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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Downselection and Basic Properties of Additively Manufactured ODS Alloys

In the AMMT program the work package for development of new materials aimed to explore the advanced manufacturing techniques that are feasible for the manufacturing of advanced materials components. A merit-based feasibility study was attempted to identify an accelerated development path for dispersion strengthened (ODS) alloys by creatively combining additive manufacturing (AM) technologies with the recent advances in ODS materials and traditional manufacturing technologies. For the fiscal year, the primary tasks were focused to develop additive manufacturing (AM) and post-build processing route for oxide dispersion strengthened (ODS) ferritic (Fe-Cr alloy or 14YWT) and austenitic (Fe-Cr-Ni alloys or 316L and 316H) alloys and to perform basic microstructural and mechanical characterizations to provide feedbacks to the alloy and processing design. Further, the multi-laboratory effort created collaboratively a decision criteria matrix to evaluate and downselect the new materials processed by advanced manufacturing methods. This report is to describe the ODS alloy processing routes combining AM processes and post-build thermomechanical treatments, mechanical and microstructural characteristics of the newly developed materials, and the application results of the decision criteria matrix for the AM ODS alloys including a downselected material and feasible processing route. Key mechanical test results including tensile strength, tensile ductility, and fracture toughness data and are reported and explained. Higher strength was measured from the ferritic ODS alloys, while higher ductility and fracture toughness were measured from the austenitic ODS alloys. Many of the decision criteria were scored the same for the AM ferritic and austenitic ODS alloys, however, the generally known fact that the austenitic alloys have higher corrosion resistance and significantly better ductility. Although these scores are not significantly different to make them highly discernable, the austenitic ODS alloys were downselected to be the primary materials group in the future research on ODS materials in AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine Learning an Ab-Initio Based Bond-Order Potential for Bismuthene

Bismuthene is a heavy 2D material whose strong spin–orbit coupling and recently observed single-element ferroelectricity have intensified interest in its structural, vibrational, and transport properties. Accurate modeling of these behaviors requires a short-range interatomic potential that can reproduce the underlying bonding physics at a fraction of the computational cost of first-principles methods. However, such a potential is currently unavailable. Here, in this work, we construct a Tersoff bond-order potential for β-bismuthene using a reinforcement-learning framework that integrates a continuous Monte Carlo Tree Search with a simplex-based local optimizer. The optimized parameter sets reproduce first-principles lattice constants, cohesive energy, the equation of state, elastic constants, and phonon dispersion. We validate the models by performing thermal-conductivity calculations and uniaxial fracture simulations our findings confirm the reliability of the resulting models across multiple thermomechanical regimes. Comparison of the three best solutions reveals how differences in pairwise interactions, angular terms, and bond-order behavior govern phonon features and mechanical responses. We demonstrate an interpretable and computationally efficient potential for bismuthene and demonstrate a general reinforcement-learning strategy for developing bond-order models in emerging 2D materials.

deformation↗
DOE OSTI2022

Performance Advantaged ..beta..-Ketone Containing Polymers - Benefits in Manufacturing, Performance, and End-of-Life

Biomass derived chemicals can possess extended functionality, often in the form of heteroatoms like oxygen and nitrogen, that can enable performance advantaged properties in emergent materials. These performance advantages can manifest in multiple ways such as reduced manufacturing intensity, better performance, or enhanced end-of-life options. One illustrative example of this concept is ..beta..-ketoadipic acid (..beta..KA), a C6 dicarboxylic acid with a ketone in its backbone. ..beta..KA can be obtained via biological cultivation from aromatic compounds, sugars, and even waste plastics. When ..beta..KA is implemented into polymers, namely nylons, in place of adipic acid the overall material properties are increased. Specifically, the glass transition temperature (which is the measurement at which temperature a plastic softens) is increased by 69 degrees C and the water permeability is reduced by 20%. Molecular dynamic (MD) simulations reveal that the ..beta..-ketone in ..beta..KA leads to restricted movement across multiple backbone carbons when compared to adipic acid. Furthermore, MD simulations reveal that the ..beta..-ketone, when compared to no-ketone or an a-ketone, can lead to an increase in hydrogen bonding between neighboring chains. Both phenomena may help explain the molecular origin of the increases in polymer performance. When implemented into polyesters, namely PET, ..beta..KA can maintain the requisite performance while enabling enhanced degradation. Aside from performance advantages in thermomechanical performance, the production of ..beta..KA also is advantaged in its manufacturing. Although estimates for the minimum selling price (MSP) of ..beta..KA exceed adipic acid the manufacture of ..beta..KAwould reduce supply chain energy and GHG emissions by >50% and >30% respectively. Further TEA analysis reveals that the MSP of ..beta..KA is primarily driven by the feedstock cost while the capital expenditures are driven largely by fermentation costs. Overall, the work presented within will be illustrative of how biomass derived molecules, namely ..beta..KA, can manifest performance advantages across multiple benchmarks and may enable a path to market for biomass-derived materials.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗
DOE OSTI2023

