozzle led to long‐term instability of the source, which can be remediated using alternative nozzle designs. This work demonstrates the feasibility of achieving higher temporal resolution in future time‐resolved X‐ray absorption measurements using table‐top LPP sources.

Nimlos, Danika [Division of Chemistry and Chemical↗
DOE OSTI2021

Synergistic data analytics for electromechanical oscillation in electric power systems

Accurate real-time estimation of the four electromechanical oscillation properties, i.e., dominant oscillation modes, mode shapes, participation factors, and coherent groups, is of great importance to assess and mitigate potential electromechanical oscillations in interconnected power systems. While eigenvalue analysis can realize such estimation, it requires precise linearized dynamic models and accurate parameters, which are highly difficult to obtain in practice. Data fusion-based modal estimation methods can extract the properties of electromechanical oscillations from measurement data without the power system model and parameters, but most of the time only one or two property assessments can be accomplished each time. To overcome this challenge, this paper presents a synergistic data analytics solution to characterize the dynamic behaviors of electromechanical oscillations from real-time measurement data. Here, the proposed method uses optimized variable projection, and it is capable of estimating all four electromechanical oscillation behavior properties from measured responses. Case studies are performed using the simulated measurement data of a 16-generator 68-bus test system and the field measurements collected by the PMUs deployed in the Yunnan Power Grid. The results demonstrate that the proposed synergistic data analytics solution can achieve satisfactory performance in capturing the properties of electromechanical oscillations from measurement data and exhibit strong robustness against measurement noise when compared with existing measurement-based methods.

42 ENGINEERING↗
DOE OSTI2023

A 32-channels readout ASIC for X-ray spectrometry and tracking in the GAPS experiment

Here this work describes the architecture and the experimental results from the characterization of a 32-channels mixed-signal Application-Specific Integrated Circuit (ASIC) developed for the readout of the lithium-drifted silicon, Si(Li), detectors of the General AntiParticle Spectrometer (GAPS) experiment dedicated to searching for dark matter. The instrument is designed for the identification of antiprotons, antideuterons and antihelium nuclei from cosmic rays during an Antarctic balloon mission scheduled for late 2024. A full custom integrated circuit, named SLIDER32 (32-channels Si-LI DEtector Readout) ASIC, has been produced in a commercial 180 nm CMOS technology. The ASIC is comprised of 32 low-noise analog readout channels featuring dynamic signal compression to comply with the wide input range, an 11-bit SAR ADC and a digital back-end section which is responsible for channel setting and for sending digital information to the data acquisition system (DAQ). The circuit design criteria and the experimental results are discussed in the paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Experimental results from the characterization of a 32-channels mixed-signal processor for the GAPS experiment

This work describes the experimental results obtained from the characterization of a 32-channels readout ASIC that is the core of a module composed by 4 Lithium-drifted Silicon, Si(Li), detectors. The module is the building block of a tracker in an upcoming balloon experiment. The activity is carried out within the General AntiParticle Spectrometer (GAPS) international collaboration, whose objective is the indirect detection of dark matter through the detection of antiparticles present in cosmic rays at low energies. The balloon flight is foreseen in 2024 from the McMurdo station in Antarctica. The ASIC is designed in a 180 nm CMOS technology and has 32 low-noise analog readout channels featuring a dynamic compression of the signal, an 11-bit SAR ADC, and a digital back-end section responsible for channel setting and for sending digital information to the data acquisition system of the tracker. This work has a twofold goal: it intends on the one hand to verify the performance of the circuit, on the other to select at least 300 good samples to be used for the assembly of the GAPS Si(Li) tracker.

Riceputi, Elisa↗
DOE OSTI2021

Correlated charge noise and relaxation errors in superconducting qubits

In This report, the central challenge in building a quantum computer is error correction. Unlike classical bits, which are susceptible to only one type of error, quantum bits (“qubits”) are susceptible to two types of error, corresponding to flips of the qubit state about the X- and Z-directions. While the Heisenberg Uncertainty Principle precludes simultaneous monitoring of X- and Z-flips on a single qubit, it is possible to encode quantum information in large arrays of entangled qubits that enable accurate monitoring of all errors in the system, provided the error rate is low. Another crucial requirement is that errors cannot be correlated. Here, we characterize a superconducting multiqubit circuit and find that charge fluctuations are highly correlated on a length scale over 600 µm; moreover, discrete charge jumps are accompanied by a strong transient suppression of qubit energy relaxation time across the millimeter-scale chip. The resulting correlated errors are explained in terms of the charging event and phonon-mediated quasiparticle poisoning associated with absorption of gamma rays and cosmic-ray muons in the qubit substrate. Robust quantum error correction will require the development of mitigation strategies to protect multiqubit arrays from correlated errors due to particle impacts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Autonomous extraction of millimeter-scale deformation in InSAR time series using deep learning

