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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 145 records · Page 8

Measurement bias in self-heating x-ray free electron laser experiments from diffraction studies of phase transformation in titanium

X-ray self-heating is a common by-product of X-ray Free Electron Laser (XFEL) techniques that can affect targets, optics, and other irradiated materials. Diagnosis of heating and induced changes in samples may be performed using the x-ray beam itself as a probe. However, the relationship between conditions created by and inferred from x-ray irradiation is unclear and may be highly dependent on the material system under consideration. Here, we report on a simple case study of a titanium foil irradiated, heated, and probed by a MHz XFEL pulse train at 18.1 keV delivered by the European XFEL using measured x-ray diffraction to determine temperature and finite element analysis to interpret the experimental data. We find a complex relationship between apparent temperatures and sample temperature distributions that must be accounted for to adequately interpret the data, including beam averaging effects, multivalued temperatures due to sample phase transitions, and jumps and gaps in the observable temperature near phase transformations. The results have implications for studies employing x-ray probing of systems with large temperature gradients, particularly where these gradients are produced by the beam itself. Finally, this study shows the potential complexity of studying nonlinear sample behavior, such as phase transformations, where biasing effects of temperature gradients can become paramount, precluding clear observation of true transformation conditions.

Crystallography↗

Determination of nuclear charge radius by extreme-ultraviolet spectroscopy of Na-like ions

We report on a method for determining the absolute nuclear charge radius of high-𝑍 elements using extreme-ultraviolet spectroscopy of highly charged Na-like ions in tandem with highly accurate atomic structure calculations of transition energy differences. The application of this method has reduced the nuclear charge radius uncertainty of 191 Ir by a factor of 8 from the currently accepted literature value, with a recently reported charge radius of 5.435(12) fm. The result reduces the charge radius uncertainty along the full Ir isotopic chain when combined with prior optical isotope shift measurements. The technique utilizes only a few million ions stored in an ion trap, which should apply to measurements with small quantities of radioactive nuclei.

Atom & ion trapping & guiding↗

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗

Exploring Interferometry Diagnostics for Optical Stochastic Cooling at FAST/IOTA

Optical Stochastic Cooling (OSC) is an advanced beam-cooling technique that will precede the traditional stochastic cooling. This method leverages optical radiation and high-precision feedback to cool the particles more efficiently than traditional stochastic methods by more than three orders of magnitude. As such, it is an enabler for the development of next generation discovery science machines at the frontiers of energy and intensity. This paper focuses on the development of the second phase of OSC and improving extreme beam cooling technique in accelerators. Along with the assembly and use of an interferometer to provide diagnostics and optimization to OSC systems. The interferometer can allow for the observation and analysis of fringe patterns from a recreated simpler version in the laser room. By leveraging interferometric techniques, OSC can achieve higher efficiency, verification, stability and performance.

Teriba, Folashade↗

EXPLORING INTERFEROMETRY DIAGNOSTICS FOR OPTICAL STOCHASTIC COOLING AT FAST/IOTA

Optical Stochastic Cooling (OSC) is an advanced beam-cooling technique that will advance the traditional stochastic cooling. This method leverages optical radiation and high-precision feedback to cool the particles more efficiently than traditional stochastic methods by more than three orders of magnitude. As such, it is an enabler for the development of next generation discovery science machines at the frontiers of energy and intensity. This paper focuses on the development of the second phase of OSC and improving extreme beam cooling techniques in accelerators. The goal was to build and characterize a Mach-Zehnder Interferometer (MZI) in the FAST laser lab using known glass plates thickness which will allow future measurements of unknown phase change due to nonlinear amplification processes.

Teriba, Folashade↗

All-optical phase conjugation using diffractive wavefront processing

Abstract Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with applications ranging from imaging to beam focusing. Here, we present a diffractive wavefront processor to approximate all-optical phase conjugation. Leveraging deep learning, a set of diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated this wavefront processor by 3D-fabricating diffractive layers and performing OPC on phase distortions never seen during training. Employing terahertz radiation, our diffractive processor successfully performed OPC through a shallow volume that axially spans tens of wavelengths. We also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and multi-wavelength nature, this diffractive wavefront processor can be used for various applications, e.g., turbidity suppression and aberration correction across different spectral bands.

