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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Unveiling the spatial distribution of molecular coherences at conical intersections by covariance X-ray diffraction signals

Significance Monitoring the real-space motion of the electrons directly involved in ultrafast molecular dynamics is a challenging goal, hindered by the strong contributions of the remaining inactive electrons. Molecular quantum coherences can provide a direct window into elementary electronic dynamics, but they could not be separately imaged so far. Here, we demonstrate a time- and frequency-resolved X-ray diffraction technique, which can employ existing stochastic X-ray pulses to separately image the coherence contributions. The technique can selectively follow the relevant electrons involved in the ultrafast dynamics and identify the confined molecular regions covered by their motion. It enables readily feasible measurements and can be straightforwardly extended to full three-dimensional imaging via X-ray and electron diffraction.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Temporal X-ray Reconstruction using Temporal and Spectral Measurements at LCLS

Transverse deflecting structures (TDSs) are widely used in accelerator physics to measure the longitudinal density of particle bunches. When used in combination with a dispersive section, the whole longitudinal phase space density can be imaged. At the Linac Coherent Light Source (LCLS), the installation of such a device downstream of the undulators enables the reconstruction of the X-ray temporal intensity profile by comparing longitudinal phase space distributions with lasing on and lasing off. However, the resolution of this TDS is limited to around 1 fs rms (root mean square), and therefore, it is not possible to resolve single self-amplified spontaneous emission (SASE) spikes within an X-ray photon pulse. By combining the power spectrum from a high resolution photon spectrometer and the temporal structure from the TDS, the overall resolution is enhanced, thus allowing the observation of temporal, single SASE spikes. The combined data from the spectrometer and the TDS is analysed using an iterative algorithm to obtain the actual intensity profile. In this paper, we present some improvements to the reconstruction algorithm as well as real data taken at LCLS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Mid-day photomixotrophy by Roseiflexus spp. and implications for the 13 C content of hot spring cyanobacterial mats

Microbial mats inhabiting extreme environments have been studied as modern analogs of stromatolites. Mats in Octopus Spring and Mushroom Spring, Yellowstone National Park, are predominated by unicellular photoautotrophic cyanobacteria (Synechococcus spp.), which are thought to cross-feed filamentous photoheterotrophic bacteria (mainly Roseiflexus spp.), except under early morning anoxic conditions when Roseiflexus spp. have been shown to fix dissolved inorganic carbon (DIC). Transcription patterns, however, suggest that Roseiflexus spp. may perform photomixotrophy, in which DIC is incorporated together with organic compounds during the daytime. We investigated the roles played by Synechococcus spp. and Roseiflexus spp. in DIC and organic matter uptake in mid-day light and oxic mats. Mass spectrometry was used to show that 13 C-bicarbonate uptake under infrared (IR) light (utilized by anoxygenic phototrophs) or visible-minus-blue light (V-B) (used by cyanobacteria) was about two-thirds and one-third, respectively, of that incorporated in full light. Laser-ablation mass spectrometry analysis demonstrated that 13 C incorporation under V-B light was restricted to the uppermost portion of the mat, whereas 13 C incorporation under IR light was maximal in deeper mat layers. 13 C-acetate, -propionate, -lactate, and -glycolate were incorporated to an equal or greater extent under IR and full light. Incorporation of 13 C into peptides showed that both Synechococcus spp. and Roseiflexus spp. were active in DIC uptake, whereas Roseiflexus spp. exhibited greater uptake of 13 C-organic acids, especially glycolate and lactate, into peptides. Peptides of proteins of the 3-hydroxypropionate pathway were labeled. Thus, Roseiflexus spp. appears to exhibit photomixotrophy throughout the day.

Roseiflexus↗
DOE OSTI2021

Free space Thomson scattering to study high energy density shocks

A free space collective Thomson scattering system has been developed to study pulsed power produced plasmas. While most Thomson scattering diagnostics on pulsed power machines use a bundle of fibers to couple scattered light from the plasma to the spectrometer, this system used free space coupling of the light, which enabled a spatially continuous image of the plasma. Initial experiments with this diagnostic were performed on an inverse wire array generated by a 200 kA, 1100 ns rise time pulse power generator. The capabilities of this diagnostic were demonstrated by using the low frequency ion acoustic wave feature of the Thomson scattering spectra to measure the plasma flow velocity. The diagnostic was demonstrated to measure velocities between 20 and 40 km/s with an error of 4.7 km/s when fitting with a 600 μm spatial resolution or 8.9 km/s when fitting with a 150 μm spatial resolution. In some experiments, the diagnostic observed a bow shock in the plasma flow as the scattering intensity increased and flow velocity decreased.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction data