Coupling Thermal-Hydraulics with Reactor Pressure Vessel Fracture Models

Because of the importance of maintaining the integrity of the reactor pressure vessel (RPV) in light-water reactors, significant effort has been devoted over the last several decades to understand the potential failure mechanisms, characterize how material properties evolve due to environmental conditions, and develop tools to assess the probability of fracture in aged RPVs during potential transient events. One important aspect of this problem that has not yet been fully addressed is the effects of nonuniform cooling on the RPV inner wall due to the way low-temperature water injected into the primary coolant system is distributed within the RPV during potential loss-of-coolant accident transients. Colder temperatures are expected in the regions near the inlets, causing a “cold-plume” effect. Rapid cooling of the RPV wall increases the likelihood of fracture initiation, and localized cooling due to cold-plume effects could potentially exacerbate this problem. The Grizzly code can perform a three-dimensional simulation of the RPV thermomechanical response as well as the probabilistic assessment of fracture for a population of pre-existing flaws, which is necessary to account for spatial variations in coolant temperature. This report documents a first effort to couple Grizzly RPV fracture models with computational fluid dynamics models performed using the Cardinal code, which allows for a realistic representation of the temperature distribution. This report demonstrates this coupling approach on two test cases: a simplified proof-of-concept scenario and a realistic small-break loss-of-coolant accident scenario. In both cases, the effects of the spatially varying temperature are evident; although, because the small-break loss-of-coolant accident scenario was far from challenging the RPV’s margins, it is still inconclusive how important cold-plume effects are in realistic accident scenarios. However, this effort represents an important step toward performing realistic analyses to determine to what extent spatially nonuniform cooling might affect RPV integrity under more aggressive accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Test Plan to Investigate the Optimal Cure Schedule of an Epoxy Resin for Its Application as an Adhesive in Optocouplers

Epoxy resins are polymeric materials that are known for their versatility, low cost, and strong thermal and mechanical properties. They can be used as coatings, adhesives, automotive primers, and have become staples in electronics, aerospace composites and semiconductor encapsulates. Recently, LANL has experienced a decline in the quality of a specialized electronic device, called an optocoupler, which is normally acquired from commercial suppliers. Because of this, a group at LANL is exploring the feasibility of in-house manufacturing of an optocoupler that is better suited for their application. The current prototype has resulted in adhesive failure after being exposed to several thermal cycles. There is a need to investigate the possible reasons for this failure, particularly how the cure schedule of the epoxy might affect its adhesive strength over time and in cycled temperatures. To assist in this investigation, a test plan has been developed involving multiple experiments using thermomechanical analysis (TMA), dynamic mechanical analysis (DMA) and differential scanning calorimetry (DSC).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Toward the Prediction and Control of Glass Transition Temperature for Donor–Acceptor Polymers

Semiconducting donor–acceptor (D–A) polymers have attracted considerable attention toward the application of organic electronic and optoelectronic devices. However, a rational design rule for making semiconducting polymers with desired thermal and mechanical properties is currently lacking, which greatly limits the development of new polymers for advanced applications. Here, polydiketopyrrolopyrrole (PDPP)-based D–A polymers with varied alkyl side-chain lengths and backbone moieties are systematically designed, followed by investigating their thermal and thin film mechanical responses. The experimental results show a reduction in both elastic modulus and glass transition temperature (Tg) with increasing side-chain length, which is further verified through coarse-grained molecular dynamics simulations. Informed from experimental results, a mass-per-flexible bond model is developed to capture such observation through a linear correlation between Tg and polymer chain flexibility. Using this model, a wide range of backbone Tg over 80 °C and elastic modulus over 400 MPa can be predicted for PDPP-based polymers. This study highlights the important role of side-chain structure in influencing the thermomechanical performance of conjugated polymers, and provides an effective strategy to design and predict Tg and elastic modulus of future new D–A polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On Residual Stresses and Reference Temperatures in Thermomechanical Simulations of Photovoltaic Modules Using the Finite Element Method

