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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Microscopic Mechanism of Lithiation and Delithiation in the Ag/C Buffer Layer for Anode‐Free Solid‐State Batteries

Abstract Lithium metal solid‐state batteries (LMSSBs) have demonstrated their high energy density and cycling performance at high current densities in an anode‐free architecture, featuring a thin Ag/C composite buffer layer (BL) between the current collector (CC) and the solid electrolyte (SE). This study explains the microscopic mechanism of the Ag/C BL by using first‐principles atomistic and continuum modeling. It is shown that Ag effectively acts as a homogeneous solid‐solution beyond AgLi 2.32 and maintains a positive potential even at AgLi 25 during lithiation. Key factors underlying the working of the Ag/C BL include lower interfacial resistance at the BL/CC interface than at the BL/SE interface, leading to predominant Li deposition on BL/CC, and substantial Ag–Li volume expansion during lithiation. This, combined with stronger BL/SE adhesion, causes BL/SE separation and Ag–Li extrusion toward the CC side. During delithiation, Ag re‐precipitates as nanoparticles uniformly on the CC, with its positive lithiation potential homogenizing Li currents in subsequent cycles. Other metals are less effective due to their relatively large overpotential, premature lithiation termination, and limited volume expansions hindering movement toward the CC. The study aids the BL design, focusing on metal choice and optimization material and microstructural properties, such as the Li‐ion conductivity and interfacial resistance.

25 ENERGY STORAGE↗
DOE OSTI2021

Laser-Induced Recoverable Fluorescence Quenching of Perovskite Films at a Microscopic Grain Scale

Understanding the fundamental properties of metal-halide perovskite materials is driving the development of novel optoelectronic applications. Here, in this paper, we report the observation of a recoverable laser-induced fluorescence quenching phenomenon in perovskite films with a microscopic grain-scale restriction, accompanied by spectral variations. This fluorescence quenching depends on the laser intensity and the dwell time under Auger recombination dominated conditions. These features indicate that the perovskite lattice deformation may take the main responsibility for the transient and show a new aspect to understand halide perovskite photo-stability. We further modulate this phenomenon by adjusting the charge carrier recombination and extraction, revealing that efficient carrier transfer can improve the bleaching resistance of perovskite grains. Our results provide future opportunities to attain high-performance devices by tuning the perovskite lattice disorder and harvesting the energetic carriers.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Hybrid Deep Learning Architecture for Classification of Microscopic Damage on NIF Laser Optics

Accurately classifying microscopic damage helps automate the repair and recycling of National Ignition Facility optics and informs the study of damage initiation and growth. This complex 12-class problem previously required human experts to distinguish and label the various damage morphologies. Finding image analysis methods to extract and calculate distinguishing features would be time consuming and challenging, so we sought to automate this task by using convolutional neural networks (CNNs) pretrained on the ImageNet database to take advantage of its automated feature discovery and extraction. We compared three model architectures on this dataset and found the one with highest overall accuracy, 99.17%, was a novel hybrid architecture, one in which we removed the final decision-making layer of the deep learner and replaced it with an ensemble of decision trees (EDT). This combines the power of feature extraction by CNNs with the decision-making strength of EDT. The accuracy of the hybrid architecture over the deep learning alone is shown to be significantly improved. Furthermore, we applied this novel hybrid architecture to an entirely different dataset, one containing images of repaired damage sites, and improved on the previously published findings, also with a demonstrably significant increase in accuracy over using the deep learner alone.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Identification of Recombination Losses in CdSe/CdTe Solar Cells from Spectroscopic and Microscopic Time-Resolved Photoluminescence

Due to the lowest-cost and best reliability, CdTe solar cells are the leading thin-film photovoltaic technology. Increasing open-circuit voltage by reducing recombination represents the most promising path toward further improvements. Analysis is needed to identify limitations that cause efficiency losses. To achieve this goal for Cu-doped CdSe/CdTe solar cells, time-resolved spectroscopy and microscopy are developed and applied. Recombination lifetimes and radiative efficiency identify that defect-mediated recombination is the dominant voltage loss mechanism. When carrier lifetimes are averaged over many crystalline grains, they increase from 180 to 430 ns when Al2O3 is applied to the back contact. The quasi-Fermi-level splitting correspondingly increases from 880–905 to 906–931 mV, indicating a pathway to overcome the long-standing 900 mV voltage limitation. However, the dominant recombination losses are attributed to the absorber bulk. From microscopic carrier lifetime measurements, it is identified that space charge fields due to charged grain boundaries (GBs) lead to recombination in the CdTe absorber bulk. At high injection, GB space charge fields are screened, but that occurs above 1 Sun excitation conditions. Alloying with selenium in the near-interface CdSeTe absorber region reduces GB losses and is identified as one of the factors leading to high radiative and power conversion efficiency.

