Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “progress properties”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Simulating the Impact Response of Composite Airframe Components

In 2010, NASA Langley Research Center obtained residual hardware from the US Army's Survivable Affordable Repairable Airframe Program (SARAP). The hardware consisted of a composite fuselage section that was representative of the center section of a Black Hawk helicopter. The section was fabricated by Sikorsky Aircraft Corporation and designated the Test Validation Article (TVA). The TVA was subjected to a vertical drop test in 2008 to evaluate a tilting roof concept to limit the intrusion of overhead mass items, such as the rotor transmission, into the fuselage cabin. As a result of the 2008 test, damage to the hardware was limited primarily to the roof. Consequently, when the post-test article was obtained in 2010, the roof area was removed and the remaining structure was cut into six different types of test specimens including: (1) tension and compression coupons for material property characterization, (2) I-beam sections, (3) T-sections, (4) cruciform sections, (5) a large subfloor section, and (6) a forward framed fuselage section. In 2011, NASA and Sikorsky entered into a cooperative research agreement to study the impact responses of composite airframe structures and to evaluate the capabilities of the explicit transient dynamic finite element code, LS-DYNA®, to simulate these responses including damage initiation and progressive failure. Finite element models of the composite specimens were developed and impact simulations were performed. The properties of the composite material were represented using both a progressive in-plane damage model (Mat 54) and a continuum damage mechanics model (Mat 58) in LS-DYNA. This paper provides test-analysis comparisons of time history responses and the location and type of damage for representative I-beam, T-section, and cruciform section components.

Jackson, Karen E.↗
DOE OSTI2019

Designing polymers for advanced battery chemistries

Electrochemical energy storage devices are becoming increasingly important to our global society, and polymer materials are key components of these devices. As the demand for high-energy density devices increases, innovative new materials that build on the fundamental understanding of physical phenomena and structure–property relationships will be required to enable high-capacity next-generation battery chemistries. In this Review, we discuss core polymer science principles that are used to facilitate progress in battery materials development. Specifically, we discuss the design of polymeric materials for desired mechanical properties, increased ionic and electronic conductivity and specific chemical interactions. We also discuss how polymer materials have been designed to create stable artificial interfaces and improve battery safety. Furthermore, the focus is on these design principles applied to advanced silicon, lithium-metal and sulfur battery chemistries.

25 ENERGY STORAGE↗
DOE OSTI2020

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗
DOE OSTI2019

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M↗
DOE OSTI2025

Spin excitations and dynamics in 2D magnets: An overview of magnons and magnetic skyrmions

van der Waals magnetic materials open up exciting possibilities to investigate fundamental spin properties in low-dimensional systems and to build compact functional spintronic structures. This review focuses on the recent progress in two-dimensional (2D) magnets that explore beyond the homogenous magnetically ordered state, including magnons (spin waves), magnetic skyrmions, and complex magnetic domains. Properties of these spin and topology excitations in 2D magnets provide insights into spin-orbit interactions and other forms of coupling between electrons, phonons, and spin-dependent excitations. Such spin-based quasiparticles can also serve as information carriers for next-generation high-speed computing elements. Furthermore, we will first lay out the general theoretical basis of dynamical responses in magnetic systems, followed by detailed descriptions of experimental progress in magnons and spin textures (including magnetic domains and skyrmions). Discussion on the experimental techniques and future perspectives are also included.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Recent progress of magnetocaloric effect and magnetic refrigerant materials of Mn compounds (invited)

Magnetocaloric and related properties of Ru and Ni substituted (MnFe){sub 2}(PSi) are presented. It is found that Ru and Ni are effective doping elements to reduce the thermal hysteresis of (MnFe){sub 2}(PSi). The origin of the thermal hysteresis is discussed on the basis of a thermodynamic model. It is shown that the elastic energy is responsible for the thermal hysteresis. We also show recent developments of the production process of Mn compounds in an industrial scale.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Final Progress Report

The research in this program involves theoretical investigations of electronic, optical and mechanical properties of graphene and its derivatives, such as bi-layer graphene, graphene-based van der Waals heterostructures, strained graphene, as well as graphene on various surfaces. One line of research has been development of theoretical models that support graphene’s large array of possible technological applications. For example one of our goals has been the understanding of surface plasmons and spin relaxation mechanisms in graphene, related to novel optoelectronics and spintronics applications. Our current research focus is on understanding the role of correlations in graphene under mechanical deformations, such as strain. The main goal is to describe the mutual interplay between strain and electron-electron interactions which could lead to the formation of novel elec- tronic phases with strongly modified electronic, magnetic and optical properties. This direction of research contributes to deeper understanding of interactions in graphene and related atomically-thin materials - a subject at the forefront of research on graphene and its derivatives.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

