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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 451 records · Page 25

An Evaluation of Actinide Reactivity with CO 2 , O 2 , and O 2 /He Gases using Inductively Coupled Plasma Tandem Mass Spectrometry: Application to Simultaneous Measurement of 241 Am/ 241 Pu Ratios in Unseparated Complex Matrices

Accurate actinide measurements are critical within the field of nuclear science. Traditional methods for actinide quantification require time-consuming sample processing prior to analysis. There is a need for rapid analytical techniques that still maintain a high degree of accuracy. In this work, actinide reactivity was assessed for multiple oxygen-containing reaction gases using quadrupole inductively coupled plasma tandem mass spectrometry (Q-ICP-MS/MS) to evaluate actinide analysis in complex sample matrices without analyte-matrix separation. A novel method was developed to measure 241 Am/ 241 Pu in complex sample matrices using O 2 /He reaction gas with no matrix removal or analyte pre-concentration. This inline method reduces matrix-derived polyatomic interferences that complicate traditional ICP-MS analyses by mass-shifting to 241 Am 16 O + and 241 Pu 16 O 2 + , allowing Am and Pu to be mass separated for simultaneous analysis. While mass shifting is efficient, a small portion of Am + (<1.3%) and Pu + (<1.4%) react to from AmO 2 + and PuO + , respectively. Therefore, a mass balance approach was used, in combination with reactivity determined from 242 Pu and 243 Am standard solutions, to correct for residual 241 PuO + and 241 AmO 2 + . The method was validated by measuring 241 Am/ 241 Pu in Pu isotope standards CRM-136 and CRM-137 (separated in March/April 1970 and February 2022, respectively) in both neat solutions and complex matrices containing diluted soil (NIST SRM 2711a, >1000 µg·g -1 ). Method detection limits of 15.9 and 9.6 fg·g -1 were determined for 241 Am and 241 Pu, respectively, and 241 Am/ 241 Pu ratios were measured with accuracies within <3.5%. In conclusion, this work presents the first direct analysis of 241 Am/ 241 Pu in unseparated complex matrices, advancing capabilities for rapid actinide measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the Activity and Selectivity of Bimetallic Metal Catalysts for Ethanol Reforming using Machine Learning

Machine learning is ideally suited for the pattern detection in large uniform datasets, but consistent experimental datasets on catalyst studies are often small. Here we demonstrate how a combination of machine learning and first-principles calculations can be used to extract knowledge from a relatively small set of experimental data. The approach is based on combining a complex machine-learning model trained on an extensive computational library of transition-state energies with simple linear regression models of experimental catalytic activities and selectivities from the literature. Using the combined model, we identify the key C–C bond scission reactions involved in ethanol reforming and perform a computational screening for ethanol reforming on monolayer bimetallic catalysts with architectures TM-Pt-Pt(111) and Pt-TM-Pt(111) (TM = 3d transition metals). The model also predicts four promising catalyst compositions for future experimental studies. In conclusion, the approach is not limited to ethanol reforming but is of general use for the interpretation of experimental observations as well as for the computational discovery of novel catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomistic insights into the nucleation and growth of platinum on palladium nanocrystals

Abstract Despite the large number of reports on colloidal nanocrystals, very little is known about the mechanistic details in terms of nucleation and growth at the atomistic level. Taking bimetallic core-shell nanocrystals as an example, here we integrate in situ liquid-cell transmission electron microscopy with first-principles calculations to shed light on the atomistic details involved in the nucleation and growth of Pt on Pd cubic seeds. We elucidate the roles played by key synthesis parameters, including capping agent and precursor concentration, in controlling the nucleation site, diffusion path, and growth pattern of the Pt atoms. When the faces of a cubic seed are capped by Br − , Pt atoms preferentially nucleate from corners and then diffuse to edges and faces for the creation of a uniform shell. The diffusion does not occur until the Pt deposited at the corner has reached a threshold thickness. At a high concentration of the precursor, self-nucleation takes place and the Pt clusters then randomly attach to the surface of a seed for the formation of a non-uniform shell. These atomistic insights offer a general guideline for the rational synthesis of nanocrystals with diverse compositions, structures, shapes, and related properties.

