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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nanostructure‐Derived Antireflectivity in Leafhopper Brochosomes

Understanding how insect‐derived biomaterials interact with light has led to new advances and interdisciplinary insights in entomology and physics. Leafhoppers are insects that coat themselves with highly ordered biological nanostructures known as brochosomes. Brochosomes are thought to provide a range of protective properties to leafhoppers, such as hydrophobicity and antireflectivity, which has inspired the development of synthetic brochosomes that mimic their structures. Despite recent progress, the high antireflective properties of brochosome structures are not fully understood. Herein, a combination of experiments and computational modeling is used to understand the structure‐, material‐, and polarization‐dependent optical properties of brochosomes modeled on the geometries found in three leafhopper species. The results qualitatively represent that light interference interaction with nanostructures naturally occurring in brochosomes is responsible for the spectral tuning and the asymmetric line shape of the reflectance spectra. Whereas prior work has focused on the computational modeling of idealized pitted particles, this work shows that light–matter interactions with brochosome structures can be tuned by varying the geometry of their cage‐like nanoscale features and by changing the arrangement of multiparticle assemblies. Broadly, this work establishes principles for the guided design of new optically active materials inspired by these unique insect nanostructures.

Banerjee, Progna↗
DOE OSTI2016

Properties of hot and dense matter from relativistic heavy ion collisions

Here, we review the progress achieved in extracting the properties of hot and dense matter from relativistic heavy ion collisions at the relativistic heavy ion collider (RHIC) at Brookhaven National Laboratory and the large hadron collider (LHC) at CERN. We focus on bulk properties of the medium, in particular the evidence for thermalization, aspects of the equation of state, transport properties, as well as fluctuations and correlations. We also discuss the in-medium properties of hadrons with light and heavy quarks, and measurements of dileptons and quarkonia. Lastly, this review is dedicated to the memory of Gerald E. Brown.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Colloquium : Excitons in atomically thin transition metal dichalcogenides

Atomically thin materials such as graphene and monolayer transition metal dichalcogenides (TMDs) exhibit remarkable physical properties resulting from their reduced dimensionality and crystal symmetry. The family of semiconducting transition metal dichalcogenides is an especially promising platform for fundamental studies of two-dimensional (2D) systems, with potential applications in optoelectronics and valleytronics due to their direct band gap in the monolayer limit and highly efficient light-matter coupling. A crystal lattice with broken inversion symmetry combined with strong spin-orbit interactions leads to a unique combination of the spin and valley degrees of freedom. In addition, the 2D character of the monolayers and weak dielectric screening from the environment yield a significant enhancement of the Coulomb interaction. The resulting formation of bound electron-hole pairs, or excitons, dominates the optical and spin properties of the material. In this article, recent progress in understanding of the excitonic properties in monolayer TMDs is reviewed and future challenges are laid out. Discussed are the consequences of the strong direct and exchange Coulomb interaction, exciton light-matter coupling, and influence of finite carrier and electron-hole pair densities on the exciton properties in TMDs. Finally, the impact on valley polarization is described and the tuning of the energies and polarization observed in applied electric and magnetic fields is summarized.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Nanoscale Mechanical Behavior of Nuclear Materials

One of the primary performance objectives targeted for improved performance of nuclear fuels is fracture toughness. New materials or composite fuel architectures that offer greater resistance to cracking under the extreme environments encountered during nuclear reactor service would provide significant improvements to steady state (e.g. heat transfer, fuel redistribution) and transient (e.g. radionuclide release at elevated temperatures) conditions. Options currently under investigation include 'nontraditional' nuclear fuels designated around high uranium density. These include uranium silicides, uranium borides, and composite fuel materials constructed of these and uranium nitride or uranium dioxide. The increase uranium density compared with uranium dioxide (UO{sub 2}) has made them interesting to a new generation of nuclear fuels research driven by the renewed push for accident-tolerant light water reactor (LWR) fuels. Measurement of the thermophysical and thermodynamic properties of these constituent materials has progressed in recent years, but evaluation of mechanical properties at relevant temperatures is necessary to support further evaluations. While thermophysical properties such as thermal conductivity, heat capacity, and thermal expansion are generally the primary properties of interest, mechanical properties will play an important role in governing the deformation and fracture of the fuel during both normal operation and potential transients. It is therefore necessary to develop techniques capable of measuring these properties to predict the response of a candidate fuel form to anticipated thermal gradients. Nanoindentation techniques provide a demonstrated alternative to traditional mechanical test methods. Much work has also been carried out over the past few years to obtain stress-strain curves using a spherical nanoindentation approach. The techniques are expected to be useful for measurement of the mechanical properties of local structure of various materials. Nanomechanical test techniques have particular value in the area of nuclear materials, where numerous factors motivate limiting the sample volume to the extent possible. However, few attempts at application of nanoindentation to evaluate the mechanical properties of the nuclear fuels and cladding materials are reported in the literature. The effect of a limited set of variables (e.g. porosity, temperature dependence) on the mechanical properties of UO{sub 2} has been explored using early nanomechanical testing techniques. However, nanomechanical evaluation has not been extended to other nuclear fuels. In this work, we demonstrate the effectiveness of using instrumented spherical nanoindentation test techniques to capture the mechanical response of regions within individual grains in ion-irradiated W and Zr over a range of ion-irradiation conditions. As well as the nanomechanical response of U-Si and UO{sub 2} fuel materials Nanoindentation results obtained at room temperature will be used to express nano- and bulk- mechanical properties as a function of material stoichiometry. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Fuel Property Characterization and Prediction

