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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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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

An Investigation on Microstructure Evolution, Mechanical Properties, and Strain Aging of Mg-1.8Zn-0.7Si-0.4Ca Biomedical Alloy Processed by Equal Channel Angular Pressing

The influence of equal channel angular pressing (ECAP) on microstructure and mechanical behavior, as well as, strain aging during ECAP and post-ECAP of Mg-1.8Zn-0.7Si-0.4Ca biomedical alloy was examined. The alloy in solid solution heat-treated condition was processed by ECAP with route B{sub C} at 350 and 400 °C. The specimens ECAPed at 350 °C were aged at 125 and 150 °C for different times. The hardness and shear punch test results indicated that performing ECAP at 350 °C for 4 passes increases the hardness and shear strength of the alloy from 48 HV and 110 MPa to 71 HV and 188 MPa, respectively. It was revealed that the average grain size of the alloy decreases from 78 µm to about 3 µm after 4 passes of ECAP. Three precipitates of CaMgSi, Ca{sub 2}Mg{sub 6}Zn{sub 3}, and Mg{sub 2}Si were detected in the solid solution specimen. After 4 passes of ECAP at 350 °C, Ca{sub 2}Mg{sub 6}Zn{sub 3} was completely dissolved and the morphology of Mg{sub 2}Si changed from Chinese script to fiber-shaped particles. Dynamic strain aging occurred at high-temperature ECAP, and the specimens were overaged during post-ECAP aging. Small MgZn particles were detected in the overaged sample.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Supersaturated calcium carbonate solutions are classical

We will present a description of nucleation phenomena in the condensed phase that takes into account non-ideal solution effects associated with cluster-cluster interaction. To do this we employ aggregation-volume bias Monte Carlo simulation, making the estimation of free-energy of large pre-critical clusters of sizes 10-20 tractable. We will compare and contrast empirical potential and electronic structure (e.g. Density functional theory) based descriptions of molecular interaction associated with the nucleation of CaCO 3 , highlighting free-energy trends and qualitative differences in populations of pre-critical clusters as a function of supersaturation. The influence of how the precise local interaction influences the non-ideal solution behavior on the nucleation and growth processes will be highlighted. This research was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.

Henzler, Katja (ORCID:0000000335905005)↗
DOE OSTI2017

Low-Temperature Hydrothermal Synthesis of Colloidal Crystal Templated Nanostructured Single-Crystalline ZnO

Single crystal semiconductors almost always exhibit better optoelectrical properties than their polycrystalline or amorous counterparts. While three-dimensionally (3D) nanostructured semiconductor devices have been proposed for numerous applications, in the vast majority of reports, the semiconductor is polycrystalline or amorphous, greatly reducing the potential for advanced properties. While technologies for 3D structuring of semiconductors via use of a 3D template have advanced significantly, approaches for epitaxially growing nanostructured single crystal semiconductors within a template remain limited. Here, we demonstrate the epitaxial growth of 3D-structured ZnO through colloidal templates formed from 225 nm and 600 nm diameter colloidal particles via a low-temperature (~80 °C) hydrothermal process using a flow reactor. The effects of the pH of the reaction solution as well as the additive used on the 3D epitaxy process are investigated. The optical and electrical properties of the epitaxially grown nanostructured ZnO are probed by reflectance, photoluminescence, and Hall effect measurements. It is found that the epitaxially grown nanostructured ZnO generally exhibits superior properties than those of polycrystalline ZnO. The demonstrated hydrothermal epitaxy process should be applicable to other chemical solution-based deposition techniques and help extend the range of materials that can be grown into a 3D nanostructured single-crystalline form.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Bismuth-Based Perovskite-Inspired Solar Cells: In Situ Diagnostics Reveal Similarities and Differences in the Film Formation of Bismuth- and Lead-Based Films

Organic–inorganic lead-based halide perovskite compounds currently yield thin film solar cells with a power conversion efficiency (PCE) of >23%. However, replacing the lead with less-toxic elements while maintaining a high PCE remains a challenge. For this reason, there has been significant effort to develop Pb-free compounds, including methylammonium bismuth iodide (MA 3 Bi 2 I 9 ), but such systems severely underperform when compared with the prototypical Pb-based methylammonium lead iodide (MAPbI 3 ). For the latter, it is known that lead complexes with polar solvents, such as dimethyl sulfoxide (DMSO) and dimethylformamide (DMF), to form iodoplumbates which can co-crystallize into solvated phases. Herein, the solidification and growth behaviors of Bi- and Pb-based films is investigated using multi-probe in situ characterization methods. It is shown that the Bi-based compound crystallizes directly and rapidly into a textured polycrystalline microstructure from a precursor solution without evolving through intermediate crystalline solvated phases, in contrast to MAPbI 3 . This solidification process produces isolated crystals and challenges the growth of continuous and crystalline films required for solar cells. Further, it is revealed that solvent engineering with antisolvent dripping is crucial to enable the formation of continuous polycrystalline films of MA 3 Bi 2 I 9 and functional solar cells thereof.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2017