The Effect of Process History on Grain Boundaries and Dislocation Substructures on Functional Properties of Nb for SRF Cavities: Plastic Formability and Microstructural Evolution. Final report

While much progress has been made in improving the performance of cavities in the past decade, reproducible performance remains elusive. This renewal of “The cost of grain boundaries on the performance of superconducting cavities” examines in further depth the interactions between forming and annealing processes and functional performance at the scale of dislocation substructure and grain boundaries. There are five tasks identified in the renewal, which are: Characterization / analysis of current cavity technology: Effect of deformation, heat treatment, surface treatments, and residual damage on cavity function (Lee and Bieler) Characterization of dislocation mechanisms in single and bicrystals (Bieler) Quantifying effects of impurities and deformation mechanisms in Nb using density functional theory calculations (Solanki) Crystal plasticity constitutive model development (Pourboghrat and Eisenlohr) Modeling and measuring thermal conductivity in thin layers (Wright)

36 MATERIALS SCIENCE↗
DOE OSTI2018

Lysophosphatidic acid receptor-2 (LPA2) and LPA5 regulate cellular functions during tumor progression in fibrosarcoma HT1080 cells

Highlights: • LPAR2 and LPAR5 expressions were elevated by long-term anticancer drug treatment in HT1080 cells. • Highly invasion HT1080-M6 cells were generated from HT1080 cells using Matrigel-coated filters. • HT1080-M6 cell invasion was shown to be 4.5 times higher than that of HT1080 cells. • The cell motile and invasive activities of HT1080-M6 cells were reduced by LPA{sub 2} inhibition. • LPA signaling via LPA{sub 2} is a potent target for the regulation of tumor progression in HT1080 cells. Lysophosphatidic acid (LPA) receptors (LPA{sub 1} to LPA{sub 6}) regulate a variety of malignant properties in cancer cells. In the present study, we investigated the roles of LPA receptors in the promotion of cellular functions during tumor progression in fibrosarcoma cells. To obtain long-term anticancer drug treated cells, human fibrosarcoma HT1080 cells were treated with methotrexate (MTX) and cisplatin (CDDP) for 6 months. LPAR2 and LPAR5 expressions were significantly higher in MTX-treated (HT-MTX) cells than in HT1080 cells. The cell motile and invasive activities of HT-MTX cells were significantly elevated compared with HT1080 cells. Although LPAR5 expression was increased in MTX and CDDP treated (HT-M-C) cells, no change of LPAR2 expression was observed. The cell motile and invasive activities of HT-M-C cells were lower than those of HT1080 cells. Moreover, to evaluate whether LPA receptors promote cell invasive activity, highly invasion (HT1080-M6) cells were established from HT1080 cells. The cell invasive activity of HT1080-M6 cells was approximately 4.5 times higher than HT1080 cell invasion. LPAR2 expression was markedly elevated in HT1080-M6 cells compared with HT1080 cells. The high cell invasion activity of HT1080-M6 cells was significantly suppressed by an antagonist of LPA{sub 2}, H2L5186303. These results suggest that LPA{sub 2} acts as a key regulator of malignant properties in HT1080 cells.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Microcracking in composite laminates under thermal and mechanical loading

Composites used in space structures are exposed to both extremes in temperature and applied mechanical loads. Cracks in the matrix form, changing the laminate thermoelastic properties. The goal of the present investigation is to develop a predictive methodology to quantify microcracking in general composite laminates under both thermal and mechanical loading. This objective is successfully met through a combination of analytical modeling and experimental investigation. In the analysis, the stress and displacement distributions in the vicinity of a crack are determined using a shear lag model. These are incorporated into an energy based cracking criterion to determine the favorability of crack formation. A progressive damage algorithm allows the inclusion of material softening effects and temperature-dependent material properties. The analysis is implemented by a computer code which gives predicted crack density and degraded laminate properties as functions of any thermomechanical load history. Extensive experimentation provides verification of the analysis. AS4/3501-6 graphite/epoxy laminates are manufactured with three different layups to investigate ply thickness and orientation effects. Thermal specimens are cooled to progressively lower temperatures down to -184 C. After conditioning the specimens to each temperature, cracks are counted on their edges using optical microscopy and in their interiors by sanding to incremental depths. Tensile coupons are loaded monotonically to progressively higher loads until failure. Cracks are counted on the coupon edges after each loading. A data fit to all available results provides input parameters for the analysis and shows them to be material properties, independent of geometry and loading. Correlation between experiment and analysis is generally very good under both thermal and mechanical loading, showing the methodology to be a powerful, unified tool. Delayed crack initiation observed in a few cases is attributed to a lack of preexisting flaws assumed by the analysis. Some interactions between adjacent ply groups are attributed to local stress concentrations. These two effects are not captured by the analysis due to its global nature. The analysis is conservative in these cases and agrees well with data after the observed onset of cracking.