Thermomechanical simulation of photovoltaic (PV) modules using the finite element method (FEM) is a useful tool to evaluate module design features in terms of structural integrity, reliability, and durability. One of the main challenges in the numerical modeling of a PV module is the incorporation of residual stresses induced by the manufacturing process. Modeling assumptions and abstractions are necessary to limit the model complexity and reduce the computational time. However, oversimplifications and incorrect assumptions can lead to erroneous numerical results. Unfortunately, much simulation work still neglects process-induced stresses. This can lead to incorrect predictions of the stress-strain history and erroneous conclusions during the design process. In this work, we review current modeling practices for incorporating process-induced stresses, and contrast numerical models that consider residual stresses with those that neglect them. We find that the simulation objective and available material properties dictate which process steps need to be modeled, and explore in depth the modeling of residual stresses induced by the lamination process. We demonstrate that a simplified cooldown procedure at the beginning of the simulation can increase the model accuracy and discuss appropriate choices for starting and reference temperatures in the finite element model.

14 SOLAR ENERGY↗
DOE OSTI2024

Thermo-rheological snapshot of melter feed conversion to glass

Slurry feed charged into an electric melter creates a layer of reacting and melting material (termed cold cap) that floats on the surface of molten glass. The rheological behavior of heated melter feed affects the spreading of slurry at the top of the cold cap and the stability of the primary foam, affecting cold-cap coverage and melter plenum temperatures. The apparent viscosity of a high-alumina high-level waste melter feed was assessed by thermomechanical analysis, high-temperature viscometer, and the hot stage microscopy method, yielding viscosity estimates from ≈10 7.5 Pa s at 550°C to ≈10 2.5 Pa s at 1050°C. As the temperature of feed materials increased, their state changed from rigid solid to dilatant fluid, to pseudoplastic bubbly liquid with dissolving solids, to fully developed foam, and finally to Newtonian glass melt.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Adamantine 1.0: A Thermomechanical Simulator for Additive Manufacturing

Adamantine is a thermomechanical simulation code that is written in C++ and built on top of deal.II (Arndt et al., 2023), p4est (Burstedde et al., 2011), ArborX (Lebrun-Grandié et al., 2020), Trilinos (The Trilinos Project Team, 2020), and Kokkos (Trott et al., 2022). Adamantine was developed with additive manufacturing in mind and it is particularly well adapted to simulate fused filament fabrication, directed energy deposition, and powder bed fusion. Adamantine employs the finite element method with adaptive mesh refinement to solve a nonlinear anisotropic heat equation, enabling support for various additive manufacturing processes. It can also perform elastoplastic and thermoelastoplastic simulations. It can handle materials in three distinct phases (solid, liquid, and powder) to accurately reflect the physical state during different stages of the manufacturing process. To enhance simulation accuracy, adamantine incorporates data assimilation techniques (Asch et al., 2016). This allows it to integrate experimental data from sensors like thermocouples and infrared (IR) cameras. This combined approach helps account for errors arising from input parameters, material properties, models, and numerical calculations, leading to more realistic simulations that reflect what occurs in a particular print.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adhesion in thermomechanically processed seaweed-lignocellulosic composite materials

The increasing concerns associated with petroleum-derived polymers motivate the development of sustainable, renewably sourced alternatives. In ubiquitous applications such as structural materials for infrastructure, the built environment as well as packaging, where natural materials such as wood are used, we rely on nonrenewable and nondegradable polymers to serve as adhesives. In wood panels, such as medium density fiberboards (MDFs), formaldehyde-based resins are predominantly used to bond wood fibers and to provide strength to the materials. To further mitigate the environmental impact of construction materials, more sustainable adhesives need to be investigated. Here, in this article, we introduce Ulva seaweed as an adhesive to enable cohesion and strength in hot-pressed wood panels. Upon hot-pressing, powdered Ulva flows in between the wood particles, generating a matrix, which provides strong binding. We show that the flexural strength of Ulva-bonded wood biocomposites increases with increasing Ulva concentrations. At an Ulva concentration of 40 wt%, our composites reach an average elastic modulus of 6.1 GPa, and flexural strength of 38.2 MPa (compared to 4.7 GPa and 22.6 MPa, respectively, for pure wood compressed at the same pressing conditions). To highlight the bonding mechanisms, we performed infrared and x-ray photoelectron spectroscopy and identified indications of fatty acid mobility during hot-pressing. In addition, we demonstrate that the presence of Ulva improves other properties of the composites such as water resistance and fame retardancy. Ulva is also shown to behave as an excellent adhesive agent between two prepressed beams. Finally, we perform an in-depth analysis of the environmental impact of wood-Ulva biocomposites.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials↗
DOE OSTI2025

Model form and sensitivity analysis of CALPHAD-based nucleation models in b-stabilized Ti alloys

Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.