Design of a Fission 99 Mo Recovery Process and Implications toward Mo Adsorption Mechanism on Titania and Alumina Sorbents

Molybdenum-99 is a parent of the most widely used medical isotope technetium-99m. Proliferation concerns have prompted development of alternative Mo production methods utilizing low enriched uranium. Alumina and titania sorbents were evaluated for separation of Mo from concentrated uranyl nitrate solutions. System, mass transfer, and isotherm parameters were determined to enable design of Mo separation processes under a wide range of conditions. A model-based approach was utilized to design representative commercial-scale column processes. The designs and parameters were verified with bench-scale experiments. The results are essential for design of Mo separation processes from irradiated uranium solutions, selection of support material and process optimization. Mo uptake studies show that adsorption decreases with increasing concentration of uranyl nitrate; howeveL, examination of Mo adsorption as a function of nitrate ion concentration shows no dependency, indicating that uranium competes with Mo for adsorption sites. These results are consistent with reports indicating that Mo forms inner-sphere complexes with titania and alumina surface groups.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Solvation Thermodynamics of Solutes in Water and Ionic Liquids Using the Multiscale Solvation-Layer Interface Condition Continuum Model

We report molecular assembly processes are generally driven by thermodynamic properties in solutions. Atomistic modeling can be very helpful in designing and understanding complex systems, except that bulk solvent is very inefficient to treat explicitly as discrete molecules. The SLIC/CDC multiscale model combines continuum solvent electrostatics based on the solvent layer interface condition (SLIC) with statistical thermodynamic models for hydrogen bonding and nonpolar modes: cavity formation, dispersion interactions, combinatorial mixing (CDC). The SLIC/CDC model predicts Gibbs energies of solvation for a database of 500 solutes in water with average accuracy better than 1 kcal/mol both for experimental measurements and for explicit-solvent molecular dynamics simulations. The separate SLIC/CDC energy mode values agree quantitatively with those computed from explicit-solvent molecular dynamics. The SLIC/SASA multiscale model combines the SLIC continuum electrostatic model with the solvent accessible surface area (SASA) nonpolar energy mode. The SLIC/SASA model predicts Gibbs energies of solvation with better than 1.4 kcal/mol average accuracy in aqueous systems and better than 1.6 kcal/mol average accuracy in ionic liquids. Both models predict solvation entropies, and are the first implicit-solvation models capable of predicting solvation heat capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

ZAM Modeling Study to Support the Tank Closure Cesium Removal (TCCR) 1A Unit

Currently at the Savannah River Site (SRS), the Tank Closure Cesium Removal (TCCR) is an “at-tank” process designed to remove cesium from aqueous tank waste. Cesium will be removed by ion exchange using the engineered IONSIV® R9120 form of Crystalline Silicotitanate (CST) media. The current TCCR design has two columns online in a lead-lag configuration to optimize media usage and achieve the target decontamination. Once the lead column is saturated with cesium, it will be removed from service, the lag column will rotate into the lead position, and a new column with fresh ion-exchange media will be placed into the lag position. The TCCR process for cesium removal from Tank 10H is detailed in X-SOW-H- 00002. Demonstration of the system began in early calendar year 2019 with two batches of salt solution generated by dissolving saltcake in Tank 10H, followed by processing of these batches through the TCCR system. A third TCCR Tank 10H dissolved saltcake batch is scheduled for processing soon. Upon completion of the demonstration with Tank 10H dissolved saltcake, Tank 9H salt solution will be transferred to Tank 10H and subsequently processed through the TCCR unit with new CST media (referred to as R9120-B 30x60) added to new IX columns. The TCCR processing campaign of Tank 9H salt solution is referred to as TCCR-1A .