This presentation describes the progress made over the last year on the Fuel Property Characterization and Prediction tasks as part of the CoOptima program under the Vehicle Technologies Office. The tasks reviewed are: Fuel Property Blending Model (F.1.2.2 and F.1.2.3), the Heat of Vaporization Measurement for Full Boiling Range Fuels (F.1.3.2), and the Flow Reactor Autoignition Kinetic Mechanism Development and Validation (F.2.1.4) tasks.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Quantifying the hierarchy of structural and mechanical length scales in granular systems

Continuum modeling of granular media is made possible by the existence of a length scale at and above which grain-resolved properties can be meaningfully homogenized. Progress has been made in identifying such length scales relevant to local structural properties such as porosity. However, a systematic analysis of scales above which different mechanical properties can be homogenized has yet to emerge. Here, X-ray tomography and 3D X-ray diffraction data are examined to identify such length scales. The data was obtained in-situ in compressed granular materials with rigid and flexible confinement. The experimental data are supplemented with validated discrete element simulations which examine different system sizes and different boundary conditions. Overall, our study reveals a hierarchy in the length scales of granular solids, with lengths governing structural variables being the shortest, lengths of stress variables being intermediate, and lengths of energy dissipation being the longest. All structural and mechanical length scales obey a power law based on the theory of Geostatistics, implying that the length scales can be found by analyzing samples significantly smaller than the length scales themselves. The length scales are also found to be sensitive to boundary conditions, implying that they are extrinsic features of granular media.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Controlling the corrosion resistance of multi-principal element alloys

Multi-principal element alloys (MPEAs) offer the possibility of many degrees of freedom in the choice of alloying elements to produce either single phase solid solutions or more complex multiphase microstructures. Large ranges of material properties have been observed for MPEAs and mastery of the selection of elements and their compositions can enable novel combinations of properties not possible in traditional alloys. From the aqueous corrosion perspective, optimization of phase stability, control of heterogeneities, passive film identity and its protectiveness, as well as substrate properties such as metal-metal bond strength and activation energy associated with dissolution, can all be controlling factors governed by alloy composition and structure. These factors can mediate the electrochemical reactions controlling spontaneous corrosion. The quest for superior properties based on well-informed element choice is suggested as a path forward guiding MPEA formulations for corrosion performance. However, gaps in fundamental knowledge exist regarding (a) the specific functions of each element, (b) the behavior of elements in unusual combinations, and (c) the formation of complex protective oxides. These issues currently hold back progress in optimization of corrosion properties.

Scully, John R.↗
DOE OSTI2014

From Ag{sub 2}Sb{sub 2}O{sub 6} to Cd{sub 2}Sb{sub 2}O{sub 7}: Investigations on an anion-deficient to ideal pyrochlore solid solution