14 SOLAR ENERGY↗
DOE OSTI2021

A cosmic microscope for the preheating era

Light fields with spatially varying backgrounds can modulate cosmic preheating, and imprint the nonlinear effects of preheating dynamics at tiny scales on large scale fluctuations. This provides us a unique probe into the preheating era which we dub the “cosmic microscope”. We identify a distinctive effect of preheating on scalar perturbations that turns the Gaussian primordial fluctuations of a light scalar field into square waves, like a diode. The effect manifests itself as local non-Gaussianity. We present a model, “modulated partial preheating”, where this nonlinear effect is consistent with current observations and can be reached by near future cosmic probes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Microscopic entropy of rotating electrically charged AdS 4 black holes from field theory localization

We employ supersymmetric localization to determine the exact partition function of 3d N = 2 gauge theories on a background given by a round S 2 fibered over a circle and certain complexified background fields. The Coulomb branch localization locus includes monopole configurations, and the partition function reduces to a matrix model. We consider the partition function of the ABJM theory on this background as an explicit case. We verify that the large-N limit of the ABJM theory partition function produces, in the Cardy limit, the entropy function of the dual rotating, electrically charged asymptotically AdS 4 supersymmetric black holes and thus provides a microscopic explanation for the Bekenstein-Hawking entropy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Search for microscopic black holes in pp collisions at $ \sqrt{s}=8 $ TeV

A search for microscopic black holes and string balls is presented, based on a data sample of pp collisions at sqrt(s) = 8 TeV recorded by the CMS experiment at the Large Hadron Collider and corresponding to an integrated luminosity of 12 inverse femtobarns. No excess of events with energetic multiparticle final states, typical of black hole production or of similar new physics processes, is observed. Given the agreement of the observations with the expected standard model background, which is dominated by QCD multijet production, 95% confidence limits are set on the production of semiclassical or quantum black holes, or of string balls, corresponding to the exclusions of masses below 4.3 to 6.2 TeV, depending on model assumptions. In addition, model-independent limits are set on new physics processes resulting in energetic multiparticle final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

A search for microscopic black holes, string balls, and sphalerons in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for microscopic black holes, string balls, and electroweak sphalerons using proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the CMS detector at the CERN LHC during the 2016–2018 data taking, and corresponding to an integrated luminosity of 138 fb −1 , is presented. Two search strategies based on control samples in data are used. Model-independent limits on the cross section of physics phenomena with multiple energetic jets, leptons, and photons are set using a method that relies on the shape invariance of the scalar sum of the transverse momenta of all objects in the event. Model-dependent limits on black hole and sphaleron production are set using a newly introduced method that has been developed for the identification of collider events with distinct kinematic features by separating them into classes based on phase space proximity. In the context of models with large extra dimensions, semiclassical black holes and string balls with masses below 8.4–11.4 TeV and 9.0–10.7 TeV, respectively, are excluded at 95% confidence level, significantly extending the reach beyond previous searches. Results of a dedicated search for electroweak sphalerons are used to derive an upper limit of 0.0034 at 95% confidence level on the fraction of quark-quark interactions, with a center-of-mass energy above the nominal sphaleron transition energy threshold of 9 TeV, that result in a sphaleron transition.

