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Results for “functionally graded material”

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 OSTI2019

Investigation of deep levels in CdZnTeSe crystal and their effect on the internal electric field of CdZnTeSe gamma-ray detector

A study of deep levels in CdZnTeSe radiationdetection materials is presented. The approach relies on electrical methods that combine time and temperature evolution of the electric field and electric current after switching on the bias voltage. Two optical methods were also applied to study the deep levels. The first method utilizes the temperature and temporal analysis of the electric-field evolution after switching off an additional light illuminating the sample at a wavelength of 940 nm. The second method involved measuring of the electric-field spectral dependence during near infrared illumination. The results are compared with those obtained with high-quality CdZnTe detector-grade material. We conclude that the introduction of Se into the lattice leads to a shift of the second ionization level of the Cd vacancy towards the conduction band, as predicted recently by first-principles calculations based on screened hybrid functionals.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Graphite Characterization: Baseline Variability Analysis Report

The Idaho National INL’s Baseline Material Property program provides many measurements of different material properties on a variety of nuclear graphite grades being investigated for irradiation-induced changes in material properties. The baseline material properties provide an unirradiated reference for comparison with measurements of those properties after irradiation. This study describes how uncertainty, or variance, in estimates of important material properties, like compressive strength, may depend on sample size, sample distribution and parameter estimation methods. Compressive strength data from two large collections of specimens from a billet of PCEA graphite (sample size = 230) and a billet of IG-110 graphite (sample size = 48) are used to illustrate these dependencies. The grades of graphite used represent approximate end members in terms of relative variability in strength measurements. Monte Carlo simulation and bootstrapping methods were used to examine variance in Weibull-parameter estimates as a function of sample size. Results were consistent with what previous statistical analyses have shown about the relationship between sample size and width of the confidence interval for maximum likelihood (ML) estimated parameters when samples are repeatedly drawn from a Weibull distribution. As a function of sample size, the precision of the modulus estimate increases faster than that of the characteristic strength. The modulus maximum likelihood estimates (MLEs) are biased for low sample sizes. The American Society for Testing and Materials document ASTM D7846-16 provides equations that describe the dependence of the variance of parameter MLEs on sample size. Using the same methodology, we show that the polynomials provided for variance dependence on sample size are inaccurate for sample sizes greater than ~120. We provide approximations to that relationship that illustrate relative constancy for sample size > ~10, in the logspace relationship of the modulus variance and the log transformed characteristic strength variance. Bootstrapping provided a means of comparing Weibull parameters obtained using ASME’s guidance for specimen collection to those obtained using different weighting in a case where strength is related to position in a billet and to grain orientation and a single distribution is used to characterize the billet. ASME specifies that samples be collected with equal representation in all locations and grain orientations. Parameter values obtained using ASME’s method were different from those obtained using random sampling of the complete data sets, and this was particularly true for the PCEA data. In addition, while the ASME approach yielded more conservative parameters for the PCEA data, the opposite was true for the IG-110 data. The difference observed for the PCEA data set likely reflects the larger number of against-grain specimens collected, which had generally higher strength than the with-grain specimens. This emphasizes the importance of the dependence of strength on location or grain orientation and suggests that it may be prudent to weight specimen collection toward the weaker subgroups if a conservative estimate as desired, as the equal weighting method recommended by ASME would will not always provide the most conservative Weibull parameters. Because spatial correlations commonly exist in certain grades of graphite, future work may involve developing a methodology for parameter inference that relaxes the assumption of independent specimens. ASTM and ASME codes recommend different parameter estimation methods and models of the Weibull distribution in different situations. Descriptions of the effects on parameter estimates for the example billets used in this study provide an example of how the method may affect the parameter estimate, and how—in this case—that compares to differences due to other factors, such as sample size and dependence on grain orientation or sample location.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Ensemble cure kinetics network (ECK-Net): A method to derive cure kinetics of thermosetting resin