Rodriguez Negron, A. M.↗
DOE OSTI2020

Characterization Report for the MP-1 Experiment Fabrication Campaign

This report covers the results of MP 1 fuel characterization analysis to provide a detailed understanding of the as-fabricated fuel that would be irradiated in the MP 1 (Mini-Plate 1) experiment. The work was performed at Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), and Los Alamos National Laboratory (LANL). Characterization of the as-fabricated fuel was performed in accordance with Characterization Plan for the Fabrication of U 10Mo for the MP 1 Experiment, hereinafter the MP 1 Characterization Plan (MAQP 2016). Under the MP 1 Characterization Plan, fuel foils at different points in the foil fabrication process (e.g., hot rolled annealed, cold rolled annealed) were studied to understand the effect of various thermomechanical processes on the fuel microstructure. Samples were sent to each of the three organizations so that testing and analysis could be performed independently using similar equipment and a standardized set of measurement and analysis procedures. The MP 1 experiment will provide an opportunity to understand the effects of processing conditions on the final fuel microstructure, to compare independently obtained results, and achieve a three-way validation. PNNL characterized 28 uranium–10 wt% molybdenum (U 10Mo) samples. Six pieces/specimens from each sample/foil were sectioned, in accordance with the MP 1 Characterization Plan. Similarly, INL and LANL also examined 24 and 17 U 10Mo specimens, respectively. These total 69 samples consist of six types of MP 1 characterization foils fabricated by Babcock and Wilcox Technologies (BWXT) from ingots produced by the Y-12 National Security Complex: • 0.047 in.-thick hot-rolled and annealed samples with and without Zr layers • 0.02 in.-thick cold-rolled and annealed samples with and without Zr layers • 0.01 in.-thick cold-rolled and annealed samples with and without Zr layers. Microstructure, chemical composition, carbide morphology, U 10Mo foil thickness, Zr thickness, mechanical properties (microhardness), and density were evaluated in both longitudinal and transverse directions for foils of the three different thicknesses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Characterization Report for the MP-1 Experiment Fabrication Campaign (Rev.1)

This report covers the results of MP 1 fuel characterization analysis to provide a detailed understanding of the as-fabricated fuel that would be irradiated in the MP 1 (Mini-Plate 1) experiment. The work was performed at Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), and Los Alamos National Laboratory (LANL). Characterization of the as-fabricated fuel was performed in accordance with Characterization Plan for the Fabrication of U 10Mo for the MP 1 Experiment, hereinafter the MP 1 Characterization Plan (MAQP 2016). Under the MP 1 Characterization Plan, fuel foils at different points in the foil fabrication process (e.g., hot rolled annealed, cold rolled annealed) were studied to understand the effect of various thermomechanical processes on the fuel microstructure. Samples were sent to each of the three organizations so that testing and analysis could be performed independently using similar equipment and a standardized set of measurement and analysis procedures. The MP 1 experiment will provide an opportunity to understand the effects of processing conditions on the final fuel microstructure, to compare independently obtained results, and achieve a three-way validation. PNNL characterized 28 uranium–10 wt% molybdenum (U 10Mo) samples. Six pieces/specimens from each sample/foil were sectioned, in accordance with the MP 1 Characterization Plan. Similarly, INL and LANL also examined 24 and 17 U 10Mo specimens, respectively. These total 69 samples consist of six types of MP 1 characterization foils fabricated by Babcock and Wilcox Technologies (BWXT) from ingots produced by the Y-12 National Security Complex: (a.) 0.047 in.-thick hot-rolled and annealed samples with and without Zr layers; (b.) 0.02 in.-thick cold-rolled and annealed samples with and without Zr layers; and (c.) 0.01 in.-thick cold-rolled and annealed samples with and without Zr layers. Microstructure, chemical composition, carbide morphology, U 10Mo foil thickness, Zr thickness, mechanical properties (microhardness), and density were evaluated in both longitudinal and transverse directions for foils of the three different thicknesses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

