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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fatty acid capped, metal oxo clusters as the smallest conceivable nanocrystal prototypes

Metal oxo clusters of the type M 6 O 4 (OH) 4 (OOCR) 12 (M = Zr or Hf) are valuable building blocks for materials science. Here, we synthesize a series of zirconium and hafnium oxo clusters with ligands that are typically used to stabilize oxide nanocrystals (fatty acids with long and/or branched chains). The fatty acid capped oxo clusters have a high solubility but do not crystallize, precluding traditional purification and single-crystal XRD analysis. We thus develop alternative purification strategies and we use X-ray total scattering and Pair Distribution Function (PDF) analysis as our main method to elucidate the structure of the cluster core. We identify the correct structure from a series of possible clusters (Zr3, Zr4, Zr6, Zr12, Zr10, and Zr26). Excellent refinements are only obtained when the ligands are part of the structure model. Further evidence for the cluster composition is provided by nuclear magnetic resonance (NMR), infrared spectroscopy (FTIR), thermogravimetry analysis (TGA), and mass spectrometry (MS). We find that hydrogen bonded carboxylic acid is an intrinsic part of the oxo cluster. Using our analytical tools, we elucidate the conversion from a Zr6 monomer to a Zr12 dimer (and vice versa), induced by carboxylate ligand exchange. Finally, we compare the catalytic performance of Zr12-oleate clusters with oleate capped, 5.5 nm zirconium oxide nanocrystals in the esterification of oleic acid with ethanol. The oxo clusters present a five times higher reaction rate, due to their higher surface area. Since the oxo clusters are the lower limit of downscaling oxide nanocrystals, we present them as appealing catalytic materials, and as atomically precise model systems. In addition, the lessons learned regarding PDF analysis are applicable to other areas of cluster science as well, from semiconductor and metal clusters, to polyoxometalates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology↗
DOE OSTI2020

Impact of moderate pump–Stokes chirp on femtosecond coherent anti-Stokes Raman scattering spectra

The effects of inducing moderate chirp in the pump and Stokes beams in chirped-probe-pulse femtosecond coherent anti-Stokes Raman scattering (CARS) spectroscopy are discussed. This is an important issue for measurements in high-pressure systems where the CARS beams must be transmitted through glass of significant thickness to reach the probe volume of interest. The effects were investigated both experimentally, by inserting disks of SF-11 glass into the pump and Stokes beam paths, and theoretically, by incorporating pulse chirp into our time-dependent density matrix (TDDM) simulations. Experimentally, we found that inducing moderate pump and Stokes chirp produced significant spectral narrowing of the nonresonant four-wave mixing contribution to the CARS signal, and this allowed us to control the resonant excitation bandwidth to eliminate interferences from neighboring species. The temperature measurement accuracy and precision were essentially unchanged with respect to the unchirped pump and Stokes case. The effect of moderate pump and Stokes chirp on the narrowing of the Raman excitation efficiency envelope was investigated by solving the full set of TDDM through direct numerical integration. The numerical efficiency of the solutions was enhanced dramatically by developing a parallel version of the TDDM code. The calculated Raman excitation efficiency profile was incorporated in our phenomenological spectral fitting codes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Automatic Search of Cataclysmic Variables Based on LightGBM in LAMOST-DR7

The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Volcano‐like Activity Trends in Au@Pd Catalysts: The Role of Pd Loading and Nanoparticle Size

The addition of palladium (Pd) to preformed gold nanoparticles (Au NPs) enables the formation of core‐shell structures with enhanced catalytic performance in oxidation reactions. However, predicting the precise palladium content required to achieve maximum catalytic activity remains difficult based on current understanding. Herein, Pd was systematically introduced onto titania‐supported Au NPs (2, 6, and 10 nm) to evaluate their performance in benzyl alcohol oxidation. A volcano‐like trend in catalytic activity was observed, where activity increased with Pd addition, peaked, and then declined. The Pd loading required for maximum activity depended on Au NP size: ≈40 at% Pd/Au for 2.6 nm, ≈20 at% Pd/Au for 6.4 nm, and ≈12.5 at% Pd/Au for 10.6 nm. For Au NPs > 6 nm, peak activity aligned with monolayer Pd coverage, while for smaller NPs (2–3 nm), optimal Pd content was below monolayer predictions. X‐ray absorption spectroscopy revealed a core‐shell structure at low Pd content, but higher Pd loadings led to Pd diffusion into the Au core. This structural transformation likely caused activity decline, indicating that AuPd alloying negatively impacts catalysis. These results highlight that core‐shell Au@Pd catalysts outperform AuPd alloys and provide crucial insights for designing highly active bimetallic catalysts.