A complete solid solution between the anion-deficient pyrochlore Ag{sub 2}Sb{sub 2}O{sub 6} and the ideal pyrochlore Cd{sub 2}Sb{sub 2}O{sub 7} has been synthesized through the standard solid state ceramic method. Each composition has been characterized by various different techniques, including powder X-ray diffraction, optical spectroscopy, electron paramagnetic resonance and {sup 121}Sb Mössbauer spectroscopy. Computational methods based on density functional theory complement this investigation. Photocatalytic activity has been studied, and transport properties have been measured on pellets densified by spark plasma sintering. The analysis of the data collected from these various techniques enables a comprehensive characterization of the complete solid solution and revealed an anomalous behavior in the Cd-rich end of the solid solution, which has been proposed to arise from a possible radical O{sup −} species in small concentrations. - Graphical abstract: A complete solid solution between the anion-deficient pyrochlore Ag{sub 2}Sb{sub 2}O{sub 6} and the ideal pyrochlore Cd{sub 2}Sb{sub 2}O{sub 7} has been synthesized and investigated through various techniques including X-ray diffraction, electron paramagnetic spectroscopy, and {sup 121}Sb-Mössbauer spectroscopy. Optical and electrical measurements have been performed, and computational methods have been applied to determine the density of states. Photocatalytic activity was monitored by the degradation of Methylene Blue, and upon cadmium substitution, the degradation amount decreased, which is attributed primarily to the changing optical and electrical properties of the solid solution. Display Omitted - Highlights: • A complete solid solution between Ag{sub 2}Sb{sub 2}O{sub 6} and Cd{sub 2}Sb{sub 2}O{sub 7} has been synthesized. • XRD reveals a relatively constant lattice parameter as the series progresses. • Optical and electrical properties have been measured for the solid solution. • Computational methods have been used to determine the density of states. • Photocatalytic degradation of Methylene Blue decreased upon cadmium substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Neutrino properties deduced from the study of lepton number violating processes at low and high energies

There is nowadays a significant progress in understanding the neutrino properties. The results of the neutrino oscillation experiments have convincingly showed that neutrinos have mass and oscillate, in contradiction with the Standard Model (SM) assumptions, and these are the first evidences of beyond SM physics. However, fundamental properties of the neutrinos like their absolute mass, their character (are they Dirac or Majorana particles?), their mass hierarchy, the number of neutrino flavors, etc., still remain unknown. In this context there is an increased interest in the study of the lepton number violating (LNV) processes, since they could complete our understanding on the neutrino properties. Since recently, the neutrinoless double beta decay was considered the only process able to distinguish between Dirac or Majorana neutrinos and to give a hint on the absolute mass of the electron neutrino. At present, the increased luminosity of the LHC experiments makes feasible the search of LNV processes at high energy as well. In this lecture I will make a brief review on our present knowledge of the neutrino properties, on the present status of the double-beta decay studies and on the first attempts to search LNV processes at LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Recent Progress in the Understanding of UK Highly Active Liquor Chemistry and Properties - 17144

In the UK Highly Active Liquor (HAL) waste is stored in stainless steel tanks prior to encapsulation in glass in one of three lines in the Waste Vitrification Plant (WVP). The chemistry and physical properties of HAL from the historic and ongoing UK reprocessing operations is well understood, following years of operations and associated research and development programmes using primarily non-active simulants. However the imminent progression to POCO of the Highly Active Storage Tanks (HASTs), where the HAL is stored, requires a more in-depth understanding of the properties of the HAL, in particular the solid phases that are known to exist. Changes in operations are expected, including the addition of new chemical wash reagents, which will result in some fundamental changes to the chemistry in the HASTs. This paper will highlight some of the key findings from recent studies into areas such as solids formation and morphology, chemical dissolution and associated re-precipitation of solids, rheology modification and chemical conversion mechanisms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Synthesis, characterization of double perovskite Ca{sub 2}MSbO{sub 6} (M = Dy, Fe, Cr, Al) materials via sol–gel auto-combustion and their catalytic properties

Double perovskite-type oxide Ca{sub 2}MSbO{sub 6} materials, where M = Dy, Fe, Cr, and Al, were prepared by using the sol–gel auto-combustion method. The role of different B-site cations on their synthesis, structures, morphologies and catalytic properties was investigated. The progress of double-perovskite type structure formation and the disappearance of the organic phases were monitored by infrared absorption spectroscopy (FTIR). Double perovskite oxide structures were evaluated using X-ray diffraction (XRD), while the microstructure of obtained compounds was studied using scanning electron microscopy (SEM). Also, BET surface areas were measured at the liquid nitrogen temperature by nitrogen adsorption. Catalytic properties of the obtained compounds were evaluated by test reaction of hydrogen peroxide decomposition. - Highlights: • Ca{sub 2}MSbO{sub 6} double perovskites were obtained by sol–gel auto-combustion method. • Ca{sub 2}MSbO{sub 6} (M = Dy, Fe, Cr and Al) as catalysts in H{sub 2}O{sub 2} decomposition • Strong relationship between particles' shape, BET area and catalytic performance • Ca{sub 2}FeSbO{sub 6} spherical grains show superior catalytic activity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Progress and outlook of Sn–Pb mixed perovskite solar cells

