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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-throughput micro-scale bandgap mapping for perovskite-inspired materials with complex composition space

Abstract To realize the full promise of high-throughput experimental workflows, the rate of sample synthesis must be matched by that of characterization. Of growing interest are contactless optical techniques that can rapidly measure material homogeneity and properties. Here, we present a hyperspectral imaging method to measure local optical bandgap distributions within samples, utilizing spatially-resolved reflectance spectra coupled with automated data analysis. We collect approximately one million optical bandgap data across the compositional space of Cs 3 (Bi x Sb 1-x ) 2 (Br y I 1-y ) 9 perovskite-inspired materials. Our results show non-monotonic bandgap variations (i.e., bandgap bowing) along six composition gradient sequences, in addition to identifying samples with multiple bandgaps in statistics. High-throughput transient absorption spectroscopy reveals that within these compositions, the depletion of the ground state carriers to excited states occurred at discrete energy levels with independent carrier dynamics, consistent with the bandgap observation and indicative of phase separation. This work demonstrates the potential for rapid optical measurements to assess material quality and homogeneity in a high-throughput experimental setting, supporting screening and recipe optimization of optoelectronic material candidates with desired carrier dynamics and optical properties.

Science & Technology - Other Topics↗
DOE OSTI2023

A new approach for simulating inhomogeneous chemical kinetics

Abstract In this paper, inhomogeneous chemical kinetics are simulated by describing the concentrations of interacting chemical species by a linear expansion of basis functions in such a manner that the coupled reaction and diffusion processes are propagated through time efficiently by tailor-made numerical methods. The approach is illustrated through modelling $$\alpha$$ α - and $$\gamma$$ γ -radiolysis in thin layers of water and at their solid interfaces from the start of the chemical phase until equilibrium was established. The method’s efficiency is such that hundreds of such systems can be modelled in a few hours using a single core of a typical laptop, allowing the investigation of the effects of the underlying parameter space. Illustrative calculations showing the effects of changing dose-rate and water-layer thickness are presented. Other simulations are presented which show the approach’s capability to solve problems with spherical symmetry (an approximation to an isolated radiolytic spur), where the hollowing out of an initial Gaussian distribution is observed, in line with previous calculations. These illustrative simulations show the generality and the computational efficiency of this approach to solving reaction-diffusion problems. Furthermore, these example simulations illustrate the method’s suitability for simulating solid-fluid interfaces, which have received a lot of experimental attention in contrast to the lack of computational studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Negative thermal expansion and the role of hybridization in perovskite-type PbTiO 3 -Bi(Cu 0.5 Ti 0.5) O 3

PbTiO 3 -BiMeO 3 ferroelectrics have attracted much attention due to not only their extremely large polarization and piezoelectricity but also their controllable thermal expansion. In this study, we present a new binary system of (1 - x)PbTiO 3 -xBi(Cu 0.5 Ti 0.5 )O 3 possessing large tetragonality and enhanced spontaneous polarization. Interestingly, a combination of near zero thermal expansion and negative thermal expansion over a temperature range of RT to T C (~550 °C) has been observed in tetragonal 0.85PbTiO 3 -0.15Bi(Cu 0.5 Ti 0.5 )O 3 . The comprehensive structure analysis addressed that the abnormal thermal expansion is coupled to the spontaneous volume ferroelectrostriction. Moreover, the chemical bonding investigation by a maximum entropy method further attests that the covalent hybridization of Pb/Bi–O bonds plays a vital role in the improved ferroelectricity and interacts with thermal vibration to dominate the crossover from positive to negative thermal expansion. fINALLY, The present studies would give direct evidence to verify the theoretical calculations and could be extended to reveal the nature of thermal expansion in ferroelectrics.

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

One-center close-coupling approach to two-center rearrangement collisions

Calculations of ionization and electron-capture cross sections in ion-atom collisions usually require solving the Schrödinger equation governing the collision system by expanding the total scattering wave function in a basis of target- and projectile-centered pseudostates. This approach leads to the two-center close-coupling equations which in some cases may become ill-conditioned due to the non-orthogonality of the underlying combined basis. Here we develop a technique which allows to accurately extract the necessary collision information, including that for the rearrangement channels, from the computationally more convenient one-center close-coupling equations which are built from only target-centered pseudostates. The robustness of the method is demonstrated by considering the proton-hydrogen scattering problem across a wide incident energy range. The developed method is then applied to study proton scattering on multielectron target of lithium. Here, the obtained results for the 2s → 2p excitation and the total electron-capture cross sections are in good agreement with corresponding experimental data. It is concluded that the presented technique could be a simpler alternative when integrated cross sections are required.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Third moments of nucleon unpolarized, polarized, and transversity parton distribution functions from physical-point lattice QCD

