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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exascale Dislocation Simulator

ExaDiS, or Exascale Dislocation Simulator, is a set of software modules written to enable numerical simulations of large groups of moving and interacting dislocations, line defects in crystals responsible for crystal plasticity. By tracking time evolution of sufficiently large dislocation ensembles, ExaDiS predicts plasticity response and plastic strength of crystalline materials. ExaDiS is built around a library of core functions for Discrete Dislocation Dynamics method specifically written to perform efficient computations on GPUs.

Bertin, Nicolas↗
DOE OSTI2025

Hierarchical Hybrid Multifunctional Materials through Interface Engineering

This project focuses on the development of stimuli-responsive hybrid multifunctional materials. We place emphasis on the design, synthesis, structural characterization, evaluation of functional properties (electronic, thermal and optical) of several (1-x)Cu 2 Se/(x)WBGS hierarchical bulk composites between Cu 2 Se, a narrow band gap semiconductor (NBGS), with a range of wider band gap semiconductors (WBGS) such as CuMSe 2 (M = Al, Ga, In, Fe, Cr) and Cu 4 TiSe 4 . Cu2Se is a well-studied NBGS with excellent thermoelectric properties (high electrical conductivity, large thermopower, etc.) while CuMSe 2 and Cu 4 TiSe 4 are high performance solar absorber materials (large band gap, large absorption coefficient, etc.). Our primary objectives are (i) to demonstrate the ability to integrate dissimilar functional properties such as large optical absorption coefficient and high electronic conductivity, within (1-x)Cu 2 Se/(x)WBGS composite; and (ii) to establish the correlation between the hierarchical structural entanglement of Cu 2 Se with WBGS (CuMSe 2 or Cu 4 TiSe 4 ) phase, the interactions between native electronic defects within the coexisting phases in the resulting (1-x)Cu 2 Se/(x)WBGS bulk composites , and the impacts on their electronic conductivity, thermal transport and optical properties.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Estimation of high temperature low cycle fatigue on the basis of inelastic strain and strainrate

Fatigue life at elevated temperature can be predicted by introducing parametric values obtained from monotonic constitutive behavior into the Universal-Slopes Equation. For directionally solidified MAR-M200+HF at 975 C, these parameters are the maximum stress achievable under entirely plastic (time-independent) and purely creep (time-dependent) conditions and the corresponding inelastic strains, as well as the elastic modulus. For materials which exhibit plasticity/creep interaction, two more pairs of monotonic parameters must be evaluated for fatigue life prediction. This life-prediction method based on the Universal-Slopes Equation, resulted from a constitutive model characterizing monotonic and cyclic data as inelastic strainrate as a function of inelastic strain. Characterizing monotonic data is this way, permitted distinction between different material responses such as strain-hardening, strain-softening, and dynamic recovery effects. Understanding and defining the region of influence of each of these effects facilitated formulation of the constitutive model in relation to the mechanical and microstructural processes occurring in the material under cyclic loading.

Berkovits, A.↗
DOE OSTI2024

Mapping causal pathways with structural modes fingerprint for perovskite oxides

Abstract Causality is innate to the determination of the fundamental mechanism controlling any physical phenomena. However, combining causality within the standard practices of computational modelling to understand structure-functionality connections is extremely rare. This work proposes a fingerprint based on key structural modes for ABO 3 -type perovskite oxides and its derivatives, combined with causal models, for predicting Kohn–Sham energies. Our study of causal models captures the inherent coupling between structural modes such as rotation, tilt and antiferroelectric displacements, responsible for phase transition, polarization, magnetization and metal–insulator transition, exhibited by these materials. Although developed for modelling specific functionality, this method is universally applicable to derive other functionalities and even different material classes while tracking hidden causal mechanisms via structural distortions.

