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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Atomically dispersed palladium catalyses Suzuki–Miyaura reactions under phosphine-free conditions

Single-atom catalysts have emerged as a new frontier in catalysis science. However, their applications are still limited to small molecule activations in the gas phase, the classic organic transformations catalyzed by single-atom catalysts are still rare. Here, we report the use of a single-atom Pd catalyst for the classic Suzuki–Miyaura carbon–carbon coupling reaction under phosphine-free and open-air conditions at room temperature. The single-atom Pd catalyst is prepared through anchoring Pd on bimetal oxides (Pd-ZnO-ZrO 2 ). The significant synergetic effect of ZnO and ZrO 2 is observed. The catalyst exhibits high activity and tolerance of a wide scope of substrates. Characterization demonstrates that Pd single atoms are coordinated with two oxygen atoms in Pd-ZnO-ZrO 2 catalyst. The catalyst can be fabricated on a multi-gram scale using a simple in situ co-precipitation method, which endows this catalytic system with great potential in practical applications.

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

Martensitic transformation in superlattices of two non-transforming metals

A number of studies have shown that the coherent integration of a second non-transforming phase in martensitic materials results in unprecedented thermo-mechanical properties. We demonstrate the possibility of martensitic transformation by epitaxially combining two non-transforming materials, Mg (hexagonal closed packed) and MgLi (body centered cubic). Density functional theory calculations predict that MgLi/Mg superlattices undergo a transformation crystallographically equivalent to MgSc alloys and can be expected to result in finite temperature shape memory behavior. We predict the zero-temperature energy of the martensite phase to be 9.3 meV/atom lower than austenite for a 50–50 at. % MgLi/Mg nanolaminate, which is expected to result in a martensitic transformation temperature of approximately 150 K. This energy difference can be tuned between 4.9 and 18.1 meV/atom by varying the fraction of the pure Mg phase in the superlattice, potentially enabling the transformation from cryogenic to room and higher temperatures. While Li diffusion might limit the applications of the systems proposed, this work opens the door to a new approach to create martensitic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

VWC-BERT: Scaling Vulnerability–Weakness–Exploit Mapping on Modern AI Accelerators

Defending cybersystems needs accurate mapping of software and hardware vulnerabilities to generalized descriptions of weaknesses, and weaknesses to exploits. These mappings enable cyber defenders to build plans for effective defense and assessment of potential risks to a cybersystem. With close to 170k vulnerabilities, manual mapping is not a feasible option. However, automated mapping is challenging due to limited training data, computational intractability, and limitations in computational natural language processing. Tools based on breakthroughs in Transformer-based language models have been demonstrated to classify vulnerabilities with high accuracy. We make three key contributions in this paper: (1) We present a new framework, \VWCBERT, that augments the Transformer-based hierarchical multi-class classification framework of Das et al. (\textsc{V2W-BERT}) with the ability to map weaknesses to exploits. (2) We implement \VWCBERT~ on modern AI accelerator platforms using two data parallel techniques for the pre-training phase and demonstrate nearly linear speedups across NVIDIA and Graphcore accelerator platforms. We observe nearly linear speedups for up to 16 V100 and 8 A100 GPUs, and about 3.4$\times$ speedup for A100 relative to V100 GPUs. We also observe excellent speedups on Graphcore, with $5.7\times$ speedup on 128 IPUs relative to 16 IPUs. Enabled by scaling, we also demonstrate higher accuracy using a larger language model, RoBERTa-Large. We show up to 87\% accuracy for strict and up to 98\% accuracy for relaxed classification. (3) We develop a novel parallel link manager for the link prediction phase and demonstrate up to 21$\times$ speedup with 16 V100 GPUs relative to one V100 GPU, and thus reducing the runtime from 2.5 hours to 10 minutes. We believe that generalizability and scalability of \VWCBERT~ will benefit both the theoretical development and practical deployment of novel cyberdefense solutions and vulnerability classification.