Using forward matrix elements of local leading-twist operators, we present a determination of the isovector third Mellin moments ⟨𝑥 2 ⟩ of nucleon unpolarized, polarized, and transversity parton distribution functions. Two lattice QCD ensembles at the physical pion mass are used, which were generated using a tree-level Symanzik-improved gauge action and 2+1 flavor tree-level improved Wilson Clover fermions coupling via 2-level HEX-smearing. Leveraging a wide set of operators, two extraction methods for the matrix elements, and the automatic inclusion of model uncertainties via bootstrapped model averages, we extract values of the third Mellin moments. Furthermore, this is the first direct calculation of these observables performed at the physical pion mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Coupling between collective modes in the deformed 98 Zr nucleus: Insights from consistent HFB + QRPA calculations with the Gogny interaction

The zirconium isotopes exhibit structural properties that present multiple challenges to nuclear theory. Investigations of the coupling present within isoscalar modes and within isovector modes are scarce but important for advancing our understanding of the microscopic picture of nuclei. To explore some of these underlying coupling features, and to test the predictive power of a state-of-the-art nuclear structure approach, we provide a detailed analysis of the properties of 90,96,98 Zr . This region includes a benchmarking case and offers insights into nuclear deformation phenomena. Here, to investigate the coupling between collective modes in deformed nuclei, we focused our analysis on the ground and excited-state properties of these isotopes, employing a consistent approach with the axially symmetric deformed Hartree-Fock-Bogoliubov (HFB) and the quasiparticle random phase approximation (QRPA) framework, both using the Gogny D1M force. This approach effectively describes both low-lying and giant-resonance states. We devoted special attention to the deformed 98 Zr nucleus, where we confirm the existence of coupling between monopole and quadrupole excitations through the 𝐾 𝜋 = 0 + QRPA components and demonstrate an analogous dipole-octupole coupling through the 𝐾 𝜋 = 0 − and 𝐾 𝜋 = 1 − components. Intrinsic transition densities and associated radial projections illustrate the coupling. Our work complements and extends earlier studies carried out using density-functional-based methods and notably, we included the complete Coulomb interaction also in the pairing fields, i.e., we treat terms exactly that are approximated in typical calculations that use the Gogny D1 and D2 interaction families.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

An Efficient Three-Dimensional CFD-Based Numerical Wave Tank for a Wave Energy Converter in Extreme Irregular Waves

A numerical wave tank approach for computational fluid dynamics (CFD) modelling of an extreme irregular seastate is presented. The technique couples a potential flow solution with a CFD solver for more efficient numerical predictions. This method has recently become attractive both for the research community and the industry working with offshore structures. The model is used to determine the response of a submerged pressure differential wave energy converter (WEC) in a fully nonlinear irregular wave condition using the high-fidelity CFD code, STAR-CCM+. Potential flow based numerical models are commonly used to predict motions and performance of wave energy converters. Wave kinematics can deviate from potential flow predictions for extreme wave conditions; the excitation loads on an absorber can also be increasingly influenced by viscous effects, not predicted by potential flow engineering level models. In these extreme conditions, a Reynolds-averaged Navier-Stokes CFD model can better predict motions and loads for a WEC. Long time series with varying random seed numbers can be used to identify singular extreme wave events from a stochastic irregular sea state. This approach simulates a more realistic wave series for a given sea state than a regular wave or a focused wave. However, it is computationally infeasible to run these long time series for three-dimensional (3D) CFD simulations. In this work, two-dimensional (2D) CFD simulations with a long domain allow the full development of an extreme nonlinear wave condition. The results are used to identify extreme events from a 50-year storm condition for the PacWave site off the coast of Oregon. A relatively short time window including this extreme event is then mapped to a 3D simulation using a user defined wave methodology. Convergence studies for domain length, wave forcing lengths, and time before the extreme event were conducted.

CFD↗
DOE OSTI2026

Single-molecule infrared spectroscopy with scanning tunneling microscopy

Probing vibrations at the single-molecule level is essential for achieving bond-specific chemical control in realistic heterogeneous environments. Here, we introduce a new measurement scheme that integrates frequency-tunable infrared excitation with scanning tunneling microscopy to characterize vibration-mediated nuclear motions of single molecules. We first validated the technique by monitoring the infrared-induced rotation of the ethynyl radical and then applied it to mapping pyrrolidine’s conformational dynamics. The resulting broadband spectra captured fundamental vibrational modes together with rich overtone and combination bands inaccessible by conventional methods, which we confirmed with isotopic substitutions. Density functional theory calculations showed that delocalized modes coupled with pyrrolidine ring puckering drive the structural transition, revealing altered selection rules compared with traditional infrared spectroscopy. Here, this new experimental platform enables molecular vibrations and transformations to be probed with atomic precision.