42 ENGINEERING↗
NASA NTRS2014

AVCOAT Density Characterization for Orion Multi-Purpose Crew Vehicle

The Orion Multi-Purpose Crew Vehicle (MPCV) will transport four crew members to and from lunar-class orbital destinations. The first orbital Exploration Flight Test (EFT-1) is scheduled for December 2014 and will provide valuable data on several systems, including the heat shield. The heat shield material is AvcoatTM, a mid-density ablator. Specifically, the heat shield contains a fiberglass-phenolic honeycomb structure filled with an ablative epoxy novolac resin. Post-flight characterization of the EFT-1 thermal protection system will be conducted in order to study the material response and measure the char front of the material. Avcoat density profiling will be conducted to study three critical material zones: char, pyrolysis, and virgin states as a function of material depth. As part of a ground test campaign, Avcoat coupons are tested at the NASA Ames Research Center Arc Jet Complex. The test campaign is set forth to study material response based on environments, perform Avcoat material density characterization, and compare the char depths from the HEAT sensor and density profiling studies. These investigations will then be compared to flight data in order to improve upon TPS material response models.

AVCOAT↗
DOE OSTI2020

Autonomous Strategies for Improved Performance and Reliability of Li‐Ion Batteries

Abstract The battery community has devoted significant effort to improve the performance and reliability of Li‐ion batteries through the development of new materials. The integration of autonomous function provides an alternative strategy to further extend performance. Autonomous material systems mimic the ability of biological systems to self‐protect, sense, regulate, and heal in response to damage and other environmental changes. When incorporated in batteries, these materials enable autonomic restoration of battery performance upon degradation, as well as autonomic shutdown or extinguishment in response to thermal runaway. Successful strategies for improving Li‐ion battery performance include controlled release of microencapsulated functional additives and the integration of self‐healing or adaptive interlayers and binders. These methods have been effective for stabilizing the solid electrolyte interface, preventing battery fires, restoring electrode conductivity, and suppressing Li dendrite growth. Challenges and opportunities exist in the further application of autonomous strategies in the battery environment. A greater variety of encapsulated additives with precise triggered‐release are needed to address specific battery degradation mechanisms. Incorporation of self‐healing polymers in solid‐state batteries facilitates improvement in interfacial and mechanical stability. The integration of autonomous strategies with battery management systems potentially enables enhanced control over multiple battery cycling parameters.

Zhao, Lihong↗
DOE OSTI2023

Correlating structural changes in thermoresponsive hydrogels to the optical response of embedded plasmonic nanoparticles

Stimuli-responsive microgels, composed of small beads with soft, deformable polymer networks swollen through a combination of synthetic control over the polymer and its interaction with water, form a versatile platform for development of multifunctional and biocompatible sensors. The interfacial structural variation of such materials at a nanometer length scale is essential to their function, but not yet fully comprehended. Here, we take advantage of the plasmonic response of a gold nanorod embedded in a thermoresponsive microgel (AuNR@PNIPMAm) to monitor structural changes in the hydrogel directly near the nanorod surface. By direct comparison of the plasmon response against measurements of the hydrogel structure from dynamic light scattering and nuclear magnetic resonance, we find that the microgel shell of batch-polymerized AuNR@PNIPMAm exhibits a heterogeneous volume phase transition reflected by different onset temperatures for changes in the hydrodyanmic radius (R H ) and plasmon resonance, respectively. The new approach of contrasting plasmonic response (a measure of local surface hydrogel structure) with R H and relaxation times paves a new path to gain valuable insight for the design of plasmonic sensors based on stimuli-responsive hydrogels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

Modeling fluvial erosion on regional to continental scales

The fluvial system is a major concern in modeling landform evolution in response to tectonic deformation. Three stream bed types (bedrock, coarse-bed alluvial, and fine-bed alluvial) differ in factors controlling their occurrence and evolution and in appropriate modeling approaches. Spatial and temporal transitions among bed types occur in response to changes in sediment characteristics and tectonic deformation. Erosion in bedrock channels depends upon the ability to scour or pluck bed material; this detachment capacity is often a power function of drainage area and gradient. Exposure of bedrock in channel beds, due to rapid downcutting or resistant rock, slows the response of headwater catchments to downstream baselevel changes. Sediment routing through alluvial channels must account for supply from slope erosion, transport rates, abrasion, and sorting. In regional landform modeling, implicit rate laws must be developed for sediment production from erosion of sub-grid-scale slopes and small channels.