Das, Siddhartha Shankar↗
DOE OSTI2023

Surface Merging Technique to Design GA-Optimized Heat Sinks

High-power density inverters require efficient and small heat dissipation systems. For liquid cooling systems, an effective heat sink design is important to enable higher heat transfer and keep the pressure drop within reasonable limits. A heat sink geometry generated from an extruded, 1D fast Fourier transform can achieve more even temperature distribution and improved heat transfer than a conventional heat sink. Building on this concept, this paper proposes a new heat sink geometry creation algorithm. Instead of one plane profile being extruded, multiple plane profiles, each created from the fast Fourier transform method, are subsequently merged by smooth surfaces along the flow direction of the heat sink. Thus, a 3D heat sink geometry is created that enables 3D coolant flow and efficient heat transfer. The volume of this design was reduced by 50% compared with pin fin heat sinks. Compared with extruded 1D fast Fourier transform heat sinks, the proposed design showed an approximately 5% device temperature reduction and a 20% pressure drop reduction.

Barua, Himel↗
DOE OSTI2023

Warping Functions Design for Long Warped ZT-DFT-s-OFDM

Time-frequency warped waveform is a novel type of well-contained waveform composed of raised cosine (RC) pulses with roll-off factors profile customized for spectrally efficient signal containment. The waveform is suited for massive machine-type communication (mMTC), and Internet-of-Things (IoT) applications. The paper is a follow-up to the original work of time-frequency warped waveforms; here, we are proposing a warping function suited for length-independent symbols, which is missing from the previous work. The paper proposes the design steps starting from a piecewise warping function with parts of straight segments and other curved parts. A maximum Out-of-band leakage is used as a criterion to determine the warping function parameters. The roll-off factors profile determined in the previous study is used as a minimum bound for the leakage limits. Gains are presented over Windowed Zero-tail Discrete Fourier Transform-spread-Orthogonal Frequency Division Multiplexing (ZT-DFT-s-OFDM) in the simulations section.

Ibrahim, Mostafa↗
DOE OSTI2021

Integrated atomic force microscopy and x-ray irradiation for in situ characterization of radiation-induced processes

Understanding radiation-induced chemical and physical transformations at material interfaces is important across diverse fields, but experimental approaches are often limited to either ex situ observations or in situ electron microscopy or synchrotron-based methods in which cases the radiation type and dose are inextricably tied to the imaging basis itself. In this work we overcome this limitation by demonstrating integration of an X-ray source with an atomic force microscope to directly monitor radiolytically-driven interfacial chemistry at the nanoscale. We illustrate the value of in situ observations by examining effects of radiolysis on material adhesion forces in aqueous solution, as well as examining the production of alkali nitrates at the interface between an alkali halide crystal surface and air. For the examined salt-air interface, direct visualization under flexible experimental conditions greatly extends prior observations by enabling the transformation process to be followed comprehensively from source-to-sink with mass balance quantitation. Overall, our novel rad-AFM opens doors into understanding the dynamics of radiolytically-driven mass transfer and surface alteration at the nanoscale in real-time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Predictive Skill of Deep Learning Models Trained on Limited Sequence Data

In this report we investigate the utility of one-dimensional convolutional neural network (CNN) models in epidemiological forecasting. Deep learning models, especially variants of recurrent neural networks (RNNs) have been studied for influenza forecasting, and have achieved higher forecasting skill compared to conventional models such as ARIMA models. In this study, we adapt two neural networks that employ one-dimensional temporal convolutional layers as a primary building block temporal convolutional networks and simple neural attentive meta-learner for epidemiological forecasting and test them with influenza data from the US collected over 2010-2019. We find that epidemiological forecasting with CNNs is feasible, and their forecasting skill is comparable to, and at times, superior to, RNNs. Thus CNNs and RNNs bring the power of nonlinear transformations to purely data-driven epidemiological models, a capability that heretofore has been limited to more elaborate mechanistic/compartmental disease models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Mapping of Texture and Phase Fractions in Heterogeneous Stress States during Multiaxial Loading of Biomedical Superelastic NiTi