36 MATERIALS SCIENCE↗

Forecasting of in situ electron energy loss spectroscopy

Abstract Forecasting models are a central part of many control systems, where high-consequence decisions must be made on long latency control variables. These models are particularly relevant for emerging artificial intelligence (AI)-guided instrumentation, in which prescriptive knowledge is needed to guide autonomous decision-making. Here we describe the implementation of a long short-term memory model (LSTM) for forecasting in situ electron energy loss spectroscopy (EELS) data, one of the richest analytical probes of materials and chemical systems. We describe key considerations for data collection, preprocessing, training, validation, and benchmarking, showing how this approach can yield powerful predictive insight into order-disorder phase transitions. Finally, we comment on how such a model may integrate with emerging AI-guided instrumentation for powerful high-speed experimentation.

36 MATERIALS SCIENCE↗

Combinatorial measurement of critical cooling rates in aluminum-base metallic glass forming alloys

Direct measurement of critical cooling rates has been challenging and only determined for a minute fraction of the reported metallic glass forming alloys. Here, we report a method that directly measures critical cooling rate of thin film metallic glass forming alloys in a combinatorial fashion. Based on a universal heating architecture using indirect laser heating and a microstructure analysis this method offers itself as a rapid screening technique to quantify glass forming ability. We use this method to identify glass forming alloys and study the composition effect on the critical cooling rate in the Al–Ni–Ge system where we identified Al 51 Ge 35 Ni 14 as the best glass forming composition with a critical cooling rate of 10 4 K/s.

36 MATERIALS SCIENCE↗

Low-temperature sprayed SnO x nanocomposite films with enhanced hole blocking for efficient large area perovskite solar cells

Scalable fabrication of charge transport layers with high uniformity and compactness is essential for the commercialization of perovskite solar cells (PSCs). Cost-effective deposition of high-quality electron transport layers (ETLs) is a particularly important step to achieve low-cost, efficient and large-area PSCs. Here, an open-air (relative humidity of 40–50%) and low-temperature (≤100 °C) ultrasonic spray coating of tin oxide (SnO 2 ) nanocomposite films incorporating nanocrystalline SnO 2 nanoparticles in an amorphous SnO x matrix is demonstrated to fabricate large-area ETLs for planar PSCs. The optimized SnO 2 /SnO x nanocomposite exhibits significantly enhanced hole-blocking and high-power conversion efficiencies of 18% and 16% for planar PSCs with an active area of 0.2 cm 2 and 1 cm 2 , respectively. More importantly, the devices show little current–voltage hysteresis as well as good shelf-life stability by maintaining ~90% of the initial performance without encapsulation after 2500 hours storage under inert conditions. Additionally, high voltages of >6.0 V have been obtained for solar modules of 2.1 cm 2 aperture area comprising six sub-cells in series, suggesting that the low-temperature, open-air and fast spray coating is suitable and transferable to deposit large-area charge transport layers for scalable PSCs or other optoelectronic devices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Robotic automation of droplet microfluidics

Droplet microfluidics enables powerful analytic capabilities but often requires workflows involving macro- and microfluidic processing steps that are cumbersome to perform manually. Here, we demonstrate the automation of droplet microfluidics with commercial fluid-handling robotics. The workflows incorporate common microfluidic devices including droplet generators, mergers, and sorters and utilize the robot's native capabilities for thermal control, incubation, and plate scanning. The ability to automate microfluidic devices using commercial fluid handling will speed up the integration of these methods into biological workflows.

59 BASIC BIOLOGICAL SCIENCES↗

Synthesis of La 2–x Sr x CuO 4 films via atomic layer-by-layer molecular beam epitaxy

Atomic layer-by-layer molecular beam epitaxy (ALL-MBE) is a sophisticated technique to synthesize high-temperature superconductor (HTS) materials. ALL-MBE produces single-crystal HTS films with atomically smooth surfaces and interfaces, as well as precise multilayer heterostructures engineered down to a single atomic layer level. This enables the fabrication of tunnel junctions, nanowires, nanorings, and other HTS devices of interest. Our group has focused on ALL-MBE synthesis and materials science of La 2–x Sr x CuO 4 (LSCO), a representative HTS cuprate. In the past two decades, we have synthesized over three thousand LSCO thin films and characterized them by a range of analytical techniques. Here, we present in full detail a systematic process for the synthesis and engineering of atomically perfect LSCO films. The procedure includes the preparation of substrates, calibration of the elemental sources, the recipe for ALL growth of LSCO films without any secondary-phase precipitates, post-growth annealing of the films, and ex situ film characterization. This report should aid replication and dissemination of this technique of synthesizing single-crystal LSCO films for basic research as well as for HTS electronic applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Shock state distributions in porous tantalum and characterization with multipoint velocimetry