42 ENGINEERING↗

Integrated optical frequency division for microwave and mmWave generation

Abstract The generation of ultra-low-noise microwave and mmWave in miniaturized, chip-based platforms can transform communication, radar and sensing systems 1–3 . Optical frequency division that leverages optical references and optical frequency combs has emerged as a powerful technique to generate microwaves with superior spectral purity than any other approaches 4–7 . Here we demonstrate a miniaturized optical frequency division system that can potentially transfer the approach to a complementary metal-oxide-semiconductor-compatible integrated photonic platform. Phase stability is provided by a large mode volume, planar-waveguide-based optical reference coil cavity 8,9 and is divided down from optical to mmWave frequency by using soliton microcombs generated in a waveguide-coupled microresonator 10–12 . Besides achieving record-low phase noise for integrated photonic mmWave oscillators, these devices can be heterogeneously integrated with semiconductor lasers, amplifiers and photodiodes, holding the potential of large-volume, low-cost manufacturing for fundamental and mass-market applications 13 .

Science & Technology - Other Topics↗

Methodologies and strategies for detecting fiber orientation in polymeric fiber-reinforced composites

In this review paper different methods and techniques for representing fiber orientation in advanced polymer matrix composites are presented. A description of the effect of fiber orientation on processing, fabrication and mechanical properties of a composite material is presented. The paper discusses the mathematical modeling and modeling techniques for fiber structure representation in polymeric composites, with an emphasis on fiber orientation in a composite part. The paper is divided into two sections; namely—destructive techniques and non-destructive techniques. The capabilities and limitations of each technique with respect to fiber orientation detection and measurements are discussed.

composites↗

The influence of laser energy on deuterium emission characteristics from a Zircaloy-4 plasma

Laser-produced plasma coupled with optical emission spectroscopy (OES) is a promising technique for detecting certain isotopes, with unique capabilities such as standoff and rapid detection and minimal to no sample preparation requirements. The key figure-of-merit for isotopic analysis using optical spectroscopy tools is the linewidth relative to the isotope shift. Although the isotopes of hydrogen (1H, 2H, and 3H) possess large isotopic shifts (1H–2H ≈ 180 pm, 1H–3H ≈ 240 pm), being a light element, the H transitions are susceptible to various broadening mechanisms in the plasma environment. One of the critical parameters that influence the linewidth of a transition in an LPP is the incident laser energy. In the present study, we evaluated the role of laser energy on plume expansion dynamics, deuterium emission intensity, and linewidth in a nanosecond laser-produced Zircaloy-4 plasma. The changes in 2Hα emission intensity and linewidth were investigated for varying laser fluence and time after plasma onset. Spatially resolved and spatially integrated OES were performed and compared to investigate the emission spectral features and linewidth of 2Hα. Monochromatic two-dimensional time-resolved imaging was also performed to understand the morphology of the deuterium and protium emission relative to all species in the plume. Our results showed that 1Hα and 2Hα emissions predominantly occur closer to the target. Measurements of 2Hα linewidth approached similar values at later times of plasma evolution regardless of the laser energy. The linewidths of the 2Hα transition showed insignificant differences between spatially resolved and spatially integrated measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An updated technique to obtain explosive kinetics data on microsecond timescales

There are few techniques available for chemists to obtain time-to-explosion data with known temperature inputs at the early stages of the design and synthesis of new explosives. In the 1960s, a technique was developed to rapidly heat milligram-quantities of confined explosives to ~1000 K on microsecond timescales. Wenograd loaded explosives inside stainless steel hypodermic needles, connected them to a fireset and rapidly discharged a capacitor through the steel. He obtained the temperature by measuring the needle resistance in a Wheatstone bridge arrangement and the time to explosion from a needle rupture. However, owing to the narrow-gauge needles used in the original research, the experiment was only possible with melt-castable explosives; it was never replicated, and modern diagnostics are now available with advances beyond the 1960s. Here, we report the development of the High Explosives Initiation Time (HEIT) test, which utilizes a 250 J pulsed power system to heat the needles. This work extends the Wenograd approach by using optical diagnostics, computational modeling, and advanced techniques to measure needle resistance and needle rupture. Preliminary rate information for pentaerythritol tetranitrate (PETN) will be presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Monitoring Sulfuric Acid and Temperature Using Raman Spectroscopy and Multivariate Chemometrics