Abstract Organic–inorganic hybrid perovskites have revolutionized solar cell research owing to their excellent material properties. Most previous research has been done on Pb-based perovskites. Recently, efforts to discover a Pb-free or Pb-less perovskite material with an ideal bandgap ranging 1.1–1.3 eV have led researchers to investigate Sn–Pb mixed perovskites. Sn–Pb mixed perovskites have a bandgap of ~ 1.25 eV, which is suitable for high-efficiency single-junction and perovskite/perovskite tandem solar cells. Moreover, the Pb content of Sn–Pb mixed perovskites is 50–60% lower than that of Pb-based perovskites, partially mitigating the Pb toxicity issue. However, incorporating Sn 2+ into the crystal structure also causes various drawbacks, such as inhomogeneous thin film morphologies, easy oxidation of Sn 2+ , and more vulnerable surface properties. Researchers have made substantial progress in addressing these challenges through improvements in compositional design, structural optimization, precursor design, and surface treatments. In this review, we provide a comprehensive overview of the progress in Sn–Pb mixed perovskite solar cells. Furthermore, we analyze the key variables and trends as well as provide an outlook for future directions in the research on Sn–Pb mixed perovskites. Graphical Abstract

14 SOLAR ENERGY↗
DOE OSTI2018

Carbon-Nanotube-Based Thermoelectric Materials and Devices

Conversion of waste heat to voltage has the potential to significantly reduce the carbon footprint of a number of critical energy sectors, such as the transportation and electricity-generation sectors, and manufacturing processes. Thermal energy is also an abundant low-flux source that can be harnessed to power portable/wearable electronic devices and critical components in remote off-grid locations. As such, a number of different inorganic and organic materials are being explored for their potential in thermoelectric-energy-harvesting devices. Carbon-based thermoelectric materials are particularly attractive due to their use of nontoxic, abundant source-materials, their amenability to high-throughput solution-phase fabrication routes, and the high specific energy (i.e., W g-1) enabled by their low mass. Single-walled carbon nanotubes (SWCNTs) represent a unique 1D carbon allotrope with structural, electrical, and thermal properties that enable efficient thermoelectric-energy conversion. Here, the progress made toward understanding the fundamental thermoelectric properties of SWCNTs, nanotube-based composites, and thermoelectric devices prepared from these materials is reviewed in detail. This progress illuminates the tremendous potential that carbon-nanotube-based materials and composites have for producing high-performance next-generation devices for thermoelectric-energy harvesting.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Atomic-Scale Manipulation and In Situ Characterization with Scanning Tunneling Microscopy

Scanning tunneling microscope (STM) has presented a revolutionary methodology to nanoscience and nanotechnology. It enables imaging of the topography of surfaces, mapping the distribution of electronic density of states, and manipulating individual atoms and molecules, all at atomic resolutions. In particular, atom manipulation capability has evolved from fabricating individual nanostructures toward the scalable production of the atomic-sized devices bottom-up. The combination of precision synthesis and in situ characterization has enabled direct visualization of many quantum phenomena and fast proof-of-principle testing of quantum device functions with immediate feedback to guide improved synthesis. Several representative examples are reviewed to demonstrate the recent development of atomic-scale manipulation, focusing on progress that addresses quantum properties by design in several technologically relevant materials systems. Integration of several atomically precisely controlled probes in a multiprobe STM system vastly extends the capability of in situ characterization to a new dimension where the charge and spin transport behaviors can be examined from mesoscopic to atomic length scale. The automation of atomic-scale manipulation and the integration with well-established lithographic processes further push this bottom-up approach to a new level that combines reproducible fabrication, extraordinary programmability, and the ability to produce large-scale arrays of quantum structures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

An adaptive granular representative volume element model with an evolutionary periodic boundary for hierarchical multiscale analysis

The hierarchical multiscale analysis normally utilizes a microscopic representative volume element (RVE) model to capture path/history-dependent macroscopic responses instead of using phenomenological constitutive models. However, for problems involving large deformation, the current RVE model used in geomechanics may lose representative properties due to the progressive distortion of the RVE box, unless a proper reinitialization is applied. This work develops an adaptive RVE model in conjunction with an evolutionary periodic boundary (EPB) algorithm for hierarchical multiscale analysis of granular materials undergoing large deformation based on a recent RVE model proposed for coupling molecular dynamics and the material point method. The proposed adaptive RVE model avoids the reinitialization of the RVE box that even undergoes extremely large shear deformation; meanwhile, it accounts for the deformation history of the RVE model and treats the interaction between boundary particles and other image particles in a more efficient way. Numerical examples with extremely large deformation are used to illustrate the adaptive granular RVE model enhanced by the proposed EPB algorithm. Furthermore, some key features of this new methodology are further discussed for clarification.

42 ENGINEERING↗