This paper introduces an Ensemble Cure Kinetics Network (ECK-Net), a neural network (NN)–based framework for modeling the cure kinetics of thermosetting resins within a phenomenological context. ECK-Net replaces traditional analytic models, which require extensive chemical insight and multiple isothermal/non-isothermal experiments, with a data-driven surrogate that maps nonlinear relationships between temperature, degree of cure, and reaction rate from differential scanning calorimetry data. The proposed approach predicts input-dependent kinetic coefficients of a generalized nth-order reaction equation rather than reaction rates directly, enabling a single unified model to represent various epoxy systems without relying on iso-conversional analysis or predefined functional forms. To ensure robustness, multiple independently trained networks under different random initializations are blended through an ensemble strategy, effectively mitigating the stochastic variability inherent to neural networks. The framework is validated using experimental datasets from multiple resin systems, including aerospace-grade materials (Toray 3900-2, Cycom 5320-1, and Hexcel 8552) and a windmill-grade resin (RIMR 035c). The model accurately reproduces the temporal evolution of the degree of cure under manufacturers’ recommended cure cycles across all tested resins systems, yielding Pearson’s correlation coefficients of 0.992, 0.994, 0.993, 0.997, respectively. To demonstrate process-level applicability, the trained network was implemented within the Abaqus environment to simulate out-of-autoclave (OOA) curing process of the CFRP panel composed of Toray T830H-6K/3900-2D prepreg. The simulation results showed excellent agreement with experimental temperature response (maximum peak temperature, simulation: 189.6 °C, experiment: 188.5 °C) and the final degree of cure (simulation: 0.948, experiment: 0.960 ± 0.013), confirming ECK-Net’s capability as a reliable alternative to conventional cure kinetics modeling methods.

Composite curing↗
DOE OSTI2022

Fragility Functions Resource Report: Documented Sources for Electricity and Water Resilience Valuation

Fragility curves provide the vulnerability between hazard intensity and an asset. Federal installations may include many different electricity and water infrastructure types (or assets) such as generators, wind turbines, solar PV, switch yards, substations and power lines as well as water distribution systems that could be affected by different hazards. The vulnerability of each asset is a function of its age, type of materials and maintenance. In addition, the vulnerability changes with the hazards intensity and has a probability distribution function associated with it. The fragility functions are used in conjunction with hazard probability and consequence valuations to determine the values at risk for examination of investment grade analyses of alternative mitigation strategies. This document provides examples of fragility functions and links to their sources for different electricity and water infrastructure assets by hazard type.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Formation of functionally graded steel by laser powder bed fusion via in-situ carbon doping

Additive Manufacturing (AM) enables functional integration by combining multiple components into a single part to shorten assembly time, reduce weight, and improve performance. Laser Powder Bed Fusion (LPBF) is an important AM method due to excellent spatial resolution, surface finish, and material properties without the need for extensive post-processing. Functional integration could be enhanced by spatial tuning of properties, but LPBF cannot readily vary material composition. Here, this paper addresses a method to add spatial composition control by printing small quantities of dopants via liquid carrier prior to laser fusion. The impact of carbon black suspension added to select regions of a Stainless Steel 316 L powder bed on melt pool dimension, hardness, and porosity is reported. The distribution of the carbon between the doped and plain layers and the resulting spatial variation in hardness is measured. Optical microscopy and composition analysis show that the carbon dispersed uniformly within the layer of deposition and diffused as little as 50 μm in the build direction. Keyhole conditions dramatically increase the inter-layer transport of the dopant. The added carbon increased hardness by >50 %. Porosity increased in doped regions but remained below 1.5 % for the best processing parameters. These results demonstrate that the composition of LPBF parts could be controlled in 3-dimensions using a dopant that is soluble in the melt pool. Additional work will be required to evaluate different dopant materials and optimize processing conditions for full density, but microalloying with soluble dopants appears to be a plausible solution to enhance functional integration with LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Adaptation of Temperature Dependent Thermal Neutron Libraries for Fast On-The-Fly Monte Carlo Sampling at Arbitrary Temperatures

Thermal neutron scattering data is necessary for reactor simulations of thermal reactors, but the data storage required can be unwieldy. This is exacerbated when simulations require a large temperature range, as is the case for accident scenarios and reactor start-up. Previous work conducted at RPI has explored and demonstrated a proof of concept of On-The-Fly (OTF) data storage with light water and crystalline graphite based on ENDF/B-VII.1. This provides an updated data storage paradigm for incoherent inelastic cross-sections that allow the data to be used to generate necessary sampling Cumulative Density Functions (CDFs) for any desired temperature. The work presented in this paper extends the previous work by implementing the proof of concept based on ENDF/B-VIII.0, instead of ENDF/B-VII.1, and to include additional materials, such as beryllium and oxygen in beryllium oxide and the new reactor grades of porous graphite. Completion of this work allows a single thermal data file to represent any thermal scattering event for a given material OTF for the temperature of interest, which greatly reduces the data storage needed with only a marginal cost in the calculation of the CDFs OTF. This paper will review the basic methodologies in generating the OTF data, as well as present the updates and improvements made in the generation process. Application of the methodologies covered in this paper show a significant reduction in the storage requirements for inelastic incoherent scattering events. In which, the evaluated ENDF/B-VIII.0 thermal scattering library can be reduced from 563.1 MB to 10.9 MB for light water and 339.3 MB to 13.6 MB for Be in BeO.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗
DOE OSTI2018