Thermoelastic deformation mechanisms in polycrystalline biomedical-grade superelastic NiTi are spatially mapped using in situ neutron diffraction during multiaxial loading and heating. The trigonal R-phase is formed from the cubic phase during cooling to room temperature and subsequently deforms in compression, tension, and torsion. The resulting R-phase variant microstructure from the variant reorientation and detwinning processes are equivalent for the corresponding strain in tension and compression, and the variant microstructure is reversible by isothermal loading. The R-phase variant microstructure is consistent between uniaxial and torsional loading when the principal stress directions of the stress state are considered (for the crystallographic directions observed here). The variant microstructure evolution is tracked and the similarity in general behavior between uniaxial and torsional loading, in spite of the implicit heterogeneous stress state associated with torsional loading, pointed to the ability of the reversible thermoelastic transformation in NiTi to accommodate stress and strain mismatch with deformation. This ability of the R-phase, despite its limited variants, to accommodate stress and strain and satisfy strain incompatibility in addition to the existing internal stresses has significance for reducing irrecoverable deformation mechanisms during loading and cycling through the phase transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design and Fabrication of Quantum Information Processing Devices (Final Report)

The goal of this work is to develop a wideband Josephson Parametric Amplifier (JPA) by the combination of a coplanar impedance transformer and a lumped Josephson Parametric Amplifier. Josephson Parametric Amplifiers take advantage of the nonlinear inductance of Josephson junctions and the nearly lossless superconductor circuits to achieve wave mixing and amplification with only quantum-limited added noise, which makes it a key component in quantum measurements, such as single-shot qubit measurement. However, the current JPAs generally have a relatively high quality factor and small bandwidth (around 50MHz to 100MHz), which limits their ability in measuring signals from a broad spectrum. Therefore, the work planned to use a coplanar impedance transformer to enhance the coupling between JPA and the signals, resulting in a small quality factor and large bandwidth. By decreasing the quality factor of JPA to around 3, one can achieve around 20dB gain within a bandwidth of several hundred MHz. Moreover, the wideband feature allows this device to explore the frequency dependence of the coupling between the JPA and the signals. Because the impedance transformer is based on a coplanar transmission line and requires no modifications of the lumped JPA, it is relatively straightforward to embed it in the current fabrication, package, and testing process for lumped JPA. The impedance transformer can be fabricated by liftoff or etching process with the lumped JPA together, which adds no fabrication complexity. The only difference is the size, which is around 3~5 times larger than lumped JPA. This may make the number of available chips on a single wafer lower. As for the public benefits, the development of this wideband JPA will make it possible to use just a single JPA device for multi-frequency signals, for example, the readout signals of a superconducting qubit chip with multiplexed readout bus. This would greatly decrease the demand for JPAs in quantum measurements.

42 ENGINEERING↗
DOE OSTI2024

Direct comparison of using a Z -transformation instead of the traditional $Q^2$ for extraction of the proton radius from $e-p$ scattering data

A discrepancy in the determination of the proton’s charge radius, r p , between muonic hydrogen spectroscopy versus classic atomic spectroscopy and electron scattering data has become known as the proton radius puzzle. Extractions of r p from electron scattering data require determination of the slope of the proton’s charge form factor, $G$$^{p}_{E}$, in the limit of Q 2 → 0 through fitting and extrapolation. Some works have presented the Z-transformation fitting technique as the best choice for this type of extraction due to the true functional form of $G$$^{p}_{E}$ being mathematically guaranteed to exist within the parameter-space of the fit function. In this work, we test this claim by examining the mathematical bias and variances introduced by this technique as compared to the more traditional Q 2 fits using statistically sampled $G$$^{p}_{E}$ parameterizations with known input radii. Furthermore, our tests conclude that the quality of the Z-transformation technique depends on the range of data used. In the case of new experiments, the fit function and technique should be selected in advance by generating realistic pseudodata and assessing the power of different techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Fast redox switches lead to rapid transformation of goethite in humid tropical soils: A Mössbauer spectroscopy study