Heterogenous materials under shock compression can be expected to reach different shock states throughout the material according to local differences in microstructure and the history of wave propagation. Here, in this work, a compact, multiple-beam focusing optic assembly is used with high-speed velocimetry to interrogate the shock response of porous tantalum films prepared through thermal-spray deposition. The distribution of particle velocities across a shocked interface is compared to results obtained using a set of defocused interferometric beams that sampled the shock response over larger areas. The two methods produced velocity distributions along the shock plateau with the same mean, while a larger variance was measured with narrower beams. The finding was replicated using three-dimensional, mesoscopically resolved hydrodynamics simulations of solid tantalum with a pore structure mimicking statistical attributes of the material and accounting for radial divergence of the beams, with agreement across several impact velocities. Accounting for pore morphology in the simulations was found to be necessary for replicating the rise time of the shock plateau. The validated simulations were then used to show that while the average velocity along the shock plateau could be determined accurately with only a few interferometric beams, accurately determining the width of the velocity distribution, which here was approximately Gaussian, required a beam dimension much smaller than the spatial correlation lengthscale of the velocity field, here by a factor of ∼30×, with implications for the study of other porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protecting backaction-evading measurements from parametric instability

Noiseless measurement of a single quadrature in systems of parametrically coupled oscillators is theoretically possible by pumping at the sum and difference frequencies of the two oscillators, realizing a backaction-evading (BAE) scheme. Although this would hold true in the simplest scenario for a system with pure three-wave mixing, implementations of this scheme are hindered by unwanted higher-order parametric processes that destabilize the system and add noise. We show analytically that detuning the two pumps from the sum and difference frequencies can stabilize the system and fully recover the BAE performance, enabling operation at otherwise inaccessible cooperativities. We also show that the acceleration demonstrated in a weak-signal-detection experiment [Jiang , PRX Quantum 4, 020302 (2023)] was only achievable because of this detuning technique.

Ruddy, E. P.↗

Characterization of a Low-Temperature Plasma (LTP) Ambient Ionization Source Using Temporally Resolved Monochromatic Imaging Spectrometry

The low-temperature plasma (LTP) probe is a common plasma-based source used for ambient desorption–ionization mass spectrometry (MS). While the LTP probe has been characterized in detail with MS, relatively few studies have used optical spectroscopy. In this paper, two-dimensional (2D) imaging at selected wavelengths is used to visualize important species in the LTP plasma jet. First, 2D steady-state images of the LTP plume for N 2 + (391.2 nm), He I (706.5 nm), and N 2 (337.1 nm) emissions were recorded under selected plasma conditions. Second, time-resolved 2D emission maps of radiative species in the LTP plasma jet were recorded through the use of a 200 ns detection gate and varying gate delays with respect to the LTP trigger pulse. Emission from He I, N 2 + , and N 2 in the plasma jet region was found to show a transient behavior (often referred to as plasma bullets) lasting only a few microseconds. The N 2 + and He I maps were highly correlated in spatial and temporal structure. Further, emission from N 2 showed two maxima in time, one before and one after the maximum emission for N 2 + and He I, due to an initial electronic excitation wave and ion–electron recombination, respectively. Third, the interaction of the LTP probe with a sample substrate and an electrically grounded metallic needle was studied. Emission from a fluorophore on the sample substrate showed an initial photon-induced excitation from plasma-generated photons followed by electronic excitation by other plasma species. The presence of a grounded needle near the plasma jet significantly extended the plasma jet lifetime and also generated a long-lived corona discharge on the needle. The effect of LTP operating parameters on emission spectra was correlated with mass-spectral results including reagent-ion signals. Lastly, five movies provide a side-by-side comparison of the temporal behavior of emitting species and insights into the interactions of the emission clouds with a sample surface as well as an external needle. Temporally and spatially resolved imaging provided insights into important processes in the LTP plasma jet, which will help improve analyte ion sampling in LTP–MS.