Howard, Alan D.↗
DOE OSTI2024

Two Spacers, One Perovskite: Integrating Ruddlesden–Popper and Dion–Jacobson Halide Perovskites

Hybrid organic–inorganic perovskites are a rapidly developing class of materials due to their desirable properties for optoelectronic applications such as their ease of synthesis, solution-processable film formation, tunable band gap, strong photoluminescence, good charge carrier mobilities, and high defect tolerance. Here, we present a novel 2D perovskite motif that seamlessly integrates the structural elements from both Ruddlesden–Popper and Dion–Jacobson halide perovskites. We demonstrate the incorporation of two different organic spacer cations in an ordered manner in 5 novel 2D perovskite iodide materials. Both a cyclic diammonium cation 3-(aminomethyl)piperidinium (3AMP) and a linear alkyl monoammonium cation (Cn = C n H 2n+4 N, n = 4–8) are present in distinct alternating layers, making the new series (Cn) 2 (3AMP)[PbI 4 ] 2 . The crystallization of these materials was optimized through careful temperature control to obtain precise crystal structures via single-crystal X-ray diffraction (XRD) which confirmed the presence of the two cations in distinct layers. The influence of the two spacers on optical properties including the band gaps and photoluminescence spectra are found to more closely resemble (3AMP)PbI 4 than (Cn) 2 PbI 4 , which can be attributed to the amount of distortion imposed by the 3AMP spacer on the lead iodide layers. The findings are supported by density functional theory calculations. The strong photoelectric response of solution-processed thin films shows the potential of these materials in photodetectors or photovoltaics. This unprecedented amalgamation of RP–DJ in (Cn) 2 (3AMP)[PbI 4 ] 2 in a structurally ordered fashion suggests a potential vastly underexplored phase space of 2D perovskites in which there are chemically different spacers in distinct layers of the structure, providing an additional parameter to tune perovskite properties.

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

High-Temperature Gas Sensor Materials with Properties Predicted via First-Principles Calculations with Machine Learning Modeling and Experimental Corroboration

Understanding the temperature dependence of functional properties of sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we first assess the temperature dependence of band gap renormalization in sensing materials by employing Allen-Heine-Cardona (AHC) theory with density functional theory (DFT) simulations corroborated with experimental observation. As the AHC calculations are impractical for high-throughput screening of materials, we employ data-driven Gaussian process regression to predict the parameters employed in the O’Donnell empirical model from a set of physical features. To mitigate the reliability issues arising from the small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as to quantify the uncertainty associated with theoretical predictions. These models capture well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions and, therefore, the variation of bandgap as a function of temperature for other novel materials. The predicted candidates from machine learning models are further validated by experiments and DFT calculations.

bandgap renormalization↗
DOE OSTI2025

Unraveling the Mechanism of Interfacial Charge Transfer and Photoresponsivity of WS 2 Quantum Dots/MoS 2 (0D–2D) Heterostructure-Based Transistors

To assess the efficacy of a mixed-dimensional van der Waals (vdW) heterostructure in modulating the optoelectronic responses of nanodevices, the charge transport properties of the transition-metal dichalcogenide (TMD)-based heterostructure comprising zero-dimensional (0D) WS 2 quantum dots (QDs) and two-dimensional (2D) MoS 2 flakes are critically analyzed. Herein, a facile strategy was materialized in developing an atomically thin phototransistor assembled from mechanically exfoliated MoS 2 and WS 2 QDs synthesized using a one-pot hydrothermal route. The amalgamated photodetectors exhibited a high responsivity of ∼8000 A/W at an incident power of 0.05 nW of white light, surpassing that of the pristine MoS 2 devices. Furthermore, the detectivity of pristine MoS 2 , which was on the order of 10 10 , increased to 10 12 Jones for the WS 2 QDs/MoS 2 heterostructure photodetector, outperforming other WS 2 -based materials. The quasiparticle band gap and density of states (DOS) are further analyzed to elucidate the photophysics of the WS 2 QD/MoS 2 hybrid assembly. The difference in the work function between MoS 2 and WS 2 QDs gives rise to an electric field across the 0D–2D interface, facilitating effective charge separation and migration and contributing to the enhancement of photoresponsivity. The analysis of optical responses using density functional theory (DFT) revealed stronger absorption and less reflection over a broader spectrum of wavelengths for the heterostructure compared to the pristine materials. The estimated optical conductivity aligns well with the experimentally predicted maximum photoresponsivity under visible light, which is attributed to the high absorbance of 2D MoS 2 . In conclusion, combining diverse spectroscopic and imaging techniques with quantum simulation provides insights that clarify the pertinence of 0D–2D TMDs in designing phototransistors.