Abstract Humid tropical forest soils experience frequent rainfall, which limits oxygen diffusion and creates redox heterogeneity in upland soils. In this study we gauged the effect of short‐term anoxic conditions on Fe mineralogy of relatively Fe‐ and C‐rich surface soils (C/Fe mole ratio ∼5) from a humid tropical forest in Puerto Rico. Soils subjected to 4‐d oxic/anoxic oscillation were characterized by selective chemical extractions, Mössbauer spectroscopy (MBS), and X‐ray diffraction. Chemical extraction data suggested that rapidly switching redox conditions had subtle effects on bulk Fe mineralogy. Mössbauer, on the other hand, indicated that (a) the soil Fe is a mixture of goethites of varying characteristics with minor contributions from ferrihydrite (<5%) and Fe(III)‐organic matter (OM) phases (∼10%), and (b) anoxic conditions rapidly transformed all forms of goethite to relatively stable Fe oxides. Such fast changes in goethite features could be due to rapid depletion and sorption of bio‐released structural Al or sorbed OM onto residual soil components. The rapid temporal changes in MBS parameters and corresponding pore water nominal oxidation state of C values suggest that Fe‐C transformations in these upland tropical soils are complex and intricately coupled. A comprehensive understanding of the fate of Fe, Al, and OM (Fe‐organic moieties) during redox switches and concurrent changes in pore water chemistry is critical for development of robust transport models in humid tropical soils, which are subject to episodic low‐redox events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Molten salt electrochemical upcycling of CO 2 to graphite for high performance battery anodes

The efficient transformation of CO 2 into a value-added material is a potential strategy to help mitigate climate effects caused by CO 2 emissions. One potential CO 2 conversion product is graphite which is an important and versatile material extensively used in many applications including as an anode for lithium-ion batteries (LIBs). Commercial graphite, however, is traditionally synthesized via the energy intensive Acheson process (>3000 °C) and the performance of such graphite can be limited under fast charging conditions which is important for vehicle electrification. We report the electrochemical transformation of CO 2 to highly crystalline nano-graphite with a controlled microstructure in a carbonate molten salt at 780 °C. The use of a nickel foam electrode and controlled electrochemical parameters during the molten salt conversion process yielded pure graphite at a lower temperature compared to the Acheson process. Moreover, when investigated as an anode material for LIBs, the CO 2 -converted graphite exhibited high reversible capacity, long cycle life, and excellent rate capability even under fast charging conditions. This process provides a way to potentially reduce carbon emissions through the utilization of waste CO 2 by converting it into value-added graphite suitable for fast charging, high-energy-density batteries for vehicle electrification.

25 ENERGY STORAGE↗
DOE OSTI2022

Partially polaron-transformed quantum master equation for exciton and charge transport dynamics

Polaron-transformed quantum master equation (PQME) offers a unified framework to describe the dynamics of quantum systems in both limits of weak and strong couplings to environmental degrees of freedom. Thus, the PQME serves as an efficient method to describe charge and exciton transfer/transport dynamics for a broad range of parameters in condensed or complex environments. However, in some cases, the polaron transformation (PT) being employed in the formulation invokes an over-relaxation of slow modes and results in premature suppression of important coherence terms. A formal framework to address this issue is developed in the present work by employing a partial PT that has smaller weights for low frequency bath modes. In this work, it is shown that a closed form expression of a second order time-local PQME including all the inhomogeneous terms can be derived for a general form of partial PT, although more complicated than that for the full PT. All the expressions needed for numerical calculation are derived in detail. Applications to a model of a two-level system coupled to a bath of harmonic oscillators, with test calculations focused on those due to homogeneous relaxation terms, demonstrate the feasibility and the utility of the present approach.