Beyond Standard Model↗
DOE OSTI2021

Possibility of an integrated transmission electron microscope: enabling complex in-situ experiments

Abstract Multimodal in-situ experiments are the wave of the future, as this approach will permit multispectral data collection and analysis during real-time nanoscale observation. In contrast, the evolution of technique development in the electron microscopy field has generally trended toward specialization and subsequent bifurcation into more and more niche instruments, creating a challenge for reintegration and backward compatibility for in-situ experiments on state-of-the-art microscopes. We do not believe this to be a requirement in the field; therefore, we propose an adaptive instrument that is designed to allow nearly simultaneous collection of data from aberration-corrected transmission electron microscopy (TEM), probe-corrected scanning transmission electron microscopy, ultrafast TEM, and dynamic TEM with a flexible in-situ testing chamber, where the entire instrument can be modified as future technologies are developed. The value would be to obtain a holistic understanding of the underlying physics and chemistry of the process-structure–property relationships in materials exposed to controlled extreme environments. Such a tool would permit the ability to explore, in-situ, the active reaction mechanisms in a controlled manner emulating those of real-world applications with nanometer and nanosecond resolution. If such a powerful tool is developed, it has the potential to revolutionize our materials understanding of nanoscale mechanisms and transients. Graphical Abstract

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Microscopic Study of Paper Decayed by Trichoderma harzianum and Paecilomyces variotii

The current study is interested in evaluating the decay of cotton, Whatman and chemical pulp caused by Trichoderma harzianum and Paecilomyces variotii. The structural changes of the paper were evaluated by Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM). The SEM results show differences in hyphae colonization and paper decay patterns between studied species under the current study; P. variotii caused an eroded structure in the cotton (cavity forming), whereas the initial T. harzianum colonization produced rupture and erosion (soft-rot decay type II) for the three types of paper ,the gaps were elongated with sharp pointed ends, which consisted either of individual cavities or in chains. Moreover, FTIR results confirmed that there a relationship could be observed between fungal decay and crystalline cellulose content because the intensity of peaks at 1335 and 1111 cm{sup −1} significantly decreased due to the fungal decay. Furthermore, the intensity of O–H stretching absorption slightly decreased, and this may be attributed to hydrolysis of cellulose molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Transmission Electron Microscope In Situ Straining Technique to Directly Observe Defects and Interfaces During Deformation in Magnesium

In-situ straining was used to study deformation behavior of hexagonal close-packed (hcp) metals.Twinning and dislocation motion, both essential to plasticity in hcp materials, were observed.Typically, these processes are characterized post-mortem by examining remnant microstructural features after straining has occurred. By imposing deformation during imaging, direct observation of active deformation mechanisms is possible. This work focuses on straining of structural metals in a transmission electron microscope (TEM), and a recently developed technique that utilizes familiar procedures and equipment to increase ease of experiments. In-situ straining in a TEM presents several advantages over conventional post-mortem characterization, most notably time-resolution of deformation and streamlined identification of active deformation mechanisms. Drawbacks to the technique and applicability to other studies are also addressed. In-situ straining is used to study twin boundary motion in hcp magnesium. A {101¯2} twin was observed during tensile and compressive loading. Twin-dislocation interactions are directly observed. Notably, dislocations are observed to remain mobile, even after multiple interactions with twin boundaries, a result which suggests that Basinki’s dislocation transformation mechanism by twinning is not present in hcp metals. The coupling of in-situ straining with traditional post-mortem characterization yields more detailed information about material behavior during deformation than either technique alone.

magnesium↗
DOE OSTI2018

E-beam manipulation of Si atoms on graphene edges with an aberration-corrected scanning transmission electron microscope

The burgeoning field of atomic-level material control holds great promise for future breakthroughs in quantum and memristive device manufacture and fundamental studies of atomic-scale chemistry. Realization of atom-by-atom control of matter represents a complex and ongoing challenge. Here, we explore the feasibility of controllable motion of dopant Si atoms at the edges of graphene via the sub-atomically focused electron beam in a scanning transmission electron microscope. Furthermore, we demonstrate that the graphene edges can be cleaned of Si atoms and then subsequently replenished from nearby source material. It is also shown how Si edge atoms may be “pushed” from the edge of a small hole into the bulk of the graphene lattice and from the bulk of the lattice back to the edge. This is accomplished through sputtering of the edge of the graphene lattice to bury or uncover Si dopant atoms. Finally, we demonstrate e-beam mediated hole healing and incorporation of dopant atoms. These experiments form an initial step toward general atomic-scale material control.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events—Concept of event-based driving volatility

