Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “microstructure engineering”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives

Microstructural characterization of composite high explosives (HEs) has become increasingly important over the last several decades in association with the development of high fidelity mesoscale modeling and an improved understanding of ignition and detonation processes. HE microstructure influences not only typical material properties (e.g., thermal, mechanical) but also reactive behavior (e.g., shock sensitivity, detonation wave shape). A detailed nondestructive 3D examination of the microstructure has generally been limited to custom-engineered samples or surrogates due to poor contrast between the composite constituents. Highly loaded (>90 wt%) HE composites such as plastic-bonded explosives (PBX) are especially difficult. Here, we present efforts to improve measurement quality by using single and dual-energy microcomputed X-ray tomography and state-of-the-art image processing techniques to study a broad set of HE materials. Some materials, such as PBX 9502, exhibit suitable contrast and resolution for an automatic segmentation of the HE from the polymer binder and the voids. Other composite HEs had varying levels of success in segmentation. Post-processing techniques that used commercially available algorithms to improve the segmentation quality of PBX 9501 as well as zero-density defects such as cracks and voids could be easily segmented for all samples. Aspects of the materials that lend themselves well to this type of measurement are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Engineering donor–acceptor conjugated polymers for high-performance and fast-response organic electrochemical transistors

To date, high-performance organic electrochemical transistors (OECTs) have mostly been based on polythiophene systems. Donor–acceptor (D–A) conjugated polymers are expected to be promising materials for OECTs owing to their high mobility and comparatively low crystallinity (good for ion diffusion). However, the OECT performance of D–A polymers lags far behind that of the polythiophenes. Here we synergistically engineered the backbone and side chain of a series of diketopyrrolopyrrole (DPP)-based D–A polymers and found that redox potential, molecular weight, solution processability, and film microstructures all have a severe impact on their performance. After systematic engineering, P(bgDPP-MeOT2) exhibited the best figure-of-merit (μC*) of 225 F cm -1 V -1 s -1 , amongst the highest performance of the reported D–A polymers. Besides, the DPP polymers exhibited high hole mobility of over 1.6 cm 2 V -1 s -1 , leading to fast response OECTs with a record low turn-off response time of 30 μs. The polymer also exhibited good operation stability with a current retention of 98.8% over 700 electrochemical switching cycles. This work reveals the complexity and systematicness in the development of D–A polymer based high-performance OECTs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data

Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.

42 ENGINEERING↗
DOE OSTI2025

Correlating energy density induced residual stress, porosity, and mechanical property variations in directed energy deposition using neutron diffraction and imaging techniques

In a directed energy deposition (DED) process, the energy density deposited into the materials drives the structure and properties. The energy density is influenced by several printing parameters, such as laser power, hatch spacing, scanning speed, etc. In this study, 316L stainless steels samples were fabricated with varying hatch spacing aiming to induce variations in sample microstructure and properties. A combination of techniques including engineering neutron diffraction, neutron computed tomography, and tensile testing, were employed to correlate the structure and macroscopic properties. Porosity was predominantly observed at the bottom of the deposited materials and was effectively reduced by decreased hatch spacing. Correlatively, compressive residual stress was observed at the bottom of the specimens, while internal stress is largely determined by the hatch spacing. The residual stress in general decreases as the hatch spacing decreases. The maximum ultimate tensile strength (UTS) was found to increase from 517.4 to 528.6 MPa with a strain increased from 0.847 to 0.897 as the hatch spacing decreased from 0.45 to 0.42 mm. However, further increase in energy density by reducing the hatch spacing resulted in a significant decrease in UTS (as low as 452 MPa). This work provides new insights from bulk non-destructive techniques into correlating energy density induced residual stress, porosity, and mechanical property variations in directed energy deposition.

316L stainless steel↗
DOE OSTI2025

Probing Surface Plasmon Dynamics in Periodic Nanostructures through Ultrafast Electron Microscopy

Surface plasmon polaritons (SPPs) can be manipulated to localize and guide light in subwavelength distances, enabling them to find applications in a wide range of areas, from sensing to quantum computing. Among several methods of SPP excitation, periodic arrays of nano- and microstructures are of particular interest, as they enable engineering SPP properties through structural parameters. Here, in this study, using the photon-induced near-field electron microscopy (PINEM) technique, we investigated the mode formation, coupling, interference, and decay of SPPs in square and hexagonal arrays of circular nanoholes under both visible and near-infrared excitation. Polarization-resolved analysis revealed the key factors governing SPP localization and interference patterns, showing that the periodicity and symmetry of the array primarily determine the SPP interference patterns and their orientation, while pump polarization mainly modulates their intensity. Time-resolved PINEM measurements demonstrated the spatial dependence of the SPP temporal characteristics. In addition, cathodoluminescence (CL) spectroscopy was employed to examine the intrinsic plasmonic characteristics of the structure. Finite difference time domain (FDTD) simulations showed strong agreement with both PINEM and CL measurements on the spatial and spectral behavior of SPPs. Understanding the spatiotemporal dynamics of SPPs on nanostructures beyond the diffraction limit is crucial for optimizing plasmonic structures for advanced photonic and quantum technologies.

Plasmonics↗
DOE OSTI2023

Advanced characterization-informed machine learning framework and quantitative insight to irradiated annular U-10Zr metallic fuels

Abstract U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Since the Experimental Breeder Reactor-II in the late 1960s, researchers accumulated a considerable amount of experience and knowledge on fuel performance at the engineering scale. However, a mechanistic understanding of fuel microstructure evolution and property degradation during in-reactor irradiation is still missing due to a lack of appropriate tools for rapid fuel microstructure assessment and property prediction based on post irradiation examination. This paper proposed a machine learning enabled workflow, coupled with domain knowledge and large dataset collected from advanced post-irradiation examination microscopies, to provide rapid and quantified assessments of the microstructure in two reactor irradiated prototypical annular metal fuels. Specifically, this paper revealed the distribution of Zr-bearing secondary phases and constitutional redistribution across different radial locations. Additionally, the ratios of seven different microstructures at various locations along the temperature gradient were quantified. Moreover, the distributions of fission gas pores on two types of U-10Zr annular fuels were quantitatively compared.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Latent Pitfalls in Microstructure-Based Modeling for Thermally Aged 9Cr-1Mo-V Steel (Grade 91)

A case study was conducted on a mechanistic model development that predicted tensile strength deterioration with thermal aging of 9Cr-1Mo-V steel in supporting the 60-year design life expected for advanced nuclear reactors. For property prediction beyond practical testing times, mechanistic modeling is highly desired, as it taps into the physics of structure–property relationships and therefore can generate reliable results for extrapolation. Meanwhile, as mechanistic models are often complicated, reflecting the intricacy of microstructure and strengthening mechanisms, pitfalls that are difficult to detect often exist. Here, this paper discusses latent pitfalls that are common in mechanistic modeling or specific in this 9Cr-1Mo-V case development through using the American Society of Mechanical Engineers verification and validation in computational solid mechanics (ASME V&V 10) standard for evaluating credibility of modeling in materials engineering. Suggestions are also made for enhancing reliability of microstructure-based modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering-scale Modeling of High-Temperature Creep and Creep Crack Growth in Alloy 316H

This document demonstrates completion of the goals described in the technical narrative of the Department of Energy’s Industry Funding Opportunity Announcement (iFOA) project entitled “Modeling and Simulation Development Pathways to Accelerating KP-FHR Licensing,” which relates to the development and demonstration of capabilities for conducting engineering-scale simulations of Alloy 316H components under high-temperature conditions. This work encompassed two major aspects: integrating and testing constitutive models for the creep response of 316H at high temperatures, and developing tools for modeling creep crack growth (CCG) in 316H. Two classes of constitutive models were used in this effort: phenomenological models based on behavior observed at the engineering scale, and reduced-order models (ROMs) that represent the nonlinear response of mesoscale models that capture the sensitivity to material microstructure and processing. Likewise, the approaches employed for CCG modeling considered both simplified engineering approaches and detailed simulations of creep and damage ahead of the crack tip. These developments, which were performed by utilizing the Grizzly code as well as the open-source libraries it depends on, strengthen Grizzly’s ability to support licensing and safety analyses of high-temperature reactor components.

316H↗
DOE OSTI2023

Outlook on texture evolution in additively manufactured stainless steels: Prospects for hydrogen embrittlement resistance, overview of mechanical, and solidification behavior

Abstract Realizing application specific manufacture with fusion-based additive manufacturing (F-BAM) processes requires understanding of the physical phenomena that drive evolution of microstructural attributes, such as texture. Current approaches for understanding texture evolution in F-BAM are majorly considerate of the phenomena occurring only during solidification. This hinders the comprehensive understanding and control of texture during F-BAM. In this perspective article, we discuss several physical phenomena occurring during and after solidification that can determine texture in F-BAM processed stainless steels (SS). A crystal plasticity-coupled hydrogen adsorption-diffusion modeling framework is also leveraged to demonstrate the prospects of grain boundary engineering with F-BAM for enhanced hydrogen embrittlement resistance of SS. Implications of varying thermokinetics in F-BAM for solidification behavior of SS are discussed. Additionally, microstructural attributes that are key to high temperature mechanical performance of SS are highlighted. Considerations as outlined in this perspective article will enable grain boundary engineering and application specific microstructural design of SS with F-BAM. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2026

Microstructural Topology as a Prescriptor for Quantum Coherence: Towards A Unified Framework for Decoherence in Superconducting Qubits

In superconducting quantum circuits, decoherence improvements are frequently obtained through process interventions that simultaneously modify surface chemistry, microstructural topology, and device geometry, leaving mechanistic attribution structurally underdetermined. Predictive materials engineering requires measurable structural statistics to be separated from geometry-dependent coupling coefficients into independently testable factors. We introduce the concept of classical and quantum microstructure. In that context, we formulate a channel-wise separable framework for decoherence in superconducting transmon qubits in which each loss channel is described by a reduced prescriptor. Here, a channel-specific microstructural state variable is determined independently of device geometry, and a geometry-dependent coupling functional is computable from field solutions without reference to surface chemistry. We derive this product form from a spatially resolved kernel representation and establish a perturbative separability criterion that defines the regime where independent variation of the variables is valid. The framework specifies five prescriptor classes for dominant loss pathways in transmon-class devices. Falsifiability is operationalized through a pre-committed 2x2 experimental protocol in which the variables must satisfy independent ratio checks within propagated uncertainty. A Minimum-Dataset Specification standardizes reporting for cross-laboratory inference. Part I establishes the conceptual and mathematical architecture; coordinated experimental validation is reserved for Part II.

Dravid, Vinayak P. [Northwestern U.]↗
DOE OSTI2022

Schmid factor crack propagation and tracking crystallographic texture markers of microstructural condition in direct energy deposition additive manufacturing of Ti-6Al-4V