Liang, Kangkai [University of California, San Dieg↗
DOE OSTI2021

A High-Throughput Method for Identifying Novel Genes That Influence Metabolic Pathways Reveals New Iron and Heme Regulation in Pseudomonas aeruginosa

The ability to simultaneously and more directly correlate genes with metabolite levels on a global level would provide novel information for many biological platforms yet has thus far been challenging. Here, we describe a method to help address this problem, which we dub “Met-Seq” ( met abolite-coupled Tn seq uencing).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

If We Build Them, They Will Run: Automated HPC Apps Deployment and Profiling with eBPF in Cloud

The high performance computing (HPC) community is in a period of transition. The rise of AI/ML coupled with a changing landscape of resources deems portability a new metric of performance, and methods to move between on-premises and cloud environments and assess compatibility are paramount. Here we design and test a strategy for bridging the gap between traditional HPC and Kubernetes environments – first containerizing applications, providing automated orchestration to run studies, and packaging the setup with automated means to assess performance using low overhead eXtended Berkeley Packet Filter (eBPF) programs. We first assess different designs for eBPF collection, demonstrating a tradeoff between number of programs deployed on a node and overhead added. We develop 5 low overhead eBPF programs that combine with streaming ML models to assess CPU, futex, TCP, shared memory, and file access across four different builds of an HPC application for CPU and GPU. We use eBPF data to generate insights into the possible underlying etiology of scaling issues. We then assess compatibility of a well-known benchmark, HPCG, across matrices of micro-architectures and optimization levels (217 containers across 24 instance types and over 7500 runs). We provide to the community 30 applications to deploy in our automated setup and perform a scaling study from 4 to a maximum of 256 nodes for both CPU and GPU applications. Finally, we use our gained knowledge about performance to generate compatibility artifacts that are used by a newly developed Kubernetes controller to intelligently select instance type based on optimizing a figure of merit. Along with insights to scaling in this environment with a collection of applications and templates to work from, we provide an overall strategy for approaching HPC application deployment and image selection based on compatibility in cloud.

Computer science↗
DOE OSTI2021

Deep learning classification of lipid droplets in quantitative phase images

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Coupling between collective modes in the deformed 98 Zr nucleus: Insights from consistent HFB+QRPA calculations with the Gogny interaction

The Zirconium isotopes exhibit structural properties that present multiple challenges to nuclear theory. Investigations of the coupling present within isoscalar modes and within isovector modes are scarce but important for advancing our understanding of the microscopic picture of nuclei. To explore some of these underlying coupling features, and to test the predictive power of a state-of the-art nuclear structure approach, we provide a detailed analysis of the properties of 90,96,98Zr. This region includes a benchmarking case and offers insights into nuclear deformation phenomena. To investigate the coupling between collective modes in deformed nuclei, we focused our analysis on the ground and excited-state properties of these isotopes, employing a consistent approach with the axially-symmetric deformed Hartree-Fock-Bogoliubov (HFB) and the Quasiparticle Random Phase Approximation (QRPA) framework, both using the Gogny D1M force. This approach effectively describes both low-lying and giant-resonance states. We devoted special attention to the deformed 98Zr nucleus, where we confirm the existence of coupling between monopole and quadrupole excitations through the K π = 0 + QRPA components and demonstrate an analogous dipole-octupole coupling through the K π = 0 − and K π = 1 − components. Intrinsic transition densities and associ ated radial projections illustrate the coupling. Our work complements and extends earlier studies carried out using density-functional-based methods and notably, we included the complete Coulomb interaction also in the pairing fields, i.e. we treat terms exactly that are approximated in typical calculations that use the Gogny D1 and D2 interaction families.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Measurement of Local Impedance Characteristics of In-Plane PEM Electrolyzer Component Features via Segmented Cell