X-ray absorption spectroscopy↗
DOE OSTI2025

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Copper Clusters Containing Hydrides in Trigonal Pyramidal Geometry

Structurally precise copper hydrides [Cu 11 H 2 {S 2 P(O i Pr) 2 } 6 (C≡CR) 3 ], R = Ph (1), C 6 H 4 F (2), and C 6 H 4 OMe (3), were first synthesized from the polyhydrido copper cluster [Cu 20 H 11 {S 2 P(O i Pr) 2 } 9 ] with nine equivalents of terminal alkynes. Later, their isolated yields were significantly improved by direct synthesis from [Cu(CH 3 CN) 4 ](PF 6 ), [NH 4 ][S 2 P(O i Pr) 2 ], NaBH 4 , and alkynes along with NEt 3 in THF. 1, 2, and 3 were fully characterized by single-crystal X-ray diffraction, ESI-MS, and multinuclear NMR spectroscopy. All three clustershave 11 copper atoms, adopting 3,3,4,4,4-pentacapped trigonal prismatic geometry, with two hydrides inside the Cu 11 cage, the position of which was ascertained by a single-crystal neutron diffraction structure of cluster 1 co-crystallized with a [Cu 7 (H){S 2 P(O i Pr) 2 } 6 ] (4) cluster. Six dithiophosphate and three alkynyl ligands stabilize the Cu 11 H 2 core in which the two hydrides adopt a trigonal pyramidal coordination mode. This coordination mode is so far unprecedented for hydride. The 1 H NMR resonance frequency of the two hydrides appears at 4.8 ppm, a value further confirmed by 2 H NMR spectroscopy for their deuteride derivatives [Cu 11 (D) 2 {S 2 P(O i Pr) 2 } 6 (C≡CR) 3 ]. A DFT investigation allows understanding the bonding within this new type of copper(I) hydrides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Interfacial Unit-Dependent Catalytic Activity for CO Oxidation over Cerium Oxysulfate Cluster Assemblies

Atomically precise cerium oxo clusters offer a platform to investigate structure–property relationships that are much more complex in the ill-defined bulk material cerium dioxide. We investigated the activity of the MCe 70 torus family (M = Cd, Ce, Co, Cu, Fe, Ni, and Zn), a family of discrete oxysulfate-based Ce 70 rings linked by monomeric cation units, for CO oxidation. CuCe 70 emerged as the best performing MCe 70 catalyst among those tested, prompting our exploration of the role of the interfacial unit on catalytic activity. Temperature-programmed reduction (TPR) studies of the catalysts indicated a lower temperature reduction in CuCe 70 as compared to CeCe 70 . In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) indicated that CuCe 70 exhibited a faster formation of Ce 3+ and contained CO bridging sites absent in CeCe 70 . Isothermal CO adsorption measurements demonstrated a greater uptake of CO by CuCe 70 as compared to CeCe 70 . The calculated energies for the formation of a single oxygen defect in the structure significantly decreased with the presence of Cu at the linkage site as opposed to Ce. Furthermore, this study revealed that atomic-level changes in the interfacial unit can change the reducibility, CO binding/uptake, and oxygen vacancy defect formation energetics in the MCe 70 family to thus tune their catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Realization of a high luminosity muon beam at the Jefferson Lab