WS2 QDs/MoS2 heterostructure↗
NASA NTRS2004

Analysis of Factors Affecting the Performance of RLV Thrust Cell Liners

The reusable launch vehicle (RLV) thrust cell liner, or thrust chamber, is a critical component of the Space Shuttle Main Engine (SSME). It is designed to operate in some of the most severe conditions seen in engineering practice. This requirement, in conjunction with experimentally observed 'dog-house' failure modes characterized by bulging and thinning of the cooling channel wall, provides the motivation to study the factors that influence RLV thrust cell liner performance. Factors or parameters believed to be directly related to the observed characteristic deformation modes leading to failure under in-service loading conditions are identified, and subsequently investigated using the cylindrical version of the higher-order theory for functionally graded materials in conjunction with the Robinson's unified viscoplasticity theory and the power-law creep model for modeling the response of the liner s constituents. Configurations are analyzed in which specific modifications in cooling channel wall thickness or constituent materials are made to determine the influence of these parameters on the deformations resulting in the observed failure modes in the outer walls of the cooling channel. The application of thermal barrier coatings and functional grading are also investigated within this context. Comparison of the higher-order theory results based on the Robinson and power-law creep model predictions has demonstrated that, using the available material parameters, the power-law creep model predicts more precisely the experimentally observed deformation leading to the 'dog-house' failure mode for multiple short cycles, while also providing much improved computational efficiency. However, for a single long cycle, both models predict virtually identical deformations. Increasing the power-law creep model coefficients produces appreciable deformations after just one long cycle that would normally be obtained after multiple cycles, thereby enhancing the efficiency of the analysis. This provides a basis for the development of an accelerated modeling procedure to further characterize dog-house deformation modes in RLV thrust cell liners. Additionally, the results presented herein have demonstrated that the mechanism responsible for deformation leading to 'dog-house' failure modes is driven by pressure, creep/relaxation and geometric effects.

Arnold, Steven M.↗
NASA NTRS2006

Effect of Thermomechanical Processing on the Microstructure, Properties, and Work Behavior of a Ti50.5 Ni29.5 Pt20 High-Temperature Shape Memory Alloy

TiNiPt shape memory alloys are particularly promising for use as solid state actuators in environments up to 300 C, due to a reasonable balance of properties, including acceptable work output. However, one of the challenges to commercializing a viable high-temperature shape memory alloy (HTSMA) is to establish the appropriate primary and secondary processing techniques for fabrication of the material in a required product form such as rod and wire. Consequently, a Ti(50.5)Ni(29.5)Pt20 alloy was processed using several techniques including single-pass high-temperature extrusion, multiple-pass high-temperature extrusion, and cold drawing to produce bar stock, thin rod, and fine wire, respectively. The effects of heat treatment on the hardness, grain size, room temperature tensile properties, and transformation temperatures of hot- and cold-worked material were examined. Basic tensile properties as a function of temperature and the strain-temperature response of the alloy under constant load, for the determination of work output, were also investigated for various forms of the Ti(50.5)Ni(29.5)Pt20 alloy, including fine wire.