Microstructure characterisation and mechanical properties of a functionally-graded NbC/high chromium white cast iron composite

Highlights: • A functionally-graded NbC – white cast iron composite was centrifugally cast. • Primary NbC particle distribution follows Stokes' Law, with 30 vol% at the surface. • Presence of primary NbC particles refined eutectic M{sub 7}C{sub 3} morphology at the surface. • The surface layer was hard and wear resistant, while the interior was tougher. • NbC and M{sub 7}C{sub 3} carbides form independent eutectic structures within the interior. - Abstract: A functionally graded NbC – high chromium white cast iron composite was successfully fabricated by centrifugal casting for high wear applications. The migration of primary NbC particles to the outer periphery, as predicted by Stokes' law, resulted in an extremely hard outer layer at the surface of a softer bulk material. Microstructural characterisation showed that both the volume fraction and the morphology of the carbides varies along the thickness of the specimen. At the outer surface, the NbC was present as primary carbides while Chinese-script NbC was found in the bulk of the material. Hardness, sliding wear and three-point bending tests confirmed that the outer layer was harder and more wear resistant than the rest of the material, which was correspondingly tougher. The study of the fracture surface of the specimens showed that there is a strong bond between NbC and the matrix such that delamination between the reinforcements and the matrix did not occur during fracture. If Chinese-script NbC can be reduced or prevented in the bulk material, further improvements to toughness could be achieved.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optically Excited Lasing in a Cavity‐Based, High‐Current‐Density Quantum Dot Electroluminescent Device

Abstract Laser diodes based on solution‐processable materials can benefit numerous technologies including integrated electronics and photonics, telecommunications, and medical diagnostics. An attractive system for implementing these devices is colloidal semiconductor quantum dots (QDs). The progress towards a QD laser diode has been hampered by rapid nonradiative Auger decay of optical‐gain‐active multicarrier states, fast device degradation at high current densities required for laser action, and unfavorable competition between optical gain and optical losses in a multicomponent device stack. Here we resolve some of these challenges and demonstrate optically excited lasing from fully functional high‐current density electroluminescent (EL) devices with an integrated optical resonator. This advance has become possible due to excellent optical gain properties of continuously graded QDs and a refined device architecture, which allows for highly efficient light amplification in a thin, EL‐active QD layer.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A projection-based method for topology optimization of structures with graded surfaces

Topology optimization (TO) is a generative design approach that is used to create new structures that are optimal for their purpose. Standard parameterizations of the TOproblem allow exploration of an arbitrarily complex design space, but must be constrained to ensure manufacturability; these constraints tend to be computationally expensive and intrusive to the design process. A relatively new parametrization of the TO problem uses geometry projection of known-manufacturable building blocksinto the design domain, but the existing library of building blocks compatible with projection is small. This project sought to expand this library with new shapes, and to determine whether theaddition of these new shapes could be used to design unit cells for micro-architected materials (MAMs) with improved stiffness-to-weight ratio compared with traditional designs,while retaining compatibility with additive manufacturing processes.Due to a reduction in scope, effort was focused on truss lattices with hollow, tapered, and curved struts. Hollowtruss lattices were found that outperform traditional designs like the octet truss in both stiffness and isotropy, as well as providing a decoupling between the stiffness and relative density. These new designs are expected to improve the performance of functionally graded structures in programmatic applications.

42 ENGINEERING↗
DOE OSTI2024

Applied radiation tags for warhead dismantlement transparency

Here, this study explores the feasibility of applying radiation tags as a Chain of Custody tool to confirm the dismantlement of individual warheads by investigating time dependent emissions from special nuclear material. Precedents of photon and neutron sources that have been used to irradiate warhead components are presented. Measurements of irradiated Highly Enriched Uranium (HEU) are used to benchmark simulations with the CINDER90 library for MCNP. Delayed gamma emissions are simulated as a function of time since irradiation of moderated HEU and Weapons Grade Plutonium with photon and neutron sources. Models of commercial 9 MV and 15 MV linacs were found to induce ~10 9 fissions/g and ~10 11 fissions/g, respectively, creating 3 to 4 orders of magnitude more delayed gammas than neutron sources, modeled at 10 10 n/s. However, a DT neutron source was found to induce sufficient fissions, ~10 7 fissions/g, to create quantifiable signatures relative to intrinsic emissions. Applied radiation tagging is determined to be technically feasible, but its operational context and practical implementation requires significant development.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