Crystallographic structure identification is crucial for understanding material properties; however, current methodologies often depend on labor-intensive and time-consuming analyses of 2D X-ray diffraction (XRD) patterns. To address these limitations, this study employs synthetic 2D XRD patterns combined with deep learning (DL) techniques to enable automated and high-throughput classification of the seven crystal systems and 230 space groups. We introduce the novel Auto Diffraction Pipeline, designed to generate synthetic 2D XRD spot patterns from crystallographic information files under diverse conditions, including varying zone axes, atomic substitution, atomic depletion and mechanical loading. These conditions enhance the realism of synthetic data, mitigating the scarcity of experimental datasets and enabling the creation of large representative training sets. Convolutional neural networks were trained and validated on these synthetic datasets to classify crystallographic structures across multiple scenarios. Our results demonstrate that integrating synthetic 2D XRD patterns with DL facilitates rapid, accurate and automated crystallographic classification, promoting the wider adoption of data-driven approaches in materials science.

Shahnazari, Ayoub [Univ. of Rochester, NY (United ↗
DOE OSTI2023

Strong-field nonsequential double photoionization using virtual-detector theory with path summation

We present an ab initio study of the nonsequential strong-field ionization dynamics of a model two-electron atom with helium character. Single- and double-ionization events are characterized and displayed using detector signals extracted at different points in the two-electron two-dimensional space. The double photoelectron momentum distribution is calculated via coherent path-summation over virtual-particle trajectories. A comparison is made between the momentum distributions obtained with the virtual-detector method, the Schrödinger wave function, and the time-dependent surface flux method developed by Tao and Scrinzi [New J. Phys. 14, 013021 (2012)]. Insights into different ionization and electron recollision pathways are gained from detailed virtual-particle tracking and energy-time readouts. Furthermore, this study demonstrates the extension of virtual-detector theory to strong-field multielectron quantum dynamics and highlights the importance of the evolving quantum phase in quasiclassical electron propagation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets

Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications ranging from solar photovoltaics to infrared lasers. While these transition levels can be measured and calculated accurately, such efforts are time-consuming and more rapid prediction methods would be beneficial. Here, we significantly reduce the time typically required to predict impurity transition levels using multi-fidelity datasets and a machine learning approach employing features based on elemental properties and impurity positions. We use transition levels obtained from low-fidelity (i.e., local-density approximation or generalized gradient approximation) density functional theory (DFT) calculations, corrected using a recently proposed modified band alignment scheme, which well-approximates transition levels from high-fidelity DFT (i.e., hybrid HSE06). Further, the model fit to the large multi-fidelity database shows improved accuracy compared to the models trained on the more limited high-fidelity values. Crucially, in our approach, when using the multi-fidelity data, high-fidelity values are not required for model training, significantly reducing the computational cost required for training the model. Our machine learning model of transition levels has a root mean squared (mean absolute) error of 0.36 (0.27) eV vs high-fidelity hybrid functional values when averaged over 14 semiconductor systems from the II–VI and III–V families. As a guide for use on other systems, we assessed the model on simulated data to show the expected accuracy level as a function of bandgap for new materials of interest. Finally, we use the model to predict a complete space of impurity charge-state transition levels in all zinc blende III–V and II–VI systems.

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

Anomalously slow hot carrier cooling and insulator-to-metal transition in a photo-doped Mott insulator

Photo-doped Mott insulators can exhibit novel photocarrier transport and relaxation dynamics and non-equilibrium phases. However, time-resolved real-space imaging of these processes are still lacking. Here, we use scanning ultrafast electron microscopy (SUEM) to directly visualize the spatial-temporal evolution of photoexcited species in a spin-orbit assisted Mott insulator α-RuCl 3 . At low optical fluences, we observe extremely long hot photocarrier transport time over one nanosecond, almost an order of magnitude longer than any known values in conventional semiconductors. At higher optical fluences, we observe nonlinear features suggesting a photo-induced insulator-to-metal transition, which is unusual in a large-gap Mott insulator. Our results demonstrate the rich physics in a photo-doped Mott insulator that can be extracted from spatial-temporal imaging and showcase the capability of SUEM to sensitively probe photoexcitations in strongly correlated electron systems.