Systematically characterizing slip behaviours on active faults is key to unraveling the physics of tectonic faulting and the interplay between slow and fast earthquakes. Interferometric Synthetic Aperture Radar (InSAR), by enabling measurement of ground deformation at a global scale every few days, may hold the key to those interactions. However, atmospheric propagation delays often exceed ground deformation of interest despite state-of-the art processing, and thus InSAR analysis requires expert interpretation and a priori knowledge of fault systems, precluding global investigations of deformation dynamics. Here, we show that a deep auto-encoder architecture tailored to untangle ground deformation from noise in InSAR time series autonomously extracts deformation signals, without prior knowledge of a fault’s location or slip behaviour. Applied to InSAR data over the North Anatolian Fault, our method reaches 2 mm detection, revealing a slow earthquake twice as extensive as previously recognized. We further explore the generalization of our approach to inflation/deflation-induced deformation, applying the same methodology to the geothermal field of Coso, California.

58 GEOSCIENCES↗
DOE OSTI2020

Imaging of multiple fluorescent proteins in canopies enables synthetic biology in plants

Reverse genetics approaches have revolutionized plant biology and agriculture. Phenomics has the prospect of bridging plant phenotypes with genes, including transgenes, to transform agricultural fields. Genetically encoded fluorescent proteins (FPs) have revolutionized plant biology paradigms in gene expression, protein trafficking and plant physiology. While the first instance of plant canopy imaging of green fluorescent protein (GFP) was performed over 25 years ago, modern phenomics has largely ignored fluorescence as a transgene expression device despite the burgeoning FP colour palette available to plant biologists. Here, we show a new platform for stand-off imaging of plant canopies expressing a wide variety of FP genes. The platform-the fluorescence-inducing laser projector (FILP)-uses an ultra-low-noise camera to image a scene illuminated by compact diode lasers of various colours, coupled with emission filters to resolve individual FPs, to phenotype transgenic plants expressing FP genes. Each of the 20 FPs screened in plants were imaged at >3 m using FILP in a laboratory-based laser range. We also show that pairs of co-expressed fluorescence proteins can be imaged in canopies. The FILP system enabled a rapid synthetic promoter screen: starting from 2000 synthetic promoters transfected into protoplasts to FILP-imaged agroinfiltrated Nicotiana benthamiana plants in a matter of weeks, which was useful to characterize a water stress-inducible synthetic promoter. FILP canopy imaging was also accomplished for stably transformed GFP potato and in a split-GFP assay, which illustrates the flexibility of the instrument for analysing fluorescence signals in plant canopies.

abiotic stress↗
DOE OSTI2020

Characterizing the Sensitivity of 40 GHz TES Bolometers for BICEP Array

The BICEP/Keck (BK) experiment aims to detect the imprint of primordial gravitational waves in the cosmic microwave background polarization, which would be direct evidence of the inflation theory. While the tensor-to-scalar ratio has been constrained to be $r_{0.05}<0.06$ at 95% c.l., further improvements on this upper limit are hindered by polarized galactic foreground emissions and removal of gravitational lensing polarization. The 30/40 GHz receiver of the BICEP Array (BA) will deploy at the end of 2019 and will constrain the synchrotron foreground with unprecedented accuracy within the BK sky patch. We will show the design of the 30/40 GHz detectors and test results summarizing its performance. The low optical and atmospheric loading at these frequencies requires our TES detectors to have low saturation power in order to be photon noise dominated. To realize the low thermal conductivity required from a 250 mK base temperature, we developed new bolometer leg designs. We will present the relevant measured detector parameters: $G, T_c, R_n, P_{sat}$, and spectral bands, and noise spectra. We achieved a per bolometer NEP including all noise components of 2.07×10 -17 W/$\sqrt{Hz}$, including an anticipated photon noise level 1.54×10 -17 W/$\sqrt{Hz}$.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo

Functional data registration is a necessary processing step for many applications. The observed data can be inherently noisy, often due to measurement error or natural process uncertainty; which most functional alignment methods cannot handle. A pair of functions can also have multiple optimal alignment solutions, which is not addressed in current literature. In this paper, a flexible Bayesian approach to functional alignment is presented, which appropriately accounts for noise in the data without any pre-smoothing required. Additionally, by running parallel MCMC chains, the method can account for multiple optimal alignments via the multi-modal posterior distribution of the warping functions. To most efficiently sample the warping functions, the approach relies on a modification of the standard Hamiltonian Monte Carlo to be well-defined on the infinite-dimensional Hilbert space. In this work, this flexible Bayesian alignment method is applied to both simulated data and real data sets to show its efficiency in handling noisy functions and successfully accounting for multiple optimal alignments in the posterior; characterizing the uncertainty surrounding the warping functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sources of error and methods to improve accuracy in interface state density analysis using quasi-static capacitance–voltage measurements in wide bandgap semiconductors