Neutron reflectometry investigations of interfacial structures of Ti/TiN layers deposited by magnetron sputtering

We report that nanolayered metal-ceramic composite systems provide the possibility to produce new materials with exceptional strength, toughness, and radiation resistance not exhibited by their individual constituents. The unusual behaviors are frequently attributed to the high density of internal interfaces. Most layered structures studied to date contain sharp interfaces and the synthesis of more diffuse interfacial structures, where the interface is graded out of the interface plane, has not been deeply explored. Here we show how neutron reflectometry was used to study the structure of magnetron sputter deposited titanium and titanium nitride (Ti/TiN) layers as a function of deposition parameters: temperature, rate of N 2 flow or pressure, electrical bias applied to the sample, and orientation of the ion source relative to the sample. These different deposition and post-processing strategies resulted in profound changes in the structure of the interfacial region between the two components in Ti/TiN x bilayers. Finally, the results show that temperature and low step-wise N 2 flow rates, but not electrical bias, can form graded interfaces in a controlled manner.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Efficient simulation of the impact of interface grading on the transport and optical properties of semiconductor heterostructures

An efficient model is proposed to evaluate the impact of interface grading on the properties of semiconductor heterostructures. In the plane-wave approximation, the interface grading is taken into account by simply multiplying the Fourier components of the potential by a Gaussian function, which results only in a very small increase of the computation time. We show that the interface grading may affect the transition energies, the field strength for resonant coupling of subbands, and even the miniband formation in complex systems such as quantum-cascade lasers. This model provides a convenient tool for the incorporation of interface grading into the design of heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Grain boundary softening from stress assisted helium cavity coalescence in ultrafine-grained tungsten

The formation of helium cavities in coarse-grained materials produces hardening proportional to the number density and size of the cavities and due to the interaction of dislocations with intragranular helium defects. In nanostructured metals containing a high density of interfacial sinks, preferential cavity formation in the grain boundaries instead produces softening that is often attributed to enhanced interfacial plasticity. Here, employing two grades of ultrafine-grained tungsten, we explore this effect using targeted implantation studies to map cavity evolution as a function of the irradiation conditions and quantify its impact on the mechanical response through nanoindentation. Softening is reported at implantation temperatures above the threshold for preferential grain boundary cavity formation but at a sufficiently low fluence prior to the growth of intragranular cavities. Collective changes in the mean cavity size, density, and morphology beneath a residual impression on an implanted surface indicate that cavity coalescence accompanied the reduction in hardness. Complementary atomistic simulations demonstrate that, in tungsten grain structures exhibiting softening, grain boundary bubble coalescence is driven by stress concentrations that further act to localize strain in the grain boundaries through cooperative deformation processes involving local atomic shuffling and sliding, dislocation emission, and even the nucleation of unstable twinning events.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Tailoring broadband light trapping of GaAs and Si substrates by self-organised nanopatterning

We report on the formation of high aspect ratio anisotropic nanopatterns on crystalline GaAs (100) and Si (100) substrates exploiting defocused Ion Beam Sputtering assisted by a sacrificial self-organised Au stencil mask. The tailored optical properties of the substrates are characterised in terms of total reflectivity and haze by means of integrating sphere measurements as a function of the morphological modification at increasing ion fluence. Refractive index grading from sub-wavelength surface features induces polarisation dependent anti-reflection behaviour in the visible-near infrared (VIS-NIR) range, while light scattering at off-specular angles from larger structures leads to very high values of the haze functions in reflection. The results, obtained for an important class of technologically relevant materials, are appealing in view of photovoltaic and photonic applications aiming at photon harvesting in ultrathin crystalline solar cells.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Investigation of static and dynamic behavior of functionally graded piezoelectric actuated Poly-Si micro cantilever probe

In the present paper a novel functionally graded piezoelectric (FGP) actuated Poly-Si micro cantilever probe is proposed for atomic force microscope. The shear piezoelectric coefficient d{sub 15} has much higher value than coupling coefficients d{sub 31} and d{sub 33}, hence in the present work the micro cantilever beam actuated by d{sub 15} effect is utilized. The material properties are graded in the thickness direction of actuator by a simple power law. A three dimensional finite element analysis has been performed using COMSOL Multiphysics® (version 4.2) software. Tip deflection and free vibration analysis for the micro cantilever probe has been done. The results presented in the paper shall be useful in the design of micro cantilever probe and their subsequent utilization in atomic force microscopes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