42 ENGINEERING↗
DOE OSTI2023

Tomographic optical emission spectroscopy of atmospheric pressure plasma interacting with complex surfaces

Plasma distribution in 3D space is heavily influenced by complex surfaces and the coupling interactions between plasma properties and interfacing material properties. For example, guided streamers that transition to surface ionization waves (SIWs) and propagate over structured dielectrics experience field enhancements that can lead to localized increases in ionization rates and complex 3D configurations that are difficult to analyze. Investigating these configurations requires techniques than can provide a more complete 3D picture. To help address this capability gap, a tomographic optical emission spectroscopy (tomo-OES) diagnostic system has been developed at Sandia National Laboratories that can resolve SIWs. The system includes four intensified cameras that measure the angular projections of the plasma light emission through bandpass filters. A dot calibration target co-registers each angular projection to the same voxel grid and an algebraic reconstruction technique (ART) recovers the light intensity at each voxel. An atmospheric pressure plasma jet (APPJ), provided by Peter Bruggeman, has been investigated and representative results are shown in Figure 1. Here, a bandpass filter was used to isolate emission from the N 2 second positive system (SPS) at 337.1 nm to capture the transition of the streamer to SIW on a planar dielectric surface (relative permittivity 3.3) located 3 mm below the APPJ [3]. The surface wave velocity was 3.5x10 4 (m/s), consistent with measurements made by Steven Shannon. Characterization of this APPJ will support the group effort of standing up a reproducible APPJ across institutions for applications such as liquid treatment, catalysis, and plasma aided combustion. Future work will investigate non-planar surfaces and eventually develop tomographic laser-induced fluorescence (tomo-LIF) approaches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A study of space charge induced non-linearity in the Single Line Of Sight camera

We report a new generation of gated x-ray detectors at the National Ignition Facility has brought faster, enhanced imaging capabilities. Their performance is currently limited by the amount of signal they can be operated with before space charge effects in their electron tube start to compromise their temporal and spatial response. We present a technique to characterize this phenomenon and apply it to a prototype of such systems, the Single Line Of Sight camera. Results of this characterization are used to benchmark Particle In Cell simulations of the electrons drifting inside the detector, which are found to well reproduce experimental data. These simulations are then employed to predict the optimum photon flux to the camera, with the goal to increase the quality of the images obtained on an experimental campaign while preventing the appearance of deleterious effects. They also offer some insight into some of the improvements that can be brought to the new pulse-dilation systems being built at Lawrence Livermore National Laboratory

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Benchmarking third-order cluster perturbation theory for electronically excited states

In this study, we investigate the reliability of cluster perturbation (CP) theory applied to the calculation of electronically excited states through a comprehensive benchmark. In CP theory, perturbative corrections are added to the properties of a parent excitation space, which converge toward the properties of a target excitation space. For the CPS(D-n) model, perturbative corrections through order n are added to the coupled cluster singles (CCS) excitation energies to target the coupled cluster singles and doubles (CCSD) excitation energies. Through a comparative analysis of excitation energy calculations across a diverse set of molecules and wavefunction methods, we present a comprehensive evaluation of the accuracy of the third-order CPS(D) model, CPS(D-3), in calculating excitation energies. Further, our findings demonstrate that CPS(D-3) is a reliable alternative to established methods, particularly CCSD, while systematically overestimating the excitation energies compared to high-level coupled cluster methods such as CC3. These results highlight the strengths and limitations of CPS(D-3), as well as the promising directions for its future development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Aluminum-Based Superconducting Tunnel Junction Sensors for Nuclear Recoil Spectroscopy

The BeEST experiment is searching for sub-MeV sterile neutrinos by measuring nuclear recoil energies from the decay of 7 Be implanted into superconducting tunnel junction (STJ) sensors. The recoil spectra are affected by interactions between the radioactive implants and the sensor materials. We are therefore developing aluminum-based STJs (Al-STJs) as an alternative to existing tantalum devices (Ta-STJs) to investigate how to separate material effects in the recoil spectrum from potential signatures of physics beyond the Standard Model. Three iterations of Al-STJs were fabricated. The first had electrode thicknesses similar to existing Ta-STJs. They had low responsivity and reduced resolution, but were used successfully to measure 7 Be nuclear recoil spectra. The second iteration had STJs suspended on thin SiN membranes by backside etching. These devices had low leakage current, but also low yield. The final iteration was not backside etched, and the Al-STJs had thinner electrodes and thinner tunnel barriers to increase signal amplitudes. These devices achieved 2.96 eV FWHM energy resolution at 50 eV using a pulsed 355 nm (~3.5 eV) laser. These results establish Al-STJs as viable detectors for systematic material studies in the BeEST experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Frontier nonequilibrium materials science enabled by ultrafast electron methods