Chan, George C. -Y.↗

Holo-omics for deciphering plant-microbiome interactions

Host-microbiome interactions are recognized for their importance to host health. An improved understanding of the molecular underpinnings of host-microbiome relationships will advance our capacity to accurately predict host fitness and manipulate interaction outcomes. Within the plant microbiome research field, unlocking the functional relationships between plants and their microbial partners is the next step to effectively using the microbiome to improve plant fitness. We propose that strategies that pair host and microbial datasets—referred to here as holo-omics—provide a powerful approach for hypothesis development and advancement in this area. We discuss several experimental design considerations and present a case study to highlight the potential for holo-omics to generate a more holistic perspective of molecular networks within the plant microbiome system. In addition, we discuss the biggest challenges for conducting holo-omics studies; specifically, the lack of vetted analytical frameworks, publicly available tools, and required technical expertise to process and integrate heterogeneous data. Finally, we conclude with a perspective on appropriate use-cases for holo-omics studies, the need for downstream validation, and new experimental techniques that hold promise for the plant microbiome research field. We argue that utilizing a holo-omics approach to characterize host-microbiome interactions can provide important opportunities for broadening system-level understandings and significantly inform microbial approaches to improving host health and fitness.

59 BASIC BIOLOGICAL SCIENCES↗

Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of 0.33% and an LoD of 0.015% for quantification of Ga in a Ce matrix. This study concludes that these machine learning methods could yield robust prediction models for rapid quality control analysis of plutonium alloys.

Rao, Ashwin P. (ORCID:0000000319312568)↗

Determination of the nonlinear thermo-optic coefficient of silicon nitride and oxide using an effective index method

There is little literature characterizing the temperature-dependent thermo-optic coefficient (TOC) for low pressure chemical vapor deposition (LPCVD) silicon nitride or plasma enhanced chemical vapor deposition (PECVD) silicon dioxide at temperatures above 300 K. In this study, we characterize these material TOC’s from approximately 300-460 K, yielding values of (2.51 ± 0.08) · 10 −5 K −1 for silicon nitride and (5.67 ± 0.53) · 10 −6 K −1 for silicon oxide at room temperature (300 K). We use a simplified experimental setup and apply an analytical technique to account for thermal expansion during the extraction process. We also show that the waveguide geometry and method used to determine the resonant wavelength have a substantial impact on the precision of our results, a fact which can be used to improve the precision of numerous ring resonator index sensing experiments.

36 MATERIALS SCIENCE↗

Final Technical Report: Testing the robustness of CMB-S4 inflation measurements to foreground models

This report summarizes the research activities for DOE award SC0024462, which focused on enhancing the robustness of CMB-S4 inflation measurements by characterizing and mitigating Galactic foreground interference. The project grounded foreground models in the physical processes of the Interstellar Medium with MHD and semi-analytic filament models, and developed analysis pipelines, such as Needlet Internal Linear Combination (NILC) techniques, to isolate faint cosmological signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Chocolate Chip Cookie Model: Dust Geometry of Milky Way–like Disk Galaxies

We present a new two-component dust geometry model, the Chocolate Chip Cookie model, where the clumpy nebular regions are embedded in a diffuse stellar/interstellar medium disk, like chocolate chips in a cookie. By approximating the binomial distribution of the clumpy nebular regions with a continuous Gaussian distribution and omitting the dust scattering effect, our model solves the dust attenuation process for both the emission lines and stellar continua via analytical approaches. Our Chocolate Chip Cookie model successfully fits the inclination dependence of both the effective dust reddening of the stellar components derived from stellar population synthesis and that of the emission lines characterized by the Balmer decrement for a large sample of Milky Way–like (MW-like) disk galaxies selected from the main galaxy sample of the Sloan Digital Sky Survey. Our model shows that the clumpy nebular disk is about 0.55 times thinner and 1.6 times larger than the stellar disk for MW-like galaxies, whereas each clumpy region has a typical optical depth of τ cl,V ~ 0.5 in the V band. After considering the aperture effect, our model prediction on the inclination dependence of dust attenuation is also consistent with observations. Not only that, in our model, the dust attenuation curve of the stellar population naturally depends on the inclination, and its median case is consistent with the classical Calzetti law. As the modeling constraints are from the optical wavelengths, our model is unaffected by the optically thick dust component, which however could bias the model's prediction of the infrared emissions.

79 ASTRONOMY AND ASTROPHYSICS↗