Noebe, Ronald↗
NASA NTRS2003

Material-dependent and material-independent selection processes in the frontal and parietal lobes: an event-related fMRI investigation of response competition

The present study used the flanker task [Percept. Psychophys. 16 (1974) 143] to identify neural structures that support response selection processes, and to determine which of these structures respond differently depending on the type of stimulus material associated with the response. Participants performed two versions of the flanker task while undergoing event-related functional magnetic resonance imaging (fMRI). Both versions of the task required participants to respond to a central stimulus regardless of the responses associated with simultaneously presented flanking stimuli, but one used colored circle stimuli and the other used letter stimuli. Competition-related activation was identified by comparing Incongruent trials, in which the flanker stimuli indicated a different response than the central stimulus, to Neutral stimuli, in which the flanker stimuli indicated no response. A region within the right inferior frontal gyrus exhibited significantly more competition-related activation for the color stimuli, whereas regions within the middle frontal gyri of both hemispheres exhibited more competition-related activation for the letter stimuli. The border of the right middle frontal and inferior frontal gyri and the anterior cingulate cortex (ACC) were significantly activated by competition for both types of stimulus materials. Posterior foci demonstrated a similar pattern: left inferior parietal cortex showed greater competition-related activation for the letters, whereas right parietal cortex was significantly activated by competition for both materials. These findings indicate that the resolution of response competition invokes both material-dependent and material-independent processes.

Psychomotor Performance/physiology↗
DOE OSTI2025

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗
DOE OSTI2022

A directional microcrack damage theory for brittle solids based on continuous hyperplasticity

We present a novel microcrack-damage theory for brittle solids under compression. Instead of using internal variables like zeroth, second or fourth rank damage tensors, the state of material damage is represented by an internal function that encapsulates the information of direction, density and size of microcracks. Just like other internal variables, the evolution of this state function must obey the second law of thermodynamics for arbitrary loading paths. This is done by casting the model in the framework of continuous hyperplasticity and enforcing a non-negative dissipation rate functional. The proposed framework offers predictions on the continuous evolution of microcrack density and the induced material anisotropy along with the macroscopic stress-strain curves. The use of continuous damage function grants the model significantly enhanced resolution in characterizing the direction-dependent response of cracked solids compared to classical models that are based on damage tensors. Two scenarios are considered in developing the theory, one assumes frictionless cracks and the other incorporates friction between crack surfaces. The results highlight that inelasticity, pressure dependence, and loading-unloading hysteresis exhibited by brittle solids are natural consequences of frictional microcracks. The proposed theory offers a generic and versatile framework to upscale micromechanical processes operating at individual crack scale to explain the macroscopic behavior of cracked solids.

Materials Science↗
DOE OSTI2021

Core-shell metallic alloy nanopillars-in-dielectric hybrid metamaterials with magneto-plasmonic coupling

Combining plasmonic and magnetic properties, namely magneto-plasmonic coupling, inspires great research interest and the search for magneto-plasmonic nanostructure becomes considerably critical. In this work, we designed a nanopillar-in-matrix structure with core–shell alloyed nanopillars for both BaTiO 3 (BTO)-Au 0.5 Co 0.5 (AuCo) and BTO-Au 0.25 Cu 0.25 Co 0.25 Ni 0.25 (AuCuCoNi) hybrid systems, i.e., ferromagnetic alloy cores (e.g., Co or CoNi) with plasmonic shells (e.g., Au or Au/Cu). These core–shell alloy nanopillars are uniformly embedded into a dielectric BTO matrix to form a vertically aligned nanocomposite (VAN) structure. Both hybrid systems present excellent epitaxial quality and interesting multi-functionality, e.g., high magnetic anisotropy, magneto-optical coupling response, tailorable plasmonic resonance wavelength, tunable hyperbolic properties and strong optical anisotropy. These alloyed nanopillars-in-matrix designs provide enormous potential for complex hybrid material designs with multi-functionality and demonstrate strong interface enabled magneto-plasmonic coupling along with plasmonic and magnetic performance.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Verification and Validation of a Three-Dimensional Composite Impact Model with Tabulated Input

A material model which incorporates several key capabilities which have been identified by the aerospace community as lacking in the composite impact models currently available in the commercial transient dynamic finite element code LS-DYNA® has been developed. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. The capability to account for the rate and temperature dependent deformation response of composites has also been incorporated into the material model. For the damage model, a strain equivalent formulation is utilized to allow for the uncoupling of the deformation and damage analyses. In the damage model, a diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure, which allows an arbitrarily shaped failure surface to be defined. A systematic series of validation and verification studies, at a variety of length scales ranging from single element simulations to simulations of a flat panel impact test, have been performed to fully exercise and evaluate the capabilities of the developed model.

Impact↗