Maddocks, Jason R.↗
DOE OSTI2021

The Buckling Spectra of Nanoparticle Surfactant Assemblies

Fine control over the mechanical properties of thin sheets underpins transcytosis, cell shape, and morphogenesis. Applying these principles to artificial, liquid-based systems has led to reconfigurable materials for soft robotics, actuation, and chemical synthesis. However, progress is limited by a lack of synthetic two-dimensional membranes that exhibit tunable mechanical properties over a comparable range to that seen in nature. In this study, we show that the bending modulus, B , of thin assemblies of nanoparticle surfactants (NPSs) at the oil–water interface can be varied continuously from sub- k B T to 10 6 k B T , by varying the ligands and particles that comprise the NPS. We find extensive departure from continuum behavior, including enormous mechanical anisotropy and a power law relation between B and the buckling spectrum width. Our findings provide a platform for shape-changing liquid devices and motivate new theories for the description of thin-film wrinkling.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Ocean Energy: Markets - Currency - Impact. Dimension of & Choices in the Technology Development Space: Preprint

This paper presents considerations of the employment of ocean wave energy to support different energy demand side applications. The key aspect in these considerations is the wave energy supported achievable positive impact and associated tangible contribution in service of common societal good and of the natural commons. The level of impact that can be delivered is dependent on both, the level of contribution of the supported energy use application, and the compatibility and unique suitability of the wave energy resource and its characteristics with the needs of the application. Thus, a variety of ocean wave energy markets, the key value indicators or "currency' in which these markets trade the value delivered and the achievable positive impact, are reflected upon. Ocean wave energy supported acquisition of high quality ocean system data across a wide spectrum of system properties is identified as a highly impactful application enabling and/or improving a comprehensive range of impactful ocean system activities. The technology development process towards these markets and desired impacts requires relevant technology development progress guidance and metrics. Going beyond technology readiness levels and technology performance levels, the notion of further technology development progress scales towards high impact and high contribution are proposed. These scales and the associated technology properties can be regarded as additional technology development dimensions to span-up the technology development space in which desired system capability and functional requirement choices and subsequent ideation, innovation, research and technology development decisions can and are to be made.

data market↗
DOE OSTI2023

Ab initio Geochemistry of Hydrous Phases (Final Report)

Hydrous phases are among the most important Earth components. They are important for a broad suite of Earth processes, including the origin of life. From both thermodynamic and structural perspectives, however, they represent some of the most complex naturally occurring materials: their bonding often includes a combination of covalent solid, weak ionic, van der Waals, and hydrogen bonding, all within large unit cells. Most are solid solutions, and many are prone to variations in layer packing. Thermodynamic modeling of these materials is fundamental for understanding present and past natural processes, including those that shaped—and continue to shape—the structure and evolution of our planet. Yet, the thermodynamic properties of these materials at appropriate conditions are challenging to measure. To make significant progress and attain a deep understanding of these materials requires an atomistic theoretical approach.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Progress With Multi-Cell Nb3Sn Cavity Development Linked With Sample Materials Characterization

Exploiting both the new Nb3Sn coating system and the materials characterization tools nearby, we report our progress in low-loss Nb3Sn films development. Nb3Sn films a few micrometers thick were grown on Nb coupons as well as single- and multi-cell cavities by the Sn-diffusion technique. Films structure and composition were investigated on coated samples and cavity cutouts with characterization tools including SEM/EDS/EBSD, AFM, XPS, SIMS towards correlating film growth and RF loss to material properties and deposition parameters. Cavity coating efforts focused on establishing techniques for coating progressively more complicated RF structures, and understanding limiting mechanisms in coated cavities. Nb3Sn coated 1.5 GHz 1-cell and 1.3 GHz 2-cell cavities have shown quality factors of 1010 at 4.3 K, with several cavities reaching above Eacc = 10 MV/m. The dominant limiting mechanisms were low field quenches and quality factor degradation above 8 MV/m. The surface data indicates a near-stoichiometric Nb3Sn consistent with the transition temperature and gap measurements. The Nb3Sn layer is covered with Nb2O5 and SnO2 native oxides and has little memory of the pre-coating surface.

Eremeev, Grigory V.↗