Most innovation in materials science and engineering resides in our ability to understand and control the intimate relationship between the structure of materials and their properties. Conventionally, the only route to discovering innovative new material properties has been to explore the structural and compositional phase space that is accessible at (or near) thermodynamic equilibrium. The characterization, manipulation and, ultimately, control of material properties far from equilibrium offers almost completely untapped possibilities for uncovering novel states and phases of materials. Investigations of materials far from equilibrium require the development of new techniques, which are capable of following dynamic processes in materials with extreme spatiotemporal resolution. Thus, ultrafast electron-based methods have become a major new frontier in materials science due to the capability of following dynamics on time scales as short as femtoseconds with the high spatial resolution and sensitivity afforded by electrons. The articles in this issue provide an exciting cross section of the novel research directions that have been enabled at this frontier. Imaging on ultrafast time scales carries critical information on phase transitions, fundamental processes involved in light-harvesting, magnetic, and plasmonic dynamics, the coupling of electronic and nuclear degrees of freedom in materials and has revealed previously hidden, nonequilibrium metastable states of matter that have no equilibrium analog.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomic Mixing of Initially Separated Mixtures

We consider the atomic mixing of two materials, initially separated in space, at fixed temperature– pressure conditions [T, p], and zero mass-mean velocity. Each material is composed of a specified set of atomic species whose density corresponds to the specieswise real Equation of State (EOS) $\tilde{&#961}$ i [T, p]. Because there are no spatial gradients in the mean [T, p] state, the only mechanism for mixing is a specieswise nonequilibrium thermal velocity distribution. The recipe for nonequilibrium species mass fluxes is taken directly from Hirschfelder, Curtiss, and Bird, who express the diffusion velocities in terms of gradients in the molar concentrations and pairwise coefficients of diffusion. EOS data from the SESAME library is used for all species. Data for the specieswise self diffusion coefficients is adopted from the Orbital Free Molecular Dynamics (OFMD) simulations of Ticknor et al.; the so-called Darken approximation is used to express the mutual diffusion coefficients of a mixture in the manner used by White et al. A one-dimensional spatial domain is used; with the left half occupied by one multispecies material and the right half occupied by the other, and with zero–gradient boundary conditions at the ends of the domain. Hence the total mass in the domain is a constant. At time t = 0 the materials are separated. Accordingly, spatial gradients at the separation point are infinite and the species fluxes are also infinite. As t → $\textbf{∞}$ the spatial gradients approach zero and a uniform set of species concentrations is obtained; at this point the system is said to be at “thermodynamic equilibrium.” Analytic solution of the problem is not possible in general due to the nonlinear concentration dependence of the species fluxes. Hence we utilize the numerical solution apparatus in Mathematica for obtaining accurate time-dependent solutions for the mixing of various initial species masses for conditions of interest in laser-driven Inertial Confinement Fusion. Concentration profiles and the speed of propagation of the mixing fronts are discussed in light of the nonlinearity of the problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Gate-Tunable Short-Wave Infrared Polycrystalline GeSn Phototransistors on Noncrystalline Substrates