High-Temperature-Performance Cyanate Ester Composites with Carboranes

Cyanate ester (CE) is an important class of materials among high-temperature performance thermosets. It is used in aerospace launch vehicles, heat sinks, booms, and trusses of satellites etc. due to its high glass transition temperatures (>220°C), excellent thermal stability, and low flammability. Current approaches to improve the thermal stability of CE include incorporation of siloxanes or phosphorus- based flame retardants (PFRs). In this work, we have explored boron-based hydroxy (PD) and epoxy (EP) functionalized carborane additives to improve the thermal properties of CE. Carborane fillers were solvent blended at various mass loadings in the resin and cured to study their effect on thermal properties. PD and EP carboranes react with CE to form iminocarbonate and oxazolidinone linkages respectively. Cure kinetics studies at different wt% loadings explained that carboranes catalyze the curing reaction by reducing curing activation energy by about 54% and 26% for 10 wt% loadings of PD and EP carboranes respectively. In addition, carborane-filled cyanate ester (CE) nanocomposites demonstrate an exceptionally high thermal stability as compared to the pristine resin in air and inert environment. Our thermogravimetric analysis (TGA) experiments show that the ultimate char yield of the resin can be increased from 0% to as high as 76% and 82% with 30 wt% PD and EP carborane loading respectively at 1000 °C in air. The initial degradation temperature T d;5 of the composites decreased with increasing carborane loadings in both air and argon. For instance, T d;5 for CE was 465 and 471.6 °C in argon and air while that for P20 was 437.4 and 452.1 °C. Modulated TGA studies gave evidence of the effect of carboranes on degradation kinetics and the mechanism of the resin in air and inert environment. The effect of bonding between carboranes and CE at various loadings on the thermal expansion of the matrix was also studied using Thermomechanical Analyzer (TMA). PD carborane reduced the T g for P20 to about 225 °C while CE had T g >350 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Wastewater Recycling Using a Hygroscopic Cooling System

This project by the Energy & Environmental Research Center (EERC), Baltimore Aircoil Company (BAC), and Great River Energy (GRE) evaluated the concept of recycling wastewater at a coal-fired power plant using a hygroscopic cooling system, which is an evaporative cooling technology analogous to conventional cooling towers, except that sparingly soluble dissolved solids are precipitated and removed as waste solids instead of purging them with a liquid blowdown stream. This technology can maximize the use of plant makeup water by obtaining useful evaporative cooling from wastewater while minimizing the volume of wastes needing disposal. Experimental activities were conducted in two phases, a laboratory-based evaluation of the properties of wastewater from the host site, GRE’s Coal Creek Station near Underwood, North Dakota, and a field test of a small pilot hygroscopic cooling system at the host site power plant. Findings from the laboratory study informed the design of the pilot system and the system’s field test performance served as the basis for a techno-economic analysis (TEA) of the hygroscopic recycling concept. At the preferred operating conditions identified during the TEA, the wet-bulb approach temperature of the tower was 7.3°C (13°F) and the volume of blowdown produced by the plant was reduced to 5.4% of its incoming volume. Waste solids produced during field testing were classified as nonhazardous waste based on the measured hazardous element content and evaluation of their leaching potential. However, to qualify as a solid for landfill disposal i.e., as determined by the U.S. Environmental Protection Agency’s paint filter test, it appears that a dewatering step beyond hydrocyclone separation is needed. The baseline levelized cost of wastewater disposal (LCWD) for hygroscopic wastewater recycling was estimated to be $\$ $3.69–$\$ $3.72 per m3 of plant blowdown. Capital cost was estimated to contribute over 54% to the LCWD, and parameters that impact capital cost such as the heat exchange coil material of construction and the tower’s wet-bulb approach temperature were identified as having the greatest impact on overall LCWD. A LCWD estimate prepared for the same application but using thermomechanical brine evaporation was almost 40% higher than that calculated for hygroscopic cooling, despite recovering distilled-quality water for reuse, while the LCWD for disposal-only, deep well injection was estimated to be 30% lower compared to hygroscopic wastewater recycling.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗
DOE OSTI2023

Physics-informed machine-learning model of temperature evolution under solid phase processes

We model temperature dynamics during Shear Assisted Proccess Extrusion (ShAPE), a solid phase process that plasticizes feedstock with a rotating tool and subsequently extrudes it into a consolidated tube, rod, or wire. Control of temperature is critical during ShAPE processing to avoid liquefaction, ensure smooth extrusion, and develop desired material properties in the extruded products. Accurate modeling of the complicated thermo-mechanical feedbacks between process inputs, material temperature, and heat generation presents a significant barrier to predictive modeling and process design. In particular, connecting micro-structural scale mechanisms of heat generation to macro-scale predictions of temperature can become computationally intractable. In this work we use a neural network (NN) model of heat generation to bridge this gap, by combining it with a simplified model of the temperature dynamics due to conduction and convection to capture the macro scale evolution of temperature. We inform the construction of the NN heat generation model using crystal plasticity simulations at the micro-structural scale to model the effects of process inputs on generation of heat. We achieved close fits of the temperature dynamics model to a diverse experimental data-set. Further, the relationships learned by the NN model between process inputs and heat generation showed qualitative agreement with those predicted by crystal plasticity simulations.

36 MATERIALS SCIENCE↗