Multivariate regression models were optimized for the quantification of sulfuric acid (H 2 SO 4 ) [0–8 M] and temperature (20 °C–80 °C) in the presence of ammonium sulfate ((NH 4 ) 2 SO 4 [0–0.6 M]) using Raman spectroscopy. Optical vibrational spectroscopy is a useful nondestructive technique for the in situ analysis of complex chemical systems notoriously difficult to monitor in situ and in real-time. Multivariate analysis, a chemometrics method, can be paired with these nondestructive optical methods for determining analyte concentration and speciation in complex solutions, such as dissociated species in polyprotic acids, e.g., H 2 SO 4 . The effect of temperature is often overlooked although it can have a major influence on speciation and the corresponding Raman spectra. Here, in this study, partial least squares regression models were optimized for the quantification of H 2 SO 4 and its two deprotonated forms as a function of temperature. Measuring bisulfate as a function of temperature is particularly challenging owing to changes in the second dissociation constant. A designed training set effectively minimized the sample set size and trained a robust predictive model with percent root mean square error of <3% for H 2 SO 4 . The practical strategy employed here was demonstrated to be effective for building chemometric models that directly account for dynamic temperatures with static samples and is shown to be amenable to flow cell analysis applications with a simple calibration transfer for process monitoring applications.

D-optimal design↗

Phonon second harmonic generation in NaBr studied by inelastic neutron scattering and computer simulation

The phenomenon of second harmonic generation (SHG) was found for phonons in anharmonic NaBr by inelastic neutron scattering. The temperature dependence of this phonon SHG was measured from 300 K to 650 K. At 300 K the second harmonic (SH) is seen as a high-energy branch around 33 meV, nearly independent of $\overrightarrow{Q}$. The temperature effective potential (TDEP) method and classical molecular dynamics (MD) simulation with machine learning interatomic potential were able to reproduce the SH, and showed that SHG occurs with the flat transverse optical (TO) phonon branch. A classical model of a nonlinear medium explains the intensity and lifetime of the SH, compared to those of the TO modes. Also successful was a quantum model based on the Heisenberg-Langevin equation for interacting phonons coupled to a thermal bath, which also predicts a spectral distribution of the SH. In conclusion, the measured temperature dependence of the intensity of the second harmonic showed that it follows the Planck distribution of a one-phonon quasiparticle, and not two TO phonons.

36 MATERIALS SCIENCE↗

Probing Plasmonic Near-Fields in Oxide-Modified Aluminum Nanocubes Using Photon-Induced Near-Field Electron Microscopy

Plasmonic nanoparticles generate strong electric fields near their surface upon photoexcitation, enabling applications in sensing, spectroscopy, and photocatalysis. Electron microscopy techniques – such as cathodoluminescence and electron energy loss spectroscopy – have been leveraged to produce nanoscale maps of localized surface plasmon (LSP) modes. More recently, photon-induced near-field electron microscopy (PINEM) has emerged as a powerful technique for imaging evanescent near-fields generated by ultrafast laser excitation. In this work, we employ PINEM within an ultrafast electron microscope, complemented by numerical calculations to investigate how optical polarization, surface modification, and light intensity affect the evanescent fields associated with LSPs on oxide-modified aluminum nanocubes. Polarization control of the incident light field enables spatial mapping of the nanocube’s LSPs at the single particle level. Systematic variation of the oxide layer thickness reveals that increased coating thickness correlates with a stronger PINEM signal and a greater energy gain of probing electrons. Additionally, higher light intensities at fixed polarization and oxide coating further amplify the PINEM signal. These findings demonstrate the utility of PINEM as a high-resolution technique for optical near-field imaging and spectroscopy of single plasmonic nanoparticles. The ability to probe single particle behavior offers new opportunities for advancing the design and characterization of nanophotonic and plasmonic materials.