GeSn is a group-IV alloy with immense potential to advance microelectronics technology due to its intrinsic compatibility with existing Si CMOS processes. With a sufficiently high Sn composition, GeSn is classified as a direct bandgap semiconductor. Polycrystalline GeSn holds several additional advantages, including its significantly lower synthesis cost compared to its epitaxial counterpart, as well as the versatility to grow these films on a variety of substrates. Here, in this work, we present a polycrystalline thin-film GeSn phototransistor on a fused silica substrate with a Sn composition of ~10%, showing a photoresponse in the short-wave infrared wavelength range, critical for emerging sensing applications. This device shows a gate-tunable response, with responsivities approaching up to 1.7 mA/W with only a 30 nm-thick GeSn layer. Furthermore, phototransistors offer additional adaptability through gating, which allows for the reduction of dark current. This not only enhances the signal-to-noise ratio but also offers more flexible integration with various image sensor readout implementations using different substrates. The specific detectivity of this phototransistor is within an order of magnitude of those of previously reported GeSn photodetectors grown by molecular beam epitaxy and chemical vapor deposition, even though the absorber is 3 to 20× thinner while the electrode spacing for photocarrier transport is approximately 15× longer than the carrier diffusion length in this work, showing great potential benefits of extending similar device structures to epitaxial GeSn layers. As these GeSn phototransistors utilize a noncrystalline substrate, our work establishes a fundamentally more versatile path toward monolithically integrated GeSn-based photodetectors for next-generation multimodal sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Orbital-Selective Instabilities and Spin Fluctuations at the Verge of Superconductivity in Interlayer-Expanded Iron Selenide

Understanding electron correlation-driven instabilities and their coupling to structural phases is essential for deciphering multiorbital pairing in unconventional superconductors. We investigate Li x (C 5 H 5 N) y Fe 2 Se 2 (x ∼ 0.6; y ∼ 0.7−0.9), a tetragonal β-FeSe intercalate with a superconducting transition temperature (T c = 39 K) closely tied to an expanded Fe-layer spacing (∼11.4 Å). High-resolution synchrotron Xray diffraction and core-level absorption spectroscopy reveal subtle lattice distortions on cooling without a symmetry-breaking transition. Instead, the material exhibits negative thermal expansion (NTE) in the two-dimensional Fe network below T S ∼ 70 K, and stiffening of local Se−Fe−Se bond dynamics near T c . The spatially incoherent rearrangement of FeSe 4 tetrahedra and the site-local fluctuations, signal reduced electron correlations compared to those of parent β-FeSe (T c = 8 K). Complementary X-ray emission spectroscopy, a fast local probe of Fe 3d valence states, detects persistent local Fe spin moments below T S , unlike quenching in related systems. These findings indicate that decoupling of Fe planes leads to an electronically driven lattice instability. The latter emerges as NTE induced from weak, orbital-selective localization of in-plane Fe 3d states rather than conventional transverse vibrations. Governed by Hund’s coupling, this selectivity permits coexistence of local spin fluctuations with itinerant d-electrons critical for enhancing T c . These results suggest that intercalation-driven d-orbital differentiation moderates electron correlations, providing a pathway to optimize the superconductivity in low-dimensional quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-Beam-Energy Control Unit Based on Triple-Bend Achromats

X-ray free electron lasers (XFELs) are the new generation of particle accelerator-based light sources, capable of producing tunable, high-power X-ray pulses that are increasingly vital across various scientific disciplines. Recently, continuous-wave (CW) XFELs driven by superconducting linear accelerators have garnered significant attention due to their ability to enhance availability by supporting multiple undulator lines simultaneously. In this paper, we introduce a novel delay system comprising four triple-bend achromats (TBAs). This delay system was combined with fast kickers and can be employed to generate electron beams on a bunch-to-bunch basis in a CW-XFEL facility. Based on the parameters of the Shanghai High-Repetition-Rate XFEL and Extreme Light Facility, start-to-end simulations demonstrate that the TBA-based delay system achieves excellent electron beam qualities while providing a wide beam-energy-tuning range from 1.39 to 8 GeV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Leveraging prior mean models for faster Bayesian optimization of particle accelerators

Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. One of the major advantages of Bayesian algorithms is the ability to incorporate prior information about beam physics and historical behavior into the model used to make control decisions. In this work, we examine incorporating prior accelerator physics information into Bayesian optimization algorithms by utilizing fast executing, neural network models trained on simulated or historical datasets as prior mean functions in Gaussian process models. We show that in ideal cases, this technique substantially increases convergence speed to optimal solutions in high-dimensional tuning parameter spaces. Additionally, we demonstrate that even in non-ideal cases, where prior models of beam dynamics do not exactly match experimental conditions, the use of this technique can still enhance convergence speed. Finally, we demonstrate how these methods can be used to improve optimization in practical applications, such as transferring information gained from beam dynamics simulations to online control of the LCLS injector, and transferring knowledge gained from experimental measurements across different operating modes, such as accelerating different ion species at the ATLAS heavy ion accelerator.

43 PARTICLE ACCELERATORS↗