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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Conservative remapping of material-dependent fields between possibly misaligned material regions

In this work, we propose an interpolation or remapping algorithm of material-dependent fields on polyhedral meshes where any source or target cell contains only one material. It is conservative and it preserves sharp material boundaries on the target mesh, even if the source and target regions delineating the same material are slightly misaligned. If those material regions are aligned, then the algorithm is also linearity-preserving and bounds-preserving. For a given material, it consists of a conservative field reconstruction on a target mesh part from a source mesh part associated with that material, followed by a repair step in case of misaligned boundaries. No assumption is made regarding the topology of the input meshes

36 MATERIALS SCIENCE↗
DOE OSTI2025

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.

chemistry↗
DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) 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 in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Zintl phases A In 2 As 2 (A = Ca, Sr, Ba): new topological insulators and thermoelectric material candidates

Recently, there has been a lot of interest in topological insulators (TIs), being electronic materials, which are insulating in their bulk but with the gapless exotic metallic state on their surface. The surface states observed in such materials behave as a perfect conductor thereby making them more suited for several cutting-edge technological applications such as spintronic devices. Here, we report the synthesis and structural characterization of the Zintl phases AIn 2 As 2 (A = Ca, Sr, Ba), which could become a new class of TIs. Crystal structure elucidation by single-crystal X-ray diffraction reveals that CaIn 2 As 2 and SrIn 2 As 2 are isostructural and crystallize in the EuIn 2 P 2 structure type (space group P6 3 /mmc, no. 194, Z = 2) with unit cell parameters a = 4.1482(6) Å, c = 17.726(4) Å; and a = 4.2222(6) Å, c = 18.110(3) Å, respectively. Their hexagonal structure is made up of alternating [In 2 As 2 ] 2– layers separated by slabs of A 2+ cations. BaIn 2 As 2 on the other hand crystallizes in the monoclinic EuGa 2 P 2 structure type (space group P2/m, no. 10, Z = 4) with unit cell parameters a = 10.2746(11) Å, b = 4.3005(5) Å, c = 13.3317(14) Å and β = 95.569(2)°. This structure is also layered, and it is made up of different type of polyanionic [In 2 As 2 ] 2– units and Ba 2+ cations. The valence electron count for all three compounds adheres to the Zintl-Klemm formalism, and all elements achieve closed-shell electronic configurations. Bulk electronic structure calculations indicate the opening of a bandgap E g ~ 0.03 eV (CaIn 2 As 2 and Sr 2 In 2 As 2 ), and E g ~0.21 eV (BaIn 2 As 2 ) in the absence of strain and spin–orbit coupling (SOC). Furthermore, these results argue in favor of the realization of a nontrivial topological insulator state under the influence of tensile strain and SOC. Preliminary transport properties on BaIn 2 As 2 are suggestive of a degenerate p-type semiconductor—a behavior which is sought after in thermoelectric (TE) materials. Since both TIs and excellent TE materials are known to favor the same material properties such as narrow bandgap, heavy elements, and strong SOC, these three Zintl phases are also projected as candidates TE materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Material Selection and Corrosion Studies of Candidate Bearing Materials for Use in Molten Chloride Salt

Molten chloride salts are being given strong consideration for use in heat transfer and storage in concentrating solar power (CSP) systems as well as in some nuclear reactor applications. Containment of the molten salt, particularly at the highest temperatures, is a major material concern and has received considerable study. Another material issue is the pumps that will be required to move the molten salt along with the bearing materials that will be required to have sufficient corrosion resistance as well as wear resistance in the high temperature salt. A pair of coordinated studies in our laboratory has addressed the corrosion, and the wear issues of candidate bearing materials including the selection of candidate materials as well as their performance in a molten sodium chloride-potassium chloride-magnesium chloride salt environment. This work addresses the selection of candidate materials and their chemical compatibility with the molten salt. The studies have identified material pairs that have suitable properties for use as bearings that would be immersed in molten chloride salt.

14 SOLAR ENERGY↗
DOE OSTI2023

Metal–Carbodithioate-Based 3D Semiconducting Metal–Organic Framework: Porous Optoelectronic Material for Energy Conversion

Solar energy conversion requires the working compositions to generate photoinduced charges with high potential and the ