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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Alloying effects on deformation induced microstructure evolution in copper

In this work, we investigated the effects of alloying elements on plastic deformation and microstructure evolution in polycrystalline copper (Cu) and Cu alloyed with 1 wt. % lead (Cu-1 %Pb). These materials were selected due to the size mismatch between Cu and Pb, with the latter forming precipitates at grain boundaries. Multi-modal characterization techniques, including neutron diffraction, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), along with finite element simulations were employed to study the deformation behavior across multiple length scales. While both Cu and Cu-1%Pb exhibited similar macroscale response and final deformation textures, both dislocation line profile analysis and TEM revealed increased dislocation density in deformed Cu-1%Pb specimens. The presence of lead precipitates also significantly affected local plastic deformation during compression, with their influence diminishing with increasing strain. These results demonstrate the complex relationships between alloying elements, plastic deformation, microstructural evolution, and material behavior under load. The insights gained from this multi-scale and multi-technique approach contribute to the fundamental understanding of microstructural evolution in immiscible alloys and are valuable for tailoring the properties of structural materials for specific engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microstructural characterization and equibiaxial flexural strength of CeO 2 and Ti-doped CeO 2

In this study, the synthesis of CeO 2 and titanium dioxide (TiO 2 ) doped CeO 2 (TDC) monoliths are investigated, and their fracture strength is assessed using an equibiaxial flexure testing technique at room temperature. Pellets were synthesized using conventional powder processing and sintering methods to produce the desired characteristics. The TiO 2 dopant concentration was optimized at 0.1 wt % TiO 2 to obtain dense, solid-solution pellets with an enhanced grain microstructure. A ball-on-ring fixture was used to obtain the TRS and Weibull parameters of over 30 pellets for CeO 2 and 0.1 wt % TDC to compare fracture behavior. The TRS of CeO 2 pellets ranged from 88 to 160 MPa and the TRS of 0.1 wt % TDC pellets ranged from 102 to 171 MPa, both being consistent with published values. Weibull parameters, such as characteristic strength and Weibull modulus, were extracted as 129 MPa and 8.5 for CeO 2 and 150 MPa and 9.3 for 0.1 wt % TDC, respectively. Although Hertzian contact damage was observed on compressive surfaces, failure initiation occurred on the tensile surfaces of both types of samples. Fracture surface analysis for CeO 2 indicated a predominantly intergranular fracture while 0.1 wt % TDC had a predominantly transgranular fracture mode. Finally, the TRS of 0.1 wt % TDC resulted in increased Weibull parameters when compared to CeO 2 , indicating sample chemistry and microstructure impact mechanical behavior for these samples.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Microstructure and mechanical properties of friction stir weld performed on neutron-irradiated 304L steel with helium

As nuclear power plants (NPPs) approach or exceed 40–60 years of service, it may become necessary to repair damaged neutron-irradiated components to prolong longevity. However, fusion welding repair of irradiated steels and metallic materials is challenging because of helium-induced cracking. This study used friction stir welding (FSW) to address helium-related issues, such as helium bubble formation and grain boundary cracking. The microstructure, helium-induced degradation, and mechanical properties of a friction stir weld produced on neutron-irradiated 304L stainless steel with approximately 5.2 appm of helium were characterized. The analysis focused on variations in grain size, texture, and the morphology of helium-induced damage in the friction stir weld. Mechanical properties were characterized on the irradiated base metal (BM) and metallurgical zones of the friction stir weld: the stir zone (SZ), the thermo-mechanically affected zone (TMAZ), and the heat affected zone (HAZ). Only minor scattered porosity in the SZ and TMAZ and a few short microcracks (below 20 μm in length) in the TMAZ were observed, indicating limited helium-induced degradation. Tensile tests revealed good mechanical properties and fractography analysis demonstrated predominantly ductile fracture. In conclusion, the results highlight the immediate and substantial benefits of the FSW approach for repairing or joining helium-containing irradiated materials in NPPs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
DOE OSTI2020

"Sintering" Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components

Selective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.

3D printing, Additive Manufacturing, polymer, sint↗
DOE OSTI2024

Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks

Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.

Sun, Yixuan (ORCID:0000000311093380)↗
DOE OSTI2024

Quantitative analysis of three-dimensional fatigue crack path selection in Mg alloy WE43 using high-energy X-ray diffraction microscopy

Fatigue short-cracks in Mg alloys display complex growth behavior due to high plastic anisotropy and crack path dependence on local microstructural features. In this study, the three-dimensional crystallography of short-crack paths in Mg alloy WE43 was characterized by mapping near-field high-energy X-ray diffraction microscopy (HEDM) reconstructed grain maps to high-resolution X-ray CT reconstructions of the fracture surfaces in the crack initiation and short-crack growth regions of six ultrasonic fatigue specimens. Crack–grain–boundary intersections were analyzed at 81 locations across the six crack paths. The basal intragranular, non-basal intragranular, or intergranular character of short-crack growth following each boundary intersection was correlated to crystallographic and geometric parameters of the trailing and leading grains, three-dimensional grain boundary plane, and advancing crack front. The results indicate that crack paths are dependent on the combined crystallographic and geometric character of the local microstructure, and crack path prediction can be improved by use of dimensionality reduction on subsets of high-linear-correlation microstructural parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Chemical compatibility of hollow ceramic cenospheres as thermal insulation for high-temperature thermal energy storage applications with molten nitrate salt

An effective insulation material that is both thermally and chemically stable in molten salts could transform the design of molten-salt-based thermal energy storage (TES) tanks. Most current molten salt TES tanks hold the metallic tank structure in direct contact with hot salt inventory, a design which leads to thermal expansion of the tank and triggers stresses that can lead to thermomechanical failures. With an internal insulation to lower the temperature at the tank structure, the extent of thermal expansion can be reduced, thereby reducing expansion-induced stresses and allowing for consideration of lower-cost tank structure materials. Conventional insulation materials are either 1) too porous and allow molten salts to permeate into the matrix, which significantly increases the thermal conductivity or 2) too dense and have a thermal conductivity that cannot provide sufficient thermal insulation. This paper presents an alternative thermal insulation concept using cenospheres which have an alumino-silicate structure. The cost analysis suggests that the low-density cenospheres can be one of the cheapest materials to provide cost-effective thermal insulation. The chemical compatibility of cenospheres is investigated in molten 60 wt% NaNO3/40 wt% KNO3 salt which is close to industrial-grade Solar Salt. This paper shows that diffusion of the sodium and potassium cations from the salt into the cenospheres occurs based on weight analysis, energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy. The cation diffusion breaks the bridging oxygen bonds and causes volume expansion of the microstructure which is responsible for the failure of the cenosphere particles. The chemical composition of the cenospheres is found to affect their compatibility with molten nitrate salt. A cenosphere product with low iron content showed the best compatibility with an average survival rate of 77.9% +/- 9.8% after 7 days of immersion in the molten nitrate salt. While even the low-iron cenospheres appear to require protection from direct molten salt contact, their slow degradation rate, closed-cell porosity, and low cost hold potential for effective use as internal tank insulation.

14 SOLAR ENERGY↗
DOE OSTI2021

In situ synchrotron diffraction and modeling of non-equilibrium solidification of a MnFeCoNiCu alloy

The solidification mechanism and segregation behavior of laser-melted Mn 35 Fe 5 Co 20 Ni 20 Cu 20 was firstly investigated via in situ synchrotron x-ray diffraction at millisecond temporal resolution. The transient composition evolution of the random solid solution during sequential solidification of dendritic and interdendritic regions complicates the analysis of synchrotron diffraction data via any single conventional tool, such as Rietveld refinement. Therefore, a novel approach combining a hard-sphere approximation model, thermodynamic simulation, thermal expansion measurement and microstructural characterization was developed to assist in a fundamental understanding of the evolution of local composition, lattice parameter, and dendrite volume fraction corresponding to the diffraction data. This methodology yields self-consistent results across different methods. Via this approach, four distinct stages were identified, including: (I) FCC dendrite solidification, (II) solidification of FCC interdendritic region, (III) solid-state interdiffusion and (IV) final cooling with marginal diffusion. It was found out that in Stage I, Cu and Mn were rejected into liquid as Mn 35 Fe 5 Co 20 Ni 20 Cu 20 solidified dendritically. During Stage II, the lattice parameter disparity between dendrite and interdendritic region escalated as Cu and Mn continued segregating into the interdendritic region. After complete solidification, during Stage III, the lattice parameter disparity gradually decreases, demonstrating a degree of composition homogenization. The volume fraction of dendrites slightly grew from 58.3 to 65.5%, based on the evolving composition profile across a dendrite/interdendritic interface in diffusion calculations. Postmortem metallography further confirmed that dendrites have a volume fraction of 64.7 ± 5.3% in the final microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models

This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of parameters. The application problem presented in this work is that of predicting creep in Grade 91 steel at 600°C. The material response is defined with a physically based microstructural model with constitutive equations emulating several observed phenomena in Grade 91 and embodied into an explicit geometry mesoscale finite element model for prior austenite grains and grain boundaries. Creep within the grains and in grain boundaries are represented by crystal plasticity for dislocation motion and a physics-based model for cavity growth and nucleation, respectively. The creep behavior of this material is influenced by several parameters, some of which have a wide range of variation based on experimental data. UQ combined with microstructural modeling can discover the core microstructural causes of experimental variability, leading to improved materials with lower variability in critical long-term material properties. In this study, we investigate the model's uncertainty to identify material properties that may be modified during production to increase creep life and analyze different components of the crystal plasticity model for improvements. For this purpose, a quantity of interest is defined as time to minimum creep rate, which correlates well to the creep failure of the material. A deep neural network model was trained and validated to be used as a surrogate for the finite element model. Then, a variance-based sensitivity analysis is performed on the surrogate model to find the Sobol indices of the input parameters in respect to the output quantity of interest. The Sobol indices are used to reduce the dimensionality of the model. Generalized polynomial chaos expansion is used on the reduced basis models to propagate the uncertainty from the input parameters to the quantity of interest using the deep neural network surrogate model. These results are benchmarked against uncertainty propagation using Monte Carlo simulations. In conclusion, the UQ performed through the reduced basis model captures almost all the uncertainty in the model with significantly fewer simulations, making it possible to perform the UQ directly via simulations with the finite element model rather than surrogate machine-learned models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Characterization of zirconium carbide microspheres synthesized via internal gelation

Microspheres of zirconium carbide with grain size 40-320 nm were synthesized using internal gelation techniques and characterized by scanning electron microscopy, synchrotron X-ray diffraction, and neutron total scattering. Compared with a polycrystalline benchmark ZrC sample prepared by plasma vapor phase deposition, the microspheres display lower variance in grain size and considerably lower microstrain representative of a more homogenous internal microstructure. However, excess carbon was present in the microspheres, evident in both the X-ray and neutron diffraction data as well as a corresponding hypostoichiometric ZrC phase. Furthermore, the excess carbon phase is assumed to be pockets of carbon that remained unreacted through the combined internal gelation and subsequent carbothermic reduction synthesis process. Atomic-scale structural characterization with neutron PDF analysis confirmed the presence of localized nano-sized domains of graphite-like carbon material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ex-situ Heat Treatment of TEM Foils in a Custom Titanium Fixture: A Case Study on Ni-based Superalloy

The advancement of microstructural characterization at the nanoscale is critical to understanding the microstructural evolution and performance of engineering materials. Transmission electron microscopy (TEM) plays a vital role in such investigations, particularly when coupled with controlled ex- and in-situ experiments. In this study, we introduce a novel method for ex-situ heat treatment (HT) of TEM foils using a custom-designed fixture, made from pure titanium, and vacuum furnace to inhibit oxidation. This approach ensures precise temperature control and minimal sample contamination during HT, critical for substructural characterization and analysis of metallic materials. The fixture consists of a titanium base with three slits, for three sample foils, and a titanium cap for closure. The entire assembly is placed in a vacuum heat treatment furnace with high vacuum capability to prevent oxidation. To validate the effectiveness of the setup, precipitation behavior and microstructural changes were studied in an IN725 variant heat-treated at 500°C for 1 hour and 282 variant heat-treated at 700°C for 1 hour, as case studies.

electron microscopy↗
DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Characterization of 316L Stainless Steel after Solid Phase Processing using Ultrasonic NDE Method

The Pacific Northwest National Laboratory undertook the Materials Characterization, Prediction, and Control Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). A motivation of the Materials Characterization, Prediction, and Control Project was to demonstrate ultrasonic testing as a nondestructive evaluation method to complement traditional destructive methods for characterizing material microstructure with emphasis on grain size determination using a method that may have future applications for real-time inline process monitoring. The objective of the work described in this report is to establish the process and an analysis method for measuring grain sizes of polycrystalline metals with ultrafine grains using ultrasonic shear wave backscattering, building on prior studies on coarser-grained material. The work involves five tasks: Measured ultrasonic backscattering experimentally for a series of 316L stainless steel specimens with various grain sizes made by friction stir processing. Calculated ultrasonic backscattering coefficients from experimental data based on a physical measurement model. Measured ground truth grain sizes of the specimens from electron backscatter diffraction grain boundary images using a generalization of the ASTM E112 (ASTM 2021) intercept method. Built a curve of ultrasonic backscattering coefficients versus the ground truth intercept-based grain sizes to determine the correlation between mean grain sizes and ultrasonic measurements. Demonstrated the ability of using the correlation curve to deduce grain sizes with measured ultrasonic backscattering coefficients for a few 316L stainless steel specimens whose grain sizes were unknown beforehand but were targeted to be an extrapolation to larger grain sizes than used to formulate the correlation curves. Experimental procedures and computational algorithms are developed and validated for these tasks. This work establishes an ultrasonic technique for characterizing material microstructure with ultrafine grains that are often resulted by solid-phase processing. The technique is nondestructive, and it has the potential to be used for real time inline process monitoring. This work successfully demonstrates the viability of an ultrasonic nondestructive evaluation method for microstructural characterization of material having ultrafine grain structure (as small as 1?mm) and produced by an advanced manufacturing method. This includes a demonstration of the method to extrapolate to other conditions. While not demonstrated here, the method is expected to be viable for in-line, or near-inline, process monitoring in advanced manufacturing applications with suitable consideration for access of instrumentation to the material being manufactured.

316 L Stainless Steel↗
DOE OSTI2025

Characterization of the degradation of gamma-irradiated elastomers using Raman spectroscopy

This report presents key findings from Raman spectroscopic analysis of gamma-irradiated rubber samples extracted from a laminated lead-damped rubber (LDR) seismic isolation device. The samples were exposed to gamma radiation from a 60Co source in a Foss Therapy Services gamma irradiator, reaching absorbed doses up to 1600 kGy. A distinct threshold near 400 kGy was identified, beyond which significant spectral changes were observed. Two Raman peaks - at approximately 425 cm-1 and 2440 cm-1 - were tracked as a function of dose using Gaussian fitting. The 425 cm-1 peak, attributed to sulfur–sulfur (S–S) bond stretching (resulting from vulcanization of the rubber), exhibited a dose-dependent upshift, indicating radiation-induced crosslinking within the sulfur-based polymer network. Conversely, the 2440 cm-1 peak, likely associated with vibrational modes of additives or impurities, showed a downward shift with increasing dose, suggesting chain scission and degradation of non-rubber constituents. These results provide first-of-a-kind insights into the microstructural evolution of elastomers under high-dose gamma irradiation and establish a preliminary dose threshold for significant degradation. Future work will incorporate multi-modal characterization—including Fourier Transform Infrared (FTIR) spectroscopy, scanning electrom microscopy (SEM) of the rubber surface morphology, thermogravimetric analysis (TGA) to determine changes in thermal stability, and mechanical testing—to correlate molecular-level changes with macroscopic performance of these elastomers as damping media in seismic isolation devices. These findings are expected to provide regulatory guidance and design criteria for qualifying low-damping rubber seismic isolators in advanced nuclear reactor applications.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Effect of Heat Treatment on Microstructure and Mechanical Property of 316L Stainless Steel Produced by Laser Powder Bed Fusion

The advanced non-light water reactor designs (Gen IV reactors), including molten salt/ very high temperature/ sodium-cooled and lead-cooled fast reactors, typically operate at higher temperatures and more extreme radiation conditions than light water reactors. An intrinsic part of the deployment and progress of Gen IV reactor designs is selecting the most suitable structural material for a specific application. Additive manufacturing (AM), a fairly new process of making physical, three-dimensional objects from a computer design file, is going to completely change the way of design, build and certify nuclear systems. It offers a range of opportunities to produce complex geometries from existing materials, offers new routes for processing of previously difficult to process materials, allows for design of new high-performance materials, and finally facilitates hybridization of dissimilar materials. This emerging technology has successfully produced cars, wind turbine blade molds and even live cells. It could also open up big opportunities for the nuclear industry to quickly deploy technologies at a fraction of the cost. So far, AM techniques have been preliminarily applied in the field of nuclear reactors, including the classical parts such as the pressure vessel of a small reactor with 508-III steel, the bottom nozzle of a fuel assembly with 304L steel, the fuel cladding with zirconium alloy and the integrated impeller of a pump and the multi-channel valve body with 316L steel [6,7]. The AM applications for operating nuclear reactors started in auxiliary plant components and have slowly migrated to metallic reactors and core components, but many of these are not safety critical components. Although many parts used for nuclear reactors have been fabricated by AM techniques, practical applications in engineering are still a long way off due to the uncertainty factors focused on the processing, material properties, analysis methods and application standards, which feeds the safety and life-cycle of the nuclear reactor. Due to rapid, repeated heating and cooling during production, a high dislocation density was present in the AM material. This microstructure feature is unstable at elevated temperature while high temperature is one of the typical operation environments for nuclear reactors. Thus, it is important to understand the thermal effect on the microstructure of AM material. The objectives of this study are to investigate the effect of heat treatment on the microstructure and mechanical properties of 316L stainless steel produced by laser powder bed fusion additive manufacturing, and to determine an appropriate heat treatment practice that will be applied to the lightweight AM lattice-structured material with the same chemistry. The heat treatment study consisted of annealing the samples at a temperature range of 800 to 1200 oC with a 50 oC increment for different times (1-24 hours), followed by vacuum or air cooling. Microstructural characterization was carried out by Scanning Electron Microscope (SEM). Grain size and crystallographic orientation were investigated by Electron Backscatter Diffraction (EBSD). Vickers hardness tests with a 0.5 kg load were employed to determine the hardness of samples after different heat treatments. After heat treatment, the random crystallographic orientation was preserved, and the volume fraction of high-angle grain boundaries (grain boundary misorientation =15 oC) remained the same. The dislocation density decreased with annealing temperature due to recovery. The fine subgrain structures in the as-printed specimen were quite stable up to 1200 oC. Minimal recrystallization was observed up to 1200 oC. Recrystallization initiated only after 8.5 hours at 1200 oC. The SEM images did not show obvious dependence of microstructure on cooling rate. The hardness of the specimens decreased with increasing annealing temperature as a result of the decrease in dislocation density. It is interesting to note that the AM material showed very similar hardness to the wrought material when annealing at similar temperature, although the microstructures are very different. Annealing at 1050 oC for 1 hour followed by air cooling was selected as the heat treatment procedure for the lattice designed lightweight AM 316L material.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coal-based Bricks & Blocks (CBBs): Process Development to Prototype Fabrication Coupled with Techno-Economic Analysis and Market Survey