The proton is the major component of the visible matter of our universe, so being able to determine its fundamental properties, such as its charge radius, is of vital importance. In recent years, several experiments have been performed for the accurate measurement of the proton radius with different experimental techniques. The main and most common are based on two different techniques: ep scattering and Lamb shift spectroscopy of regular hydrogen atoms. The latter can also be performed on muonic hydrogen atoms with a significant improvement in accuracy. Recent measurements that use this method have highlighted a discrepancy between the results obtained with the diffusion of electrons and those obtained with the spectroscopic technique leading to the so-called ?proton radius puzzle?. The explanation of why this difference between the measured values exists is still a matter of discussion. The last attempt to address the puzzle was the PRad Experiment. It was performed with a unique experimental setup that gave the scientists an excellent control on the systematic errors that are usually present in electron-proton scattering experiments. This has significantly increased the precision of the measurement, bringing it in the same area as the spectroscopic ones done on muonic hydrogen atoms, which are considered the most precise. However, to solve the puzzle once and for all, even more precise electron scattering measurements are needed. Alternatively, new methods can be used, such as eg. muon-proton scattering at low transferred momenta in order to lower the systematic errors that comes with the measurement. This thesis tries to address this problem by studying the set up of an intense muon beam at the Jefferson Laboratory (JLab) that can be used to carry out a high-precision m ? p scattering experiment. Using Montecarlo simulations I studied the muon production resulting from the interaction of the primary electron beam with the beam-dump at JLab Hall-A. The simulations were performed using the FLUKA package via the FLAIR graphical interface. In this study, I modified an existing geometry (built for the ?Beam Dump eXperiment?) and performed several studies in order to optimize the muon beam parameters. In order to estimate the beam intensity, I studied the muon generation and transportation through the concrete bunker surrounding the Hall-A beam-dump. Detailed studies on muon attenuation and dispersion at different depth allowed me to track the beam profile in space and momentum as a function of the distance from the beam-dump. Last, but not least, I studied a possible tagging system for the muon beam. The tagging system will allow us to know with good precision (O(1=1000)) the energy of each muon of the beam. Based on the results obtained, I created an event generator that incorporates the detailed description of the muon beam (energy, position, emittance) useful to define and optimize the experimental setup for a future measurement of the proton radius at the JLab.

Fulci, Antonino↗
DOE OSTI2023

Characterization of mApple as a Red Fluorescent Protein for Cryogenic Single-Molecule Imaging with Turn-Off and Turn-On Active Control Mechanisms

Single-molecule superresolution microscopy is a powerful tool for the study of biological structures on size scales smaller than the optical diffraction limit. Imaging samples at cryogenic temperatures (77 K) reduces the quantum yield of photobleaching for many fluorescent labels, yielding localization precisions below 10 nm. Cryogenic imaging further enables correlation with cryogenic electron tomography. A key limitation in applying methods such as PALM and STORM to samples maintained at 77 K is the limited number of fluorophores known to undergo efficient turn-on and turn-off mechanisms necessary to control the sparsity of active emitters. Here we find that mApple, a red-emitting fluorescent protein, undergoes a novel turn-off mechanism in response to simultaneous illumination with two colors of light. This turn-off mechanism enables localization of many individual molecules in initially bright samples, but the final density of localizable emitters is limited by relatively inefficient turn-on (photoactivation). Bulk excitation and emission spectroscopy shows that mApple has access to two distinct emissive states as well as dark states accessible optically or through changes in pH. The bright and stable emission of mApple enables widefield collection of single-molecule emission spectra, which highlight the complex nature and environmental sensitivity of states observed in red fluorescent proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Percolated Ionic Aggregate Morphologies and Decoupled Ion Transport in Precise Sulfonated Polymers Synthesized by Ring-Opening Metathesis Polymerization

Here, we describe a set of precise single-ion conducting polymers that form self-assembled percolated ionic aggregates in glassy polymer matrices and have decoupled transport of metal cations. These precise single-ion conductors (SICs), synthesized by a scalable ring-opening metathesis polymerization, consist of a polyethylene backbone with a sulfonated phenyl group pendant on every fifth carbon and are fully neutralized by a counterion X + (Li + , Na + , or Cs + ). Experimental X-ray scattering measurements and fully atomistic molecular dynamics (MD) simulations are in good agreement. The MD simulations show that the ionic groups nanophase separate from the polymer backbone to form percolating ionic aggregates. Using graph theory, we find that within the Li + - and Na + -neutralized polymers the percolated aggregates exhibit planar and ribbon-like configurations at intermediate length scales, while the percolated aggregates within the Cs + -neutralized polymers are more isotropic. Electrical impedance spectroscopy measurements show that the ionic conductivities exhibit Arrhenius behavior, with conductivities of 10 –7 to 10 –6 S/cm at 180 °C. In the MD simulations, the cations move between sulfonate groups in the percolated aggregates, larger ions travel further, and overall cations travel further than the polymer backbones, indicating a decoupled ion-transport mechanism. Thus, the percolated ionic aggregates in these polymers can serve as pathways to facilitate decoupled ion motion through a glassy polymer matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