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Coupled Hydrothermal Extraction and Ligand-Associated Swellable Glass Media Recovery of Rare Earth Elements from Coal Fly Ash (Final Report)

Wayne State University (WSU) researchers, in collaboration with the University of California-Los Angeles (UCLA) and Los Alamos National Laboratory (LANL), have successfully developed a new sorbent media used in a process that concentrated the rare earth content in a coal fly ash sample from southeast MI by >350×, resulting in >13 wt% REO powder. The project developed a new DTPA-associated media that was used to concentrate total REEs. This project demonstrated a coupled hydrothermal extraction and solid-liquid recovery process that produced REO powder from raw fly ash while nearly eliminating the use of organic solvents. The project successfully: 1) identified a commercially viable ash supply with >$2.5 M in REO value being deposited monthly, 2) hydrothermally extracted >77% of REEs in coal fly ash (20% more than acid alone), 3) developed a new sorbent media that was used to concentrate REEs, 4) and engineered a process that resulted in a >13 wt% REO powder. The media also demonstrates a selectivity for mid and heavy REEs over Ce and La and the potential for use in separating individual rare earth elements. An invention disclosure for the sorbent media has been filed with WSU and a patent application will be submitted in the near future. The project examined the potential to couple hydrothermal leaching of coal fly ash with the engineering of a custom ligand-associated media to provide an organic solvent-free method of extracting and recovering REEs. Fly ash feedstock was collected from Detroit area coal-fired power plants, characterized for REE content, and subjected to a bench-top batch hydrothermal leaching/dissolution process inside custom-build pressure reactors at Los Alamos National Laboratory (LANL). This process applied a dissolution technique previously developed to process spent nuclear fuel and other nuclear materials. The modified ash was acidified and the resulting leachate was enriched with REEs along with Ca, Al, and Si. Ligands known to be effective in lanthanide/actinide separation were evaluated based on a series of criteria such as selectivity and association to organosilica through hydrophobicity. Batch experiments were conducted to establish the best conditions (e.g., pH, eluent, etc.) and best ligand systems for the effective extraction of REEs from the alkaline feed solution obtained from the hydrothermal leaching process. Once the organosilica-ligand extraction media was developed for REE concentration, an acidic solution was used to back extract and concentrate the REEs into a heavily REE-laden strip solution. The REEs in the strip solution were precipitated with oxalate to produce rare earth oxides.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Anodic processes in the chemical and electrochemical etching of Si crystals in acid-fluoride solutions: Pore formation mechanism

The interaction of heavily doped p- and n-type Si crystals with hydrofluoric acid in the dark with and without contact with metals having greatly differing work functions (Ag and Pd) is studied. The dependences of the dissolution rates of Si crystals in HF solutions that contain oxidizing agents with different redox potentials (FeCl{sub 3}, V{sub 2}O{sub 5} and CrO{sub 3}) on the type and level of silicon doping are determined. Analysis of the experimental data suggests that valence-band holes in silicon are not directly involved in the anodic reactions of silicon oxidation and dissolution and their generation in crystals does not limit the rate of these processes. It is also shown that the character and rate of the chemical process leading to silicon dissolution in HF-containing electrolytes are determined by the interfacial potential attained at the semiconductor–electrolyte interface. The mechanism of electrochemical pore formation in silicon crystals is discussed in terms of selfconsistent cooperative reactions of nucleophilic substitution between chemisorbed fluorine anions and coordination- saturated silicon atoms in the crystal subsurface layer. A specific feature of these reactions for silicon crystals is that vacant nonbonding d{sup 2}sp{sup 3} orbitals of Si atoms, associated with sixfold degenerate states corresponding to the Δ valley of the conduction band, are involved in the formation of intermediate complexes. According to the suggested model, the pore-formation process spontaneously develops in local regions of the interface under the action of the interfacial potential in the adsorption layer and occurs as a result of the detachment of (SiF{sub 2}){sub n} polymer chains from the crystal. Just this process leads to the preferential propagation of pores along the <100> crystallographic directions. The thermodynamic aspects of pore nucleation and the effect of the potential drop across the interface, conduction type, and free-carrier concentration in the crystal on the pore size and structure are discussed. The concepts developed in the study can consistently account for experimental facts characterizing the etching of silicon crystals with various electrical parameters under various conditions providing the anodic polarization of crystals in HF-containing solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Inferring the Dynamics of the State Evolution During Quantum Annealing

To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we propose to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Furthermore, using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called "slicing", we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits.

42 ENGINEERING↗
DOE OSTI2019

A graph theoretic framework for representation, exploration and analysis on computed states of physical systems

A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to these problems. Of interest are phenomena described by partial differential equations, with solutions being obtained by computation. The motivation is to gain insight that may otherwise be difficult to attain because of the high dimensionality of computed solutions. We consider graph theoretic representations that are made possible by low-dimensional states defined on the systems. These states are typically functionals of the high-dimensional solutions, and therefore retain important aspects of the high-fidelity information present in the original, computed solutions. Our method is rooted in regarding each state as a vertex on a graph and identifying edges via processes that are induced either by numerical solution strategies, or by the physics. Correspondences are drawn between the sampling of stationary states, or the time evolution of dynamic phenomena, and the analytic machinery of graph theory. A collection of computations is examined in this framework and new insights to them are presented through analysis of the corresponding graphs.