The sequence of instantaneous driving decisions and its variations, known as driving volatility, prior to involvement in safety critical events can be a leading indicator of safety. Here, this study focuses on the component of “driving volatility matrix” related to specific normal and safety-critical events, named “event-based volatility.” The research issue is characterizing volatility in instantaneous driving decisions in the longitudinal and lateral directions, and how it varies across drivers involved in normal driving, crash, and/or near-crash events. To explore the issue, a rigorous quasi-experimental study design is adopted to help compare driving behaviors in normal vs unsafe outcomes. Using a unique real-world naturalistic driving database from the 2nd Strategic Highway Research Program (SHRP), a test set of 9593 driving events featuring 2.2 million temporal samples of real-world driving are analyzed. This study features a plethora of kinematic sensors, video, and radar spatiotemporal data about vehicle movement and therefore offers the opportunity to initiate such exploration. By using information related to longitudinal and lateral accelerations and vehicular jerk, 24 different aggregate and segmented measures of driving volatility are proposed that captures variations in extreme instantaneous driving decisions. In doing so, careful attention is given to the issue of intentional vs. unintentional volatility. The volatility indices, as leading indicators of near-crash and crash events, are then linked with safety critical events, crash propensity, and other event specific explanatory variables. Owing to the presence of unobserved heterogeneity and omitted variable bias, fixed- and random-parameter discrete choice models are developed that relate crash propensity to unintentional driving volatility and other factors. Statistically significant evidence is found that driver volatilities in near-crash and crash events are significantly greater than volatility in normal driving events. After controlling for traffic, roadway, and unobserved factors, the results suggest that greater intentional volatility increases the likelihood of both crash and near-crash events. A one-unit increase in intentional volatility is associated with positive vehicular jerk in longitudinal direction increases the chance of crash and near-crash outcome by 15.79 and 12.52 percentage points, respectively. Importantly, intentional volatility in positive vehicular jerk in lateral direction has more negative consequences than intentional volatility in positive vehicular jerk in longitudinal direction. Compared to acceleration/deceleration, vehicular jerk can better characterize the volatility in microscopic instantaneous driving decisions prior to involvement in safety critical events. Finally, the magnitudes of correlations exhibit significant heterogeneity, and that accounting for the heterogeneous effects in the modeling framework can provide more reliable and accurate results. The study demonstrates the value of quasi-experimental study design and big data analytics for understanding extreme driving behaviors in safe vs. unsafe driving outcomes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Fundamental microscopic properties as predictors of large-scale quantities of interest: Validation through grain boundary energy trends

Correlations between fundamental microscopic properties computable from first principles, which we term canonical properties, and complex large-scale quantities of interest (QoIs) provide an avenue to predictive materials discovery. Here, we propose that such correlations can be efficiently discovered through simulations utilizing approximate interatomic potentials (IPs), which serve as an ensemble of “synthetic materials”. As a proof of principle we build a regression model relating canonical properties to the symmetric tilt grain boundary (GB) energy curves in face-centered cubic crystals, characterized by the scaling factor in the universal lattice matching model of Runnels et al. (2016), which we take to be our QoI. Our analysis recovers known correlations of GB energy to other properties and discovers new ones. We also demonstrate, using available density functional theory (DFT) GB energy data, that the regression model constructed from IP data is consistent with DFT results, confirming the assumption that the IPs and DFT belong to same statistical pool and thereby validating the approach. Regression models constructed in this fashion can be used to predict large-scale QoIs based on first-principles data and provide a general method for training IPs for QoIs beyond the scope of first-principles calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Microscopically derived potential energy surfaces from mostly structural considerations

A simple procedure to estimate the quadrupole Potential-Energy-Surface (PES) is presented, using mainly structural information, namely the content of the shell model space and the Pauli exclusion principle. Further microscopic properties are implicitly contained through the use of results from the Möller and Nix tables or experimental information. A mapping to the geometric potential is performed yielding the PES. The General Collective Model is used in order to obtain an estimate on the spectrum and quadrupole transitions, adjusting only the mass parameter. First, we test the conjecture on known nuclei, deriving the PES and compare them to known data. We will see that the PES approximates very well the structure expected. Having acquired a certain confidence, we predict the PES of several chain of isotopes of heavy and super-heavy nuclei and at the end we investigate the structure of nuclei in the supposed island of stability. One of the main points to show is that simple assumptions can provide already important information on the structure of nuclei outside known regions and that spectra and electromagnetic transitions can be estimated without using involved calculations and assumptions. The procedure does not allow to calculate binding energies. The method presented can be viewed as a starting point for further improvements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Ground-state and stability properties of 288-308 118 Og isotopes based on semi-microscopic calculations