AuPd Nanoicosahedra: Atomic-Level Surface Modulation for Optimization of Electrocatalytic and Photocatalytic Energy Conversion

Modulation of bimetallic nanocatalysts with atomic precision would allow for significant increases in catalyst activity through the optimization of heteroatomic interplay. In practice, this level of control over homogeneously turning the heteroatomic states in the surface regions of catalysts remains a great challenge for practical applications requiring mass production. In this work, a one-step aqueous strategy for preparation of AuPd nanoicosahedra core–shell structures has been developed. By turning the molar ratio of Au and Pd precursors, the nanoicosahedra could be made with uniform core composition (Pd ~20%) and largely flexible surface compositions (Pd: 20–70%). Under model reactions of electrochemical ethanol oxidation (EOR) and 4-nitrophenol (4-NP) reduction, the Au 55 Pd 45 surface displayed superior activities. Here, x-ray absorption spectroscopy revealed that AuPd nanoicosahedra with Pd-poor surfaces (Au 79 Pd 21 and Au 60 Pd 40 ) maintain Au-like electronic structures while those with Pd-rich surfaces are more Pd-like. The Au 55 Pd 45 surface struck a delicate balance between the two extremes, leading to the optimal Au–Pd interplay for catalytic performance. Overall, the development of a one-step aqueous strategy for atomic-level control over bimetallic nanoparticle surface states is an important milestone for future advances in catalysis. Our findings in atomic-scale catalyst design will bring deep insights into the fields of nanosynthesis and heterogeneous catalysis, which will be beneficial for further scientific breakthroughs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Tailoring the Near-Surface Environment of Rh Single-Atom Catalysts for Selective CO 2 Hydrogenation

For this study, we used a combination of experimental spectroscopies, density functional theory calculations, and CO 2 hydrogenation studies to investigate the effects of modifying single-atom Rh 1 /TiO 2 catalysts with functionalized phosphonic acid monolayers. We found that the deposition of specific amine-functionalized ligands resulted in an ~8× increase in site-specific CO 2 reduction turnover frequency at 150 °C and a ~2× increase at 250 °C. On-stream stability also improved following ligand deposition. The effect of the modifier on reactivity was highly sensitive to the proximity of the amine functional group to the surface, which was controlled by adjusting the length of the phosphonic acid tail. Furthermore, deposition of alkyl phosphonic acids without an amine functional group resulted in blocked CO 2 adsorption and a near-complete loss of catalytic activity. Infrared spectroscopy studies suggested that the amine group provided binding sites for CO 2 that enabled hydrogenation when the amine was positioned near a Rh1 site. Phosphonic acid-modified catalysts also exhibited high selectivity to CO over the series product methane; the selectivity effect was traced to modification of the Rh1 sites to favor CO desorption. Phosphonic acid deposition resulted in 80–90% loss of accessible Rh1 sites, likely due to blocking by tail groups. However, even with the loss of sites, under low-temperature reaction conditions, the rates of CO 2 hydrogenation were improved with the coatings, indicating that the remaining sites are highly efficient. Organic functionalization of the supports for atomically dispersed catalysts offers the opportunity to precisely control the positioning of functional groups in the vicinity of a well-defined active site, potentially enabling an additional level of control over active site design.

