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At least 451 records · Page 25

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗

DOE OSTI2023

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Shear deformation of pure-Cu and Cu/Nb nano-laminates using micromechanical testing

Solid phase processing by introducing shear deformation into materials can result in unique microstructure evolution and enhanced mechanical properties, especially for immiscible systems such as Cu/Nb. To better understand the correlation between microstructure and deformation behavior during shear, a dedicated testing design of stress localization at predicted sites is necessary. In this study, a specialized S-shaped specimen geometry is implemented to apply localized simple-shear loading in pure-Cu and Cu/Nb accumulative roll-bonded nanolaminates. The nanoscale microstructure and proximity of interfaces in Cu/Nb offer a ~2.8-fold increase in shear stresses than pure-Cu. In pure-Cu, the plastic instability causes shear banding and an in-plane lattice rotation. In Cu/Nb, a partial bending of the interfaces occurred, resulting in a localized lattice rotation. The adapted geometry for micro-scale specimens thus successfully captures the shear deformation at predicted sites in two distinct material systems and could potentially be a powerful technique to study the deformation mechanisms.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Adaptive Forward Modeling Method for Analysis and Reconstructions of Orientation Image Map

IceNine is a MPI-parallel orientation reconstruction and microstructure analysis code. It's primary purpose is to reconstruct a spatially resolved orientation map given a set of diffraction images from a high energy x-ray diffraction microscopy (HEDM) experiment (1). In particular, IceNine implements the adaptive version of the forward modeling method (2, 3). Part of IceNine is a library used to for conbined analysis of the microstructure with the experimentally measured diffraction signal. The libraries is also designed for tapid prototyping of new reconstruction and analysis algorithms. IceNine is also built with a simulator of diffraction images with an input microstructure.

Frankie Li, ShiuFai↗

DOE OSTI2014

Adaptive Forward Modeling Method for Analysis and Reconstructions of Orientation Image Map

Frankie Li, Shiu Fai↗

NASA NTRS2019

In Situ Observation of Growth Dynamics in DECLIC Directional Solidification Insert Onboard ISS: DSI-R Flight Campaign

The study of solidification microstructure formation is of utmost importance for materials design and processing, as solid-liquid interface patterns largely govern mechanical and physical properties. Pattern selection occurs under dynamic conditions of growth in which the initial morphological instability evolves nonlinearly and undergoes a reorganization process. The dynamic and nonlinear nature of this instability renders in situ observation of the interface an invaluable tool to gain knowledge on the time-evolution of the interface pattern. Transparent organic analogs, which solidify like metallic alloys, allow direct visualization of interface dynamics. Extensive ground-based studies of both metallic and organic bulk samples have established the presence of significant convection during solidification processes that alters the formation of interfacial microstructures. A reduced-gravity environment is therefore mandatory for fluid flow elimination in bulk samples. In the framework of the CNES project MISOL3D (MIcrostrutures de SOLidification 3D) and the NASA projects DSIP (Dynamical Selection of 3D Interface Patterns), SPADES (SPAtiotemporal Evolution of three-dimensional DEndritic array Structures) and CAMUS (ComputAtional Studies of MicrostrUcture Formation During Alloy Solidification in Microgravity), we participated in the development of the Directional Solidification Insert (DSI) of the DEvice for the study of Critical Liquids and Crystallization (DECLIC). The DECLIC-DSI is dedicated to in situ and real-time characterization of solid-liquid interface patterns during directional solidification of transparent alloys in diffusive transport regime. Between April 2010 and March 2011, the first ISS campaign (DSI) explored the entire range of microstructures resulting in unprecedented observations. A second campaign (DSI-R), performed between October 2017 and December 2018, in which the insert contained an alloy of higher solute concentration, allowed to complete the benchmark database. The increase of solute concentration resulted in well-developed dendritic patterns at lower velocities (lower interface curvature and larger tip radius). The microstructure resulting from dendritic growth is dominant in metallurgy so that it is fundamental to understand the mechanisms of its formation. The main aims of this experimental campaign are to understand: the mechanisms of the cell to dendrite transition, the fundamental mechanisms of sidebranching formation, the dependence of dendrite tip shapes on growth conditions, the interaction of primary array and secondary sidebranches, and the influence of subgrain boundaries on the spatiotemporal organization of the array structure. Preparation, analysis and interpretation of the experiments performed onboard ISS are considerably enhanced by experiments performed on ground using thin-samples (Pr. Trivedi’s group) and phase-field simulations of microstructure formation in a diffuse growth regime (Pr. Karma’s group). In this summary, we will present an initial assessment of the results obtained during the DSI-R campaign. Nomenclature Vp: pulling velocity G: thermal gradient L: solidified length rtip: tip curvature radius Acronyms/Abbreviations CADMOS: Centre d'Aide au Développement des activités en Micro-pesanteur et des Opérations Spatiales CNES: Centre National d’Études Spatiales DECLIC: Device for the study of Critical LIquids and Crystallization DSI: Directional Solidification Insert DSI-R: Directional Solidification Insert - Refurbish ISS: International Space Station NASA: National Aeronautics and Space Administration PF: phase-field SCN: Succinonitrile 3D: three-dimensional