The decline of coal use for energy production provides an abundance of local feedstock for new innovative uses and value-added products. Expanding the U.S. coal-value chain to manufacture high-value carbon products can strengthen the nation’s energy and mineral security, enhance the U.S. national defense security, increase the United States’ economic prosperity, while achieving U.S. environmental objectives. The primary project goal is a relatively light-weight composite product with superior (or comparable) compressive strength. Both virgin and, where available, post-consumer recycled thermoplastic versions are tested for each thermoplastic species. A useful attribute of thermoplastics as binders is that they can be heated to their melting point, cooled, and reheated again without significant degradation. A key advantage of thermoset CBBs is that they require only mixing and molding. CBB advantages include low cost, availability, binding ability and processability. Coal-based bricks and blocks (CBBs) weigh about 50% less than clay bricks and can be manufactured with an interlocking design to promote ease of use for the novice builder. CBB formulation is evaluated according to a design-of-experiments (DoE) approach. DoE variables are a) relative weight fractions of binder, b) relative proportions of large versus small (milled) anthracite size fractions, and c) additive percentage. Fabrication methods include hot-press molding and extrusion, the later being the most commercially viable. CBBs are tested for compressive strength, modulus of rupture (by flexure test) and water absorption per ASTM C67, with density determined by the Archimedes drainage method. Fractured interfaces are examined by SEM (Scanning Electron Microscopy) to resolve fracture dynamics and interior microstructure uniformity. Differential scanning calorimetry (DSC) is used to compare plastic transition temperatures i.e., glass and melting temperatures to contrast virgin with post-consumer recycled thermoplastics and optimize their usage. These results are used in the DoE analysis to identify the binder and relative weight percentages for optimum strength, density, and porosity. Overall, CBBs possess strength comparable to clay-based bricks but are non-permeable and hydrophobic, and hence resistant to degradation by freeze-fracturing, corrosion, and efflorescence. The strongest composites have been made with the following thermoplastic binders (in order of strength): thermoset, high-density polyethylene crosslink resin, high-density polyethylene, nylon 6/6, and polypropylene. Results from a techno-economic analysis TEA show economy of scale for CBBs by modularization and reveal the binder as the cost driver for material costs. Ideally, the incorporation of post-consumer recycled thermoplastic will decrease material acquisition costs and increase product sustainability. Notably, CBBs do not require the high temperature calcination needed to produce cement, nor do they require firing in the 1600-2400 °F range for three days using natural gas, as do clay brick equivalents. Instead, CBBs are heated to a modest <600 °F according to the melt flow index of the thermoplastic binder. Existing anthracite mines can be expanded to produce CBBs to reduce aggregate transportation costs and emissions that exist for clay bricks. TEA reflects this reduced energy cost while a comparative CO2 emission analysis quantifies the reduced environmental footprint. The market survey identifies several commercialization opportunities, dependent upon the brick classification.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