Metallic additive manufacturing (AM) provides a customizable and tailorable manufacturing process for new engineering designs and technologies. The greatest challenge currently facing metallic AM is maintaining control of microstructural evolution during solidification and any solid state phase transformations during the build process. Ti-6Al-4V has been extensively surveyed in this regard, with the potential solid state and solidification microstructures explored at length. In this study, we evaluate the applicability of previously determined crystallo- graphic markers of microstructural condition observed in electron beam melting powder bed fusion (PBF-EB) builds of Ti-6Al-4V in a directed energy deposition (DED) build process. The aim of this effort is to elucidate whether or not these specific crystallographic textures are useful tools for indicating microstructural conditions in AM variants beyond PBF-EB. Parent β-Ti grain size was determined to be directly related to α-Ti textures in the DED build process, and the solid state microstructural condition could be inferred from the intensity of specific α-Ti orientations. Qualitative trends on the as-solidified β-Ti grain size were also determined to be related to the presence of a fiber texture, and proposed as a marker for as-solidified grain size in any cubic metal melted by AM. Analysis of the DED Ti-6Al-4V build also demonstrated a near complete fracture of the build volume, suspected to originate from accumulated thermal stresses in the solid state. Crack propagation was found to only appreciably occur in regions of slow cooling with large α +β colonies. Schmid factors for the basal and prismatic α-Ti systems explained the observed crack pathway, including slower bifurcation in colonies with lower Schmid factors of both slip systems. Colony morphologies and localized equiaxed β-Ti solidification were also found to originate from build pauses during production and uneven heating of the build edges during deposition. Tailoring of DED Ti-6Al-4V microstructures with the insight gained here is proposed, along with cautionary insight on preventing unplanned build pauses to maintain an informed and controlled thermal environment for microstructural control.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Microstructure‐Informed Analysis Framework for Lattice Structures: Guiding Topology‐Material Synergy in Titanium Alloys

In this work we discuss a microstructure‐informed analysis framework for lattice structures that maps the material's microstructural response to guide topology selection and mechanical performance optimization. By coupling geometrical topology with intrinsic material behavior, we demonstrate how anisotropic microstructural response can inform the design of optimized lattice structures. To illustrate this concept, we focus on two distinct classes of titanium alloys: Ti5553 (Ti‐5Al‐5Mo‐5V‐3Cr wt%), which exhibits a predominantly ‐phase microstructure, and Ti64 (Ti‐6Al‐4V wt%), which features a dual‐phase structure. These alloys exhibit markedly different mechanical responses under multiaxial loading in “fully dense” solid form. The strut‐level stress analysis of these alloys reveals how specific microstructural characteristics can guide the selection of appropriate lattice topologies. Two representative lattice configurations, one stretching‐dominated and one bending‐dominated, are evaluated under identical loading conditions to explore how microstructure‐driven design can lead to topology choices that are better suited to accommodate shear or other critical local stress states, thereby enhancing mechanical performance. A strut‐level mechanics‐based analysis is performed to evaluate shear stress distribution and highlight the role of topology‐microstructure synergy and compatibility in determining overall lattice behavior. The findings emphasize the importance of designing structures that are both load‐aware and microstructure‐responsive, enabling more effective material utilization in advanced engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microstructure manipulation via machining and heat treatments in hybrid manufacturing of 316L stainless steel

Hybrid manufacturing combines additive and subtractive (machining) processes in a single platform to reduce the total time to fabricate a component in its final form. Here we show that if sufficient plastic deformation can be imparted to the material during machining, recrystallization can be triggered during post-fabrication heat treatment. This can enable highly localized microstructure control. Additionally, we show that stainless steel 316L, when machined without coolant accumulates significant plastic strain compared to when machined with coolant that results in faster recrystallization kinetics during heat treatment. These effects are limited to the surface while the bulk microstructure remains unaffected.

316L stainless steel↗
DOE OSTI2025

Coupled phase field damage and crystal plasticity analysis of intragranular fracture: The role of crystallographic orientation and voids