Segmented cells are a class of advanced diagnostic devices that enable the measurement of current distribution within the active area of an electrochemical cell, allowing for the evaluation of localized impacts from operating conditions, flow fields and component inhomogeneities. Segmented cell devices have been applied to support R&D efforts for the advancement of polymer electrolyte membrane fuel cell technologies and more recently proton exchange membrane water electrolysis (PEMWE). Beyond current density distributions, segmented cells have been successfully deployed to collect the distribution of other relevant parameters such as high frequency resistance and electrode potentials. Very recently, a promising impedance method has been reported for water electrolysis where a one-dimensional segmented cell is coupled to a multichannel potentiostat, to enable the measurement of local cell impedances, further expanding the diagnostic capabilities of the segmented cell. In this study, we will present recent efforts to accurately measure local impedance characteristics for a PEMWE cell using a two-dimensional segmented cell device coupled with a multichannel potentiostat. The distribution of local resistances, i.e. high frequency, charge transfer, mass transport and catalyst layer, and iR-free overpotentials were successfully measured after eliminating sources of random and systematic error. We will discuss the application of this diagnostic on a cell containing a 1 cm feature simulating an ionomer skin. The results from these tests give insights if such an irregularity needs to be classified as a defect, and highlight the usefulness of coupling impedance spectroscopy with segmented cells for holistic spatial diagnostics of electrochemical devices.

08 HYDROGEN↗
DOE OSTI2021

Analysis of Organophosphorus-Based Nerve Agent Degradation Products by Gas Chromatography-Mass Spectrometry (GC-MS): Current Derivatization Reactions in the Analytical Chemist’s Toolbox

The field of gas chromatography-mass spectrometry (GC-MS) in the analysis of chemical warfare agents (CWAs), specifically those involving the organophosphorus-based nerve agents (OPNAs), is a continually evolving and dynamic area of research. The ever-present interest in this field within analytical chemistry is driven by the constant threat posed by these lethal CWAs, highlighted by their use during the Tokyo subway attack in 1995, their deliberate use on civilians in Syria in 2013, and their use in the poisoning of Sergei and Yulia Skripal in Great Britain in 2018 and Alexei Navalny in 2020. These events coupled with their potential for mass destruction only serve to stress the importance of developing methods for their rapid and unambiguous detection. Although the direct detection of OPNAs is possible by GC-MS, in most instances, the analytical chemist must rely on the detection of the products arising from their degradation. To this end, derivatization reactions mainly in the form of silylations and alkylations employing a vast array of reagents have played a pivotal role in the efficient detection of these products that can be used retrospectively to identify the original OPNA.

sarin↗
DOE OSTI2025

Acoustic Sensing Fiber Coupled with Highly Magnetostrictive Ribbon for Small-Scale Magnetic-Field Detection

Fiber-optic sensing has shown promising development for use in detecting magnetic fields for downhole and biomedical applications. Coupling existing fiber-based strain sensors with highly magnetostrictive materials allows for a new method of magnetic characterization capable of distributed and high-sensitivity field measurements. This study investigates the strain response of the highly magnetostrictive alloys Metglas® 2605SC and Vitrovac® 7600 T70 using Fiber Bragg Grating (FBG) acoustic sensors and an applied AC magnetic field. Sentek Instrument’s picoDAS interrogated the distributed FBG sensors set atop a ribbon of magnetostrictive material, and the corresponding strain response transferred to the fiber was analyzed. Using the Vitrovac® ribbon, a minimal detectable field amplitude of 60 nT was achieved. Using Metglas®, an even better sensitivity was demonstrated, where detected field amplitudes as low as 3 nT were measured via the strain response imparted to the FBG sensor. Distributed FBG sensors are readily available commercially, easily integrated into existing interrogation systems, and require no bonding to the magnetostrictive material for field detection. The simple sensor configuration with nanotesla-level sensitivity lends itself as a promising means of magnetic characterization and demonstrates the potential of fiber-optic acoustic sensors for distributed measurements.

Dejneka, Zach (ORCID:0000000179415708)↗
DOE OSTI2025

Systematic improvement of trial states in phaseless auxiliary-field quantum Monte Carlo

We extend the use of coupled cluster (CC) trial states in the phaseless auxiliary-field quantum Monte Carlo (AFQMC) method beyond single and double excitations to include both triple and quadruple excitations. With this AFQMC/CC hierarchy, we are able to systematically benchmark the method's performance on molecular systems as the quality of the trial is improved. Our results show that the phaseless AFQMC energy improves systematically and is typically significantly more accurate than the energy of the underlying trial state. However, the relative improvement compared to the trial CC energy decreases as we ascend the CC hierarchy. As the CC wavefunction is usually further approximated when used as an AFQMC trial, we also explore the relationship between the components of the CC wavefunction and the resulting AFQMC/CC error. Our results suggest that improving the representation of the CC wave function in the AFQMC trial does not always lower the bias even when it increases the fidelity of the trial with the exact ground state.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2020

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