In this study, we present theoretical predictions on the stability properties of the yet unknown {sup 276−293,295−308}{sub 118}Og isotopes using the Skyrme-SLy4 nucleon–nucleon interaction and the deformed Woods–Saxon single-particle potential in a semi-microscopic approach. The ground-state masses, binding energy, deformations and fission barriers are calculated from the total energy surfaces produced in a multidimensional deformation space using the dynamical differential evolution optimization method. Besides, the Q-values of the different decay modes and the nucleon separation energies for each isotope, and its α-decay (T{sub α}) and spontaneous fission half-lives are also calculated. Our study revealed the {sub 290−296}Og elements to be the most bound Oganesson isotopes, among which {sup 302,304,306}Og elements are predicted to be spherical nuclei, and {sup 299,300,301,303,305}Og elements are shown to be almost spherical. The predicted ground-state and decay properties successfully reproduced the available data of the solely known Oganesson isotope {sup 294}Og. In addition to the principle α-decay modes, we studied the rival decay modes that challenge the stability of nuclei in the superheavy regions, namely the electron capture β{sup +} decays and the spontaneous fission. An overall oscillating increasing behavior of T{sub α} with the mass number is obtained, which obviously reverses the hesitating decreasing behavior of Q{sub α} and follows increasing trend of the corresponding change in the neutron-skin thickness after α-decays. The {sub 291,294−296,299−302}Og isotopes are expected to have relatively long half-lives, T{sub α} ≈ 1–45 ms, while {sup 295}Og is found to have the longest half-life between the considered nuclei. The {sub 291−300}Og isotopes exhibited relatively high fission barriers and small branching ratios for their spontaneous fission modes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Scanning tunneling microscope tip-induced formation of Bi bilayers on Bi 2 Te 3

We report the formation of Bi(111) bilayer islands and crater structures on Bi 2 Te 3 (111) surfaces induced by voltage pulses from a scanning tunneling microscope tip. Pulses above a threshold voltage (+3 V) produce craters ∼0.5μm in diameter, similar to the size of the tip. Redeposited material self-assembles into a network of atomically ordered islands with a lattice constant identical to the underlying Bi2Te3 surface. The island size monotonically decreases over several micrometers from the pulse site, until the pristine Bi 2 Te 3 surface is recovered. We assign these islands to Bi bilayer based on atomic resolution images, analysis of step heights, and tunneling spectroscopy. Here, the dependence of bilayer formation on bias polarity and the evidence for defect diffusion together suggest a mechanism driven by the interplay of field evaporation and tunneling-current-induced Joule heating.

Bi bilayer↗
DOE OSTI2020

Multimodal imaging and machine learning to enhance microscope images of shale

A machine learning based image processing workflow is presented to enhance shale source rock microscopic images obtained using diverse imaging platforms. Images were acquired from a 30 μm diameter cylindrical Vaca Muerta shale sample using both nondestructive Transmission X-Ray Microscopy (TXM, alternately referred to as nano computed tomography) and destructive Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM). Output cross-sectional images from each modality were aligned using a combination of manual and automated registration techniques to create a registered image dataset. We then apply this dataset for two image processing tasks: prediction of image cross sections with SEM-like resolution from nondestructive TXM data and repair of charged region artifacts (localized accumulation of electrons) within SEM images. The image processing algorithms for both tasks use deep learning models, specifically image-to-image Convolutional Neural Networks (CNNs) and conditional Generative Adversarial Networks (cGANs). In the image enhancement tasks, we are able to achieve significant qualitative and quantitative improvement in TXM images. Here, the best model reaches an average Peak Signal to Noise Ratio (PSNR) of 15.8 dB. Conditioning on TXM data is also shown to reduce artifacts from SEM charging, achieving an average PSNR of 25.8 dB. Furthermore, our results suggest that properly trained and validated networks are capable of significant enhancement of images obtained using nondestructive techniques, thereby improving interpretation of two- and three-dimensional images while preserving samples for future use.

58 GEOSCIENCES↗