Mota, F.L.↗

DOE OSTI2023

Compositionally complex perovskite oxides: Discovering a new class of solid electrolytes with interface-enabled conductivity improvements

Compositionally complex ceramics (CCCs), including high-entropy ceramics, offer a vast, unexplored compositional space for materials discovery. Herein, we propose and demonstrate strategies for tailoring CCCs via a combination of non-equimolar compositional designs and control of grain boundaries (GBs) and microstructures. Using oxide solid electrolytes for all-solid-state batteries as an example, we have discovered a class of compositionally complex perovskite oxides (CCPOs) with improved lithium ionic conductivities beyond the limit of conventional doping. For example, we demonstrate that the ionic conductivity can be improved by >60% in (Li 0.375 Sr 0.4375 )(Ta 0.375 Nb 0.375 Zr 0.125 Hf 0.125 )O 3-δ compared with the (Li 0.375 Sr 0.4375 )(Ta 0.75 Zr 0.25 )O 3-δ (LSTZ) baseline. Furthermore, the ionic conductivity can be improved by another >70% via quenching, achieving >270% of the LSTZ. Notably, we demonstrate GB-enabled conductivity improvements via both promoting grain growth and altering GB structures through compositional designs and processing. In a broader perspective, this work suggests new routes for discovering and tailoring CCCs for energy storage and many other applications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Development of Lightweight Structural Materials with Improved Properties for Fission Batteries

Fission batteries require lightweight structural materials that demonstrate structural resilience when subjected to repeated shutdown, transportation, startup cycles, and certain external conditions, including rare events such as seismic vibrations and tsunamis. The objectives of this project are (1) to produce lightweight structural materials whose strength-to-weight ratios and fatigue resistance exceed those of current widely used structural materials such as 316 stainless steels (SS316), and (2) to enhance radiation tolerance of structural materials over a suitable service temperature range. To achieve these, (1) a lattice structure will be produced, (2) advanced modeling and simulation tools will be employed to design lattice structures (e.g., a gyroid structure) that reduce stress concentrations and thus increase fatigue resistance, and (3) one-dimensional (1-D) carbon nanotubes will be added to enhance radiation resistance. To validate our solution, high-temperature tensile and fatigue testing, in combination with microstructure characterization, will be conducted on wrought materials, additively manufactured solid materials, and the designed lightweight lattice structure material. Ion irradiation, microstructure characterization, and nanoindentation will be carried out to investigate the effect of 1-D carbon nanotubes on radiation tolerance. Successful completion of this project will deliver a material to serve as a substitute for current SS316 using the same chemistry but with lighter weight and improved mechanical properties. In addition, a material with carbon nanotubes can be designed for improved radiation tolerance over a suitable service temperature range. This project will establish new techniques in innovative materials/lattice design, advanced macroscale properties prediction, and the application of state-of-the-art processes.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Formulation and validation of a reduced order model of 2D materials exhibiting a two-phase microstructure as applied to graphene oxide [Formulation and validation of a reduced order model of 2D materials exhibiting a two-phase microstructure]