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

Rapid spatial analysis of surrogate TRISO fuel particles using laser-induced breakdown spectroscopy image analysis

Laser-induced breakdown spectroscopy (LIBS) mapping enables rapid elemental and spatial analysis of solid samples. In this work, surrogate TRi-structural ISOtropic (TRISO) particles with various layers consisting of Zr, W, C, and Si were used to demonstrate the use of a new thickness measurement tool developed to analyze elemental images generated from LIBS maps. Zr particles with varying outer-layer thicknesses ranging from 16 to 32 μm were measured with scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) and LIBS with both a complementary metal-oxide-semiconductor (CMOS) detector and an intensified charged coupled device (ICCD) detector. LIBS maps of particles were completed using CMOS and ICCD spectrometers with effective spatial resolutions of 4 and 2 μm, respectively. The novel thickness measurement tool identified layer regions within a LIBS map and then identified the locations of the boundaries between these layers. The tool then generated up to 1000 random profiles stemming radially from the center region, which were used to measure the layer thickness/radius. This image analysis tool demonstrated LIBS's ability to provide values comparable with SEM-EDS (3.7% relative difference) along with a 95% reduction in measurement time. Furthermore, the precision of these measurements was on par with the SEM-EDS measurements at <15% relative standard deviation. Following the analysis of the Zr particles, W particles with increased complexity (e.g., five versus three layers) were analyzed using both the CMOS and ICCD spectrometers simultaneously. The spatial dimensions were extracted with an average relative difference of 2.7% and an average relative standard deviation of 9%.

Andrews, Hunter B. [Oak Ridge National Laboratory ↗
DOE OSTI2021

25 Siβ + -decay spectroscopy

Background: β-decay spectroscopy provides valuable information on exotic nuclei and a stringent test for nuclear theories beyond the stability line. Purpose: To search for new β-delayed protons and γ rays of 25 Si to investigate the properties of 25 Al excited states. Method: 25 Si β decays were measured by using the Gaseous Detector with Germanium Tagging system at the National Superconducting Cyclotron Laboratory. The protons and γ rays emitted in the decay were detected simultaneously. Here, a Monte Carlo method was used to model the Doppler broadening of 24 Mg γ-ray lines caused by nuclear recoil from proton emission. Shell-model calculations using two newly developed universal sd-shell Hamiltonians were performed. Results: The most precise 25Si half-life to date has been determined. A new proton branch at 724(4) keV and new proton-γ-ray coincidences have been identified. Three 24 Mg γ-ray lines and eight 25 Al γ-ray lines are observed for the first time in 25 Si decay. The first measurement of the 25 Si β-delayed γ-ray intensities through the 25 Al unbound states is reported. All the bound states of 25 Al are observed to be populated in the β decay of 25 Si. Several inconsistencies between the previous measurements have been resolved, and new information on the 25 Al level scheme is provided. An enhanced decay scheme has been constructed and compared to the mirror decay of 25 Na and the shell-model calculations. Conclusions: The measured excitation energies, γ-ray and proton branchings, log $ft$ values, and Gamow-Teller transition strengths for the states of 25 Al populated in the β decay of 25 Si are in good agreement with the shell model calculations, offering gratifyingly consistent insights into the fine nuclear structure of 25 Al.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

InAs Terahertz Metalens Emitter for Focused Terahertz Beam Generation

Metasurfaces have opened doors to combining multiple photonic functionalities in a single compact device. In particular, the ability to generate short terahertz (THz) pulses with precise wavefront engineering in a single THz metasurface redefined the role metasurfaces can play in THz systems. Here, an InAs metalens emitter which generates and focuses a THz pulse beam is demonstrated using a 130 nm thick InAs metasurface designed as a binary‐phase Fresnel zone plate. The THz beam is focused to a spot of ≈430 μm at 1 THz with a short focal length of 5 mm and large numerical aperture of 0.5. Nanoscale InAs Mie resonators comprising the metasurface enable THz generation with an amplitude as high as 20 times compared to plasmonic THz emitters and several times compared to a 1 mm thick ZnTe crystal. This InAs metasurface emitter provides a new paradigm for designing THz imaging, spectroscopy, and communication systems, where THz beam generation and shaping are performed with a single device without compromising the generation efficiency, while eliminating losses and avoiding limitations of phase matching of conventional nonlinear optics approaches.

47 OTHER INSTRUMENTATION↗