Damage evolution in engineering metal alloys at the grain scale exhibits significant microstructural heterogeneity and anisotropy. These heterogeneities create local hotspots for stress and strain localization, leading to void nucleation. Crystal orientation influences the active slip systems around voids, affecting lattice rotation and potentially forming discontinuities. At low triaxiality, voids may change shape due to lower stress, rotation, elongation, and coalescence. At high triaxiality, the correlation between crystal orientation and void growth rate becomes stronger, resembling the behavior observed in isolated single crystals. Therefore, understanding the effects of crystal orientation, heterogeneous strain, and defect evolution is crucial for single crystal fracture characterization. Here, in this work, a coupled phase-field damage (PFD) and crystal plasticity (CP) model is implemented within a finite element framework to analyze crystal deformation and failure. The CP method employs a dislocation density-based constitutive model, while intragranular failure is modeled using an anisotropic PFD method. The PFD model considers both the stored energy due to elastic stretching and the energy release due to defect formation and crack formation. A single crystal Al2219 with an intracrystalline spherical void is chosen to analyze fracture. The study finds that fracture propagation is strongly correlated with crystal orientations. This coupled CP-PFD model provides accurate failure prediction in crystalline materials by incorporating the effects of crystal orientations and existing voids. This study demonstrates how the local microstructure and defects influence plastic deformation and failure mechanisms in metal alloys.

Aluminum alloy↗
DOE OSTI2022

Engineering grain boundary anisotropy to elucidate grain growth behavior in alumina

Current grain growth models have evolved to account for the relationship between grain boundary energy/mobility anisotropy and the five degrees of grain boundary character. However, the role of grain boundary networks on overall growth kinetics remains poorly understood. To experimentally investigate this problem, a highly textured Al 2 O 3 was fabricated by colloidal casting in a strong magnetic field to engineer a unique spatial distribution of grain boundary character. Microstructural evolution was quantified and compared to an untextured sample. From this comparison, a prevalence of (0001)/(0001) terminated grain boundaries with anisotropic networks were identified in the textured sample. These boundaries and their networks were found to be driving grain growth at a faster rate than predicted by models. These findings will allow better modelling of grain growth in real systems by experimentally exploring the impact thereon of grain boundary plane anisotropy and relative energy/mobility differences between neighboring boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In Situ Wood Delignification toward Sustainable Applications

As one of the most abundant and versatile natural materials on Earth, recently wood has attracted tremendous attention from scientists and engineers due to its outstanding advantages, including hierarchically porous microstructure, high mechanical strength, environmental friendliness, renewability, and biodegradability. Wood’s hierarchically porous structure and chemical components (e.g., cellulose, hemicelluloses, and lignin) enable its mechanical, ionic, optical, and thermal properties to be tuned via physical, chemical, and/or thermal modifications. Among these various approaches, the chemical delignification of bulk wood is the most fascinating, in which the majority of lignin and hemicelluloses is removed while leaving the cellulose intact, maintaining wood’s physical integrity and hierarchical structure. This delignified structure is unique, composed of hollow, aligned channels made up of cellulose microfibrils, and particularly attractive given its origin from a sustainable and renewable resource. As a result, delignified wood has attracted increasing attention for applications that go far beyond traditional wood utilization, such as lightweight yet strong structural materials, energy storage and conversion, environmental remediation, flexible electronics, and bioengineering. Here, we review recent developments in bulk wood delignification strategies toward the achievement of such advanced wood technologies for sustainable applications, with a focus on the research in our group. Similar to chemical pulping and bleaching, wood delignification involves a series of nucleophilic reactions based on alkaline Na 2 SO 3 or Na 2 S systems (i.e., chemical pulping) or electrophilic, radical, and oxidation reactions based on H 2 O 2 , ClO 2 , or NaClO systems (i.e., chemical bleaching) to deconstruct, fragment, and promote the hydrophilicity of lignin macromolecules, which finally make lignin easier to be removed. We discuss the structure and properties of partially and near-completely delignified wood, with a focus on process-structure–property relationships. The resulting delignified wood materials, with tunable structure and properties, demonstrate various advanced functions, in a wide range of advanced applications, such as building and construction, green energy, and electronics. Finally, the potential challenges and appealing perspectives of in situ wood delignification are discussed. In situ wood delignification, as a powerful modification strategy, has speeded up the development of advanced wood technologies and wood-based functional materials and products.

36 MATERIALS SCIENCE↗