Characterizing interface trap states in commercial wide bandgap devices using frequency-based measurements requires unconventionally high probing frequencies to account for both fast and slow traps associated with wide bandgap materials. The C - ψs technique has been suggested as a viable quasi-static method for determining the interface trap state densities in wide bandgap systems, but the results are shown to be susceptible to errors in the analysis procedure. Here this work explores the primary sources of errors present in the C - ψs technique using an analytical model that describes the apparent response for wide bandgap MOS capacitor devices. Measurement noise is shown to greatly impact the linear fitting routine of the 1/C$^{*2}_s$ vs Ψ s plot to calibrate the additive constant in the surface potential/gate voltage relationship, and an inexact knowledge of the oxide capacitance is also shown to impede interface trap state analysis near the band edge. In addition, a slight nonlinearity that is typically present throughout the 1/C$^{*2}_s$ vs Ψ s plot hinders the accurate estimation of interface trap densities, which is demonstrated for a fabricated n-SiC MOS capacitor device. Methods are suggested to improve quasi-static analysis, including a novel method to determine an approximate integration constant without relying on a linear fitting routine.

42 ENGINEERING↗
DOE OSTI2025

Attention to quantum complexity

The imminent era of error-corrected quantum computing demands robust methods to characterize quantum state complexity from limited, noisy measurements. We introduce the Quantum Attention Network (QuAN), a classical artificial intelligence (AI) framework leveraging attention mechanisms tailored for learning quantum complexity. Inspired by large language models, QuAN treats measurement snapshots as tokens while respecting permutation invariance. Combined with our parameter-efficient miniset self-attention block, this enables QuAN to access high-order moments of bit-string distributions and preferentially attend to less noisy snapshots. We test QuAN across three quantum simulation settings: driven hard-core Bose-Hubbard model, random quantum circuits, and toric code under coherent and incoherent noise. QuAN directly learns entanglement and state complexity growth from experimental computational basis measurements, including complexity growth in random circuits from noisy data. In regimes inaccessible to existing theory, QuAN unveils the complete phase diagram for noisy toric code data as a function of both noise types, highlighting AI’s transformative potential for assisting quantum hardware.

Kim, Hyejin [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2023

SPLENDAQ: A Detector-Agnostic Data Acquisition System for Small-Scale Physics Experiments

Many scientific applications from rare-event searches to condensed matter system characterization to high-rate nuclear experiments require time-domain triggering on a raw stream of data, where the triggering is generally threshold-based or randomly acquired. When carrying out detector R &D, there is a need for a general data acquisition (DAQ) system to quickly and efficiently process such data. In the SPLENDOR collaboration, we are developing the Python-based SPLENDAQ package for this exact purpose—it offers two main features for offline analysis of continuous data: a threshold triggering algorithm based on the time-domain optimal filter formalism and an algorithm for randomly choosing nonoverlapping segments for noise measurements. Further, combined with the commercially available Moku platform, developed by Liquid Instruments, we have a full pipeline of event building off raw data with minimal setup. Here, we review the underlying principles of this detector-agnostic DAQ package and give concrete examples of its utility in various applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A quantum eigenvalue solver based on tensor networks

Electronic ground states are of central importance in chemical simulations, but have remained beyond the reach of efficient classical algorithms except in cases of weak electron correlation or one-dimensional spatial geometry. We introduce a hybrid quantum-classical eigenvalue solver that constructs a wavefunction ansatz from a linear combination of matrix product states in rotated orbital bases, enabling the characterization of strongly correlated ground states with arbitrary spatial geometry. The energy is converged via a gradient-free generalized sweep algorithm based on quantum subspace diagonalization, with a potentially exponential speedup in the off-diagonal matrix element contractions upon translation into compact quantum circuits of linear depth in the number of qubits. Chemical accuracy is attained in numerical experiments for both a stretched water molecule and an octahedral arrangement of hydrogen atoms, achieving substantially better correlation energies compared to a unitary coupled-cluster benchmark, with orders of magnitude reductions in quantum resource estimates and a surprisingly high tolerance to shot noise. This proof-of-concept study suggests a promising new avenue for scaling up simulations of strongly correlated chemical systems on near-term quantum hardware.

chemistry↗