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

Spectroscopic features of dissolved iodine in pristine and gamma-irradiated nitric acid solutions

While iodine speciation is important for a wide range of nuclear activities, understanding the mechanisms of the transformations of iodine between chemical forms and the sensitivity of these transitions to solution conditions and exposure to radiation remains an active area of research. This work curates spectroscopic data from several experimental techniques and establishes their sensitivity and limitations in detecting changes in iodine speciation in both neutral and acidic regimes. The techniques include Raman spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy, 127 I NMR spectroscopy, and ultraviolet-visible (UV-Vis) spectroscopy. Analysis of these data indicates that these commonly accessible spectroscopies often have dynamic ranges of measurable concentrations that do not always overlap between all techniques. The experimental techniques are disparately sensitive to iodide (I - ), molecular iodine (I 2 ), iodate (IO 3 - ), and periodate (IO 4 - ) species. Raman, FTIR, and NMR spectra were subsequentially analyzed using two-dimensional correlation analyses to generate high-resolution autocorrelation spectra. Here, the use of these spectroscopies is then extended to tracking acidification-induced and gamma irradiation-induced transformations of dissolved sodium iodate in deionized water and concentrated nitric acid. Both dissolution into nitric acid and irradiation with a gamma source are demonstrated to perturb the iodine speciation promoting their assembly into molecular iodine (I 2 ) and/or triiodide (I 3 - ). While I 2 and I 3 - species are undetectable with FTIR spectroscopy and 127 I NMR spectroscopy, the species can be detected with UV-Vis spectroscopy, and in some instances, I 3 - can be detected with Raman spectroscopy in the low wavenumber region. Ultimately, the results of this work provide a path to designing optimal combinations of techniques to detect forms of iodine across a wide range of concentrations and conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Investigation of phase-transformation path in TiZrHf(VNbTa)x refractory high-entropy alloys and its effect on mechanical property

Refractory high-entropy alloys (RHEAs) show a great potential as structural materials due to their remarkable properties, such as high strength and thermal stability. Despite these advantages, the RHEAs still suffer from the limited ductility at room temperature. To overcome the strength-ductility trade-off, the new RHEA design strategy, transformation-induced plasticity (TRIP) HEAs, have been developed by applying metastability-engineering approach. With the newly developed RHEAs design strategy, we designed metastable RHEAs, TiZrHfVxNbxTax (x = 1.0, 0.5 and 0.1) with decrease of the β-stabilizing elements (V, Nb, and Ta) to promote the transformation-induced ductility and work-hardening capability. The proper addition of the β-stabilizing elements (V, Nb, and Ta) into the ternary equi-molar TiZrHf alloy (TiZrHfV 0.1 Nb 0.1 Ta 0.1 ) leads to stress/strain-induced phase transformation from the body-centered cubic (BCC) to hexagonal-close-packed (HCP) α' and/or orthorhombic α" phases. Here, detailed studies on the phase transformation sequence during the deformation were carried out using X-ray diffraction (XRD), electron back-scattered diffraction (EBSD), and transmission-electron microscope (TEM), which revealed the stepwise phase transformation that is responsible for the strong strain hardening behavior. Furthermore, we further suggested the new transformation-induced-plasticity (TRIP) HEA design strategy, applying the Bo-Md approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Single-shot Quantum Signal Processing Interferometry

Quantum systems of infinite dimension, such as bosonic oscillators, provide vast resources for quantum sensing. Yet, a general theory on how to manipulate such bosonic modes for sensing beyond parameter estimation is unknown. We present a general algorithmic framework, quantum signal processing interferometry (QSPI), for quantum sensing at the fundamental limits of quantum mechanics by generalizing Ramsey-type interferometry. Our QSPI sensing protocol relies on performing nonlinear polynomial transformations on the oscillator's quadrature operators by generalizing quantum signal processing (QSP) from qubits to hybrid qubit-oscillator systems. We use our QSPI sensing framework to make efficient binary decisions on a displacement channel in the single-shot limit. Theoretical analysis suggests the sensing accuracy, given a single-shot qubit measurement, scales inversely with the sensing time or circuit depth of the algorithm. We further concatenate a series of such binary decisions to perform parameter estimation in a bit-by-bit fashion. Numerical simulations are performed to support these statements. Our QSPI protocol offers a unified framework for quantum sensing using continuous-variable bosonic systems beyond parameter estimation and establishes a promising avenue toward efficient and scalable quantum control and quantum sensing schemes beyond the NISQ era.

Physics↗
DOE OSTI2020

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