42 ENGINEERING↗
DOE OSTI2025

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING↗
DOE OSTI2018

WearGP: A computationally efficient machine learning framework for local erosive wear predictions via nodal Gaussian processes

Computational fluid dynamics (CFD)-based wear predictions are computationally expensive to evaluate, even with a high-performance computing infrastructure. Thus, it is difficult to provide accurate local wear predictions in a timely manner. Data-driven approaches provide a more computationally efficient way to approximate the CFD wear predictions without running the actual CFD wear models. In this paper, a machine learning (ML) approach, termed WearGP, is presented to approximate the 3D local wear predictions, using numerical wear predictions from steady-state CFD simulations as training and testing datasets. The proposed framework is built on Gaussian process (GP) and utilized to predict wear in a much shorter time. The WearGP framework can be segmented into three stages. At the first stage, the training dataset is built by using a number of CFD simulations in the order of O (10 2 ). At the second stage, the data cleansing and data mining process are performed, where the nodal wear solutions are extracted from the solution database to build a training dataset. At the third stage, the wear predictions are made, using trained GP processes. Two CFD case studies including 3D slurry pump impeller and casing are used to demonstrate the WearGP framework, in which 144 training and 40 testing data points are used to train and test the proposed method, respectively. The numerical accuracy, computational effiency and effectiveness between the WearGP framework and CFD wear model for both slurry pump impellers and casings are compared. It is shown that the WearGP framework can achieve highly accurate results that are comparable with the CFD results, with a relatively small size training dataset, with a computational time reduction in an order of 10 5 to 10 6 .

42 ENGINEERING↗
DOE OSTI2025

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Methods and systems for utilizing carbide lime or slag

Provided herein are methods comprising a) treating a slag solid or carbide lime suspension with an ammonium salt in water to produce an aqueous solution comprising calcium salt, ammonium salt, and solids; b) contacting the aqueous solution with carbon dioxide from an industrial process under one or more precipitation conditions to produce a precipitation material comprising calcium carbonate and a supernatant aqueous solution wherein the precipitation material and the supernatant aqueous solution comprise residual ammonium salt; and c) removing and optionally recovering ammonia and/or ammonium salt using one or more steps of (i) recovering a gas exhaust stream comprising ammonia during the treating and/or the contacting step; (ii) recovering the residual ammonium salt from the supernatant aqueous solution; and (iii) removing and optionally recovering the residual ammonium salt from the precipitation material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Experimental and numerical study of the effects of solution concentration and temperature on concrete under external sulfate attack

The work reports on an experimental programme, conducted to validate comprehensively our previously proposed coupled chemo-transport model for external sulfate attack on concrete. Specifically, the effects of the concentration of sulfate solution and temperature on the distribution of sulfate ions in concrete are experimentally investigated and used to demonstrate the accuracy of the modeling framework. Further, the profile of aluminate depletion and the leaching depth numerically are investigated. For all cases the model predictions are in good agreement with the experimental results, showing increases of the concentration of sulfate ions in concrete with higher concentrations of sulfate solution and higher temperatures. It is concluded that higher sulfate solution concentration and temperature enhance the processes involved in the external sulfate attack on concrete, namely diffusion of sulfate ions and their chemical reactions with concrete. It is found that these parameters affect the external sulfate attack predominantly via the chemical reaction process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward

The inevitable presence of uncertain parameters in critical applications of process optimization can lead to undesirable or infeasible solutions. For this reason, optimization under parametric uncertainty was, and continues to be a core area of research within Process Systems Engineering. Multiparametric programming is a strategy that offers a holistic perspective for the solution of this class of mathematical programming problems. Specifically, multiparametric programming theory enables the derivation of the optimal solution as a function of the uncertain parameters, explicitly revealing the impact of uncertainty in optimal decision-making. By taking advantage of such a relationship, new breakthroughs in the solution of challenging formulations with uncertainty have been created. Apart from that, researchers have utilized multiparametric programming techniques to solve deterministic classes of problems, by treating specific elements of the optimization program as uncertain parameters. In the past years, there has been a significant number of publications in the literature involving multiparametric programming. The present review article covers recent theoretical, algorithmic, and application developments in multiparametric programming. Additionally, several areas for potential contributions in this field are discussed, highlighting the benefits of multiparametric programming in future research efforts.

Pappas, Iosif↗