Novel 2D materials, e.g., graphene oxide (GO), are attractive building blocks in the design of advanced materials due to their reactive chemistry, which can enhance interfacial interactions while providing good in-plane mechanical properties. Recent studies have hypothesized that the randomly distributed two-phase microstructure of GO, which arises due to its oxidized chemistry, leads to differences in nano- vs meso–scale mechanical responses. However, this effect has not been carefully studied using molecular dynamics due to computational limitations. Herein, a continuum mechanics model, formulated based on density functional based tight binding (DFTB) constitutive results for GO nano-flakes, is establish for capturing the effect of oxidation patterns on the material mechanical properties. GO is idealized as a continuum heterogeneous two-phase material, where the mechanical response of each phase, graphitic and oxidized, is informed from DFTB simulations. A finite element implementation of the model is validated via MD simulations and then used to investigate the existence of GO representative volume elements (RVE). We find that for the studied GO, an RVE behavior arises for monolayer sizes in excess to 40 nm. Moreover, we reveal that the response of monolayers with two main different functional chemistries, epoxide-rich and hydroxyl–rich, present distinct differences in mechanical behavior. In addition, we explored the role of defect density in GO, and validate the applicability of the model to larger length scales by predicting membrane deflection behavior, in close agreement with previous experimental and theoretical observations. As such the work presents a reduced order modeling framework applicable in the study of mechanical properties and deformation mechanisms in 2D multiphase materials.

36 MATERIALS SCIENCE↗

NASA NTRS2019

Heatshield Entry Modeling Using a Design, Analysis, and Optimization Toolbox

The Mars Science Laboratory (MSL) was protected during its Mars atmospheric entry by an instrumented heatshield that used NASA's Phenolic Impregnated Carbon Ablator (PICA). PICA is a lightweight carbon fiber/polymeric resin material that offers excellent performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of atmospheric entry and material response. MEDLI recorded, among others, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase the capability of the Design, Analysis, and Optimization of Thermal Protection Materials (DAOTPM) software. DAO-TPM is a Python based framework that works as a link between mission design, aerothermal and radiative environment computation, Thermal Protection Systems (TPS) microstructure analysis, material response and optimization tools. The toolbox has a Graphical User Interface (GUI) that allows the user to build as well as run the various software and utilities used to design, analyze and optimize a heatshield during atmospheric entry.

Meurisse, Jeremie B. E.↗

NASA NTRSDate not supplied

3D Construction of Biologically Derived Materials

System for the 3D Construction of Biologically Derived Materials, Structures, and Parts NASA has developed a novel approach for macroscale biomaterial production by combining synthetic biology with 3D printing. Cells are biologically engineered to deposit desired materials, such as proteins or metals, derived from locally available resources. The bioengineered cells build different materials in a specified 3D pattern to produce novel microstructures with precise molecular composition, thickness, print pattern, and shape. Scaffolds and reagents can be used for further control over material product. This innovation provides modern design and fabrication techniques for custom-designed organic or organic-inorganic composite biomaterials produced from limited resources. Benefits Conserves resources. Few raw or bulk starting materials needed Enables custom design of diverse materials Fast, portable, macroscale, on-demand manufacturing High-fidelity microstructures Uses commercially available parts Applications Biomaterials, biotechnology Organic-inorganic composite materials On-demand manufacturing In situ resource utilization Space stations Military Infrastructure materials The Technology Once genes for a desired material type, delivery mode, control method and affinity have been chosen, assembling the genetic components and creating the cell lines can be done with well-established synthetic biology techniques. A 3D microdeposition system is used to make a 3D array of these cells in a precise, microstructure pattern and shape. The engineered cells are suspended in a printable 'ink'. The 3D microdeposition system deposits minute droplets of the cells onto a substrates surface in a designed print pattern. Additional printer passes thicken the material. The cell array is fed nutrients and reagents to activate the engineered genes within the cells to create and deposit the desired molecules. These molecules form the designed new material. If desired, the cells may be removed by flushing. The end product is thus a 3D composite microstructure comprising the novel material. This innovation provides a fast, controlled production of natural, synthetic, and novel biomaterials with minimum resource overhead and reduced pre- and post-processing requirements.