PINEM↗

Defect Engineering in Large‐Scale CVD‐Grown Hexagonal Boron Nitride: Formation, Spectroscopy, and Spin Relaxation Dynamics

Recently, numerous techniques have been reported for generating optically active defects in exfoliated hexagonal boron nitride (hBN), which hold transformative potential for quantum photonic devices. However, achieving on-demand generation of desirable defect types in scalable hBN films remains a significant challenge. Here, it is demonstrated that formation of negative boron vacancy defects, V B − , in suspended, large-area CVD-grown hBN is strongly dependent on the type of bombarding particles (ions, neutrons, and electrons) and irradiation conditions. In contrast to suspended hBN, defect formation in substrate-supported hBN is more complex due to the uncontrollable generation of secondary particles from the substrate, and the outcome strongly depends on the thickness of the hBN. Different defect types are identified by correlating spectroscopic and optically detected magnetic resonance features, distinguishing boron vacancies (formed by light ions and neutrons and emitting at 800 nm) from other optically active defects emitting at 650 nm assigned to anti-site nitrogen vacancy (N B V N ) and reveal the presence of additional “dark” paramagnetic defects that influence spin-lattice relaxation time (T 1 ) and zero-field splitting parameters, all of which strongly depend on the defect density. These results underscore the potential for precisely engineered defect formation in large-scale CVD-grown hBN, paving the way for the scalable fabrication of quantum photonic devices.

CVD↗

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗

DNA-PAINT Imaging with Hydrogel Imprinting and Clearing

Hydrogel-embedding is a versatile technique in fluorescence microscopy, offering stabilization, optical clearing, and the physical expansion of biological specimens. DNA-PAINT is a super-resolution microscopy approach based on the diffusion and transient binding of fluorescently labeled oligos, but its feasibility in hydrogels has not yet been explored. In this study, we demonstrate that polyacrylamide hydrogels support sufficient diffusion for effective DNA-PAINT imaging. Using acrydite-anchored oligonucleotides imprinted from patterned DNA origami nanostructures and microtubule filaments in fixed cells, we find that hydrogel embedding preserves docking strand positioning at the nanoscale. Sample clearing via protease treatment had minor structural effects on the microtubule structure and enhanced diffusion and accessibility to hydrogel-imprinted docking strands. Our work demonstrates promising potential for diffusion and binding-based fluorescence imaging applications in hydrogel-embedded samples.

DNA origami↗

Low-temperature formation of Ti2AlN during post-deposition annealing of reactive multilayer systems

M n+1 AXn-phase Ti 2 AlN thin-films were synthesized using reactive sputtering-based methods involving the deposition of single-layer TiAlN, and Ti/AlN and TiN/TiAl multilayers of various modulation periods at ambient temperature and subsequent annealing at elevated temperatures. Ex situ and in situ x-ray diffraction measurements were used to characterize the Ti 2 AlN formation temperature and phase fraction. During annealing, Ti/AlN multilayers yielded Ti 2 AlN at a significantly lower in situ temperature of 650 °C compared to TiN/TiAl multilayers or single-layer TiAlN (750 °C). The results suggest a reactive multilayer mechanism whereby distinct Ti and AlN layers react readily to release exothermic energy resulting in lower phase transition temperatures compared to TiN and TiAl layers or mixed TiAlN. With a modulation period of 5 nm, however, Ti/AlN multilayers yielded Ti 2 AlN at a higher temperature of 750 °C, indicating a disruption of the reactive multilayer mechanism due to a higher fraction of low-enthalpy interfacial TiAlN within the film.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model

The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. Although a plethora of experimental techniques, including but not limited to optical contrast, Raman spectroscopy, nonlinear optical spectroscopy, near-field optical imaging, and hyperspectral imaging, facilitate the measurement of 2D material thickness, comprehensive data for many materials remain elusive. Over the past decade, the exponential proliferation of 2D materials and their heterostructures has outstripped the capabilities of conventional experimental and computational approaches. In this evolving landscape, machine learning (ML) has emerged as an indispensable tool, offering a scalable approach to augment these traditional methodologies. Addressing the critical gap, we introduce THICK2D—Thickness Hierarchy Inference and Calculation Kit for 2D Materials. This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. To demonstrate the utility and robustness of THICK2D, we successfully used the toolkit to predict the thickness of more than 8000 2D-based materials, sourced from two extensive 2D materials databases. THICK2D is disseminated as an open-source utility, accessible on GitHub at https://github.com/gmp007/THICK2D, and archived on Zenodo at https://10.5281/zenodo.11216648.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