3D↗

DOE OSTI2024

Design and Characterization of Hierarchically-Strengthened, Cast Al-Ce-Ni-Mn-Sc-Zr Alloys for High-Temperature Applications

We characterize the microstructure and mechanical properties of cast Al-Ce-Ni-Mn-Sc-Zr alloys designed for structural use above 300 °C. We first report on the effect of Ni on the as-cast phase formation, where all alloys consist of fine Al11Ce3 and Ni-rich eutectic phases, but the identity of the Ni-rich phase varies with Ni content. Furthermore, these alloys contain four coarsening-resistant strengthening phases as determined from SEM and APT investigations: (i) Al11Ce3 and (ii) Ni-rich micron-scale platelets formed during eutectic solidification, (iii) L12-Al3(Sc,Zr) nanoprecipitates formed during secondary aging, and (iv) Mn solute in the α-Al matrix. The Al-Ce-Ni-Mn-Sc-Zr alloy possesses higher microhardness and creep resistance than compositionally simpler alloys containing fewer of the strengthening phases, indicating that these strengthening mechanisms synergize to provide increased ambient- and elevated-temperature strength.

Ekaputra, Clement↗

DOE OSTI2026

A modified scheil approach for nucleation-dependent solidification pathways

As-solidified microstructures of near-eutectic alloys often contain multiple primary phases that are not expected from equilibrium phase diagrams. Such microstructures are caused by cooling-rate-dependent solidification pathways, a factor not captured by the Scheil–Gulliver model or variations thereof. Here, we present a model and algorithm that incorporate the critical nucleation undercooling for each solid phase into the Scheil–Gulliver model. We hypothesize that the non-equilibrium microstructure formation is primarily governed by a nucleation-competition mechanism. This mechanism accounts for both stable/metastable phase selection and primary-phase formation within eutectic regions driven by asymmetric nucleation barriers. The model is validated against a hypereutectic Al-Fe alloy, where it successfully reproduces the observed microstructural constituents, revealing the key dependencies of solidification microstructure on nucleation kinetics. Applicability to multicomponent systems is demonstrated through a hypereutectic Al–Fe–Si ternary alloy, where the model successfully predicts divorced eutectic microstructures and the associated oscillatory solidification pathways along univariant lines. As a result, the proposed framework establishes a nucleation-dependent computational approach for interpreting and predicting solidification microstructures.

Alloy design↗

DOE OSTI2019

Elevated temperature microstructure evolution of a medium-entropy CrCoNi superalloy containing Al,Ti

A new medium-entropy superalloy was produced based on the compositions of equiatomic CrCoNi and Ni-base superalloy Inconel 740H. Initial alloy design was performed using Thermo-Calc. The aging response and microstructural stability were assessed following heat treatment at temperatures between 600 and 900 °C and durations up to 100 h. Aging from a fully recrystallized state resulted in negligible grain growth and produced γ’ and σ phases. The same phases were present after aging from a cold-rolled state, but partially recrystallized microstructures resulted in multi-modal size distributions and heterogeneous spatial arrangements. Finally, room temperature hardness measurements were used to correlate aging conditions with quantitative precipitate measurements and mechanical properties.

36 MATERIALS SCIENCE↗

DOE OSTI2012

A Benchmark Study on Casting Residual Stress

Stringent regulatory requirements, such as Tier IV norms, have pushed the cast iron for automotive applications to its limit. The castings need to be designed with closer tolerances by incorporating hitherto unknowns, such as residual stresses arising due to thermal gradients, phase and microstructural changes during solidification phenomenon. Residual stresses were earlier neglected in the casting designs by incorporating large factors of safety. Experimental measurement of residual stress in a casting through neutron or X-ray diffraction, sectioning or hole drilling, magnetic, electric or photoelastic measurements is very difficult and time consuming exercise. A detailed multi-physics model, incorporating thermo-mechanical and phase transformation phenomenon, provides an attractive alternative to assess the residual stresses generated during casting. However, before relying on the simulation methodology, it is important to rigorously validate the prediction capability by comparing it to experimental measurements. In the present work, a benchmark study was undertaken for casting residual stress measurements through neutron diffraction, which was subsequently used to validate the accuracy of simulation prediction. The stress lattice specimen geometry was designed such that subsequent castings would generate adequate residual stresses during solidification and cooling, without any cracks. The residual stresses in the cast specimen were measured using neutron diffraction. Considering the difficulty in accessing the neutron diffraction facility, these measurements can be considered as benchmark for casting simulation validations. Simulations were performed using the identical specimen geometry and casting conditions for predictions of residual stresses. The simulation predictions were found to agree well with the experimentally measured residual stresses. The experimentally validated model can be subsequently used to predict residual stresses in different cast components. This enables incorporation of the residual stresses at the design phase along with external loads for accurate predictions of fatigue and fracture performance of the cast components.

36 MATERIALS SCIENCE↗

DOE OSTI2012

Cu/Nb nano-composite wires processed by severe plastic deformation for applications in high pulsed magnets: effects of the multi-scale microstructure on the mechanical properties

Copper-based high strength and high electrical conductivity nano-composite wires reinforced by Nb nano-tubes are prepared by severe plastic deformation, applied with an Accumulative Drawing and Bundling process (ADB), for the windings of high pulsed magnets. The ADB process leads to a multi-scale Cu matrix containing up to N = 85{sub 4} (52.2.10{sup 6}) continuous parallel Nb tubes with diameter down to few tens nano-meters. After heavy strain, the Nb nano-tubes exhibit a homogeneous microstructure with grain size below 100 nm. The Cu matrix presents a multi-scale microstructure with multi-modal grain size distribution from the micrometer to the nano-meter range. The use of complementary characterization techniques at the microscopic and macroscopic level (in-situ tensile tests in the TEM, nano-indentation, in-situ tensile tests under high energy synchrotron beam) shed light on the interest of the multi-scale nature of the microstructure to achieve extreme mechanical properties, therefore allowing for design guidelines to further improve these properties. (authors)

36 MATERIALS SCIENCE↗

DOE OSTI2023

Efficient Reversible Operation and Stability of Novel Solid Oxide Cells

This project aims to develop and test novel Reversible Solid Oxide Cells (ReSOCs) specifically designed to yield low area specific resistance, as required to achieve high round trip efficiency in reversible operation at high current density. A key objective is to improve long-term reversible SOC durability; mechanistic degradation models will be used to predict long-term durability using input data from accelerated testing that combines electrochemical life testing with quantitative microstructural and chemical evaluation. The modeling tasks seek to design low-loss, low-cost ReSOC systems using input data from the experimental cell studies. A key challenge is to develop a thermal management strategy that maintains thermally self-sustaining operation while operating the stack at a potential lower than the thermo-neutral steam electrolysis voltage of ~1.3 V, to maintain high efficiency.

08 HYDROGEN↗

DOE OSTI2021

Domain knowledge-informed, process-mapping AI graph for designing Fe-based alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Continuous improvement in efficiency of a power plant relies on designing materials for use at increasingly higher temperature and/or pressure, for 100,000s hours of operation. Due to complexity, non-linearity and high-dimensionality of the problem, traditional Machine Learning (ML) approaches require unreasonably large datasets for the data-driven model development. Science-based material and process engineering complements hard data with, sometimes soft and intuitive, empirical domain knowledge. Artificial Intelligence (AI) was used in this study to incorporate such knowledge into computational graph architecture (process-mimicking artificial neuron design, causal layer and graph structures, ensemble modeling of latent states) and learning procedures (variable transformation, fuzzy physics pre-training and freezing of deep layers, virtual microstructure representation, and adversarial multi-objective optimization). The first alloys design pathways suggested by the AI tool (pyroMind) passed a preliminary engineering review on soundness and transparency.</span>

Romanov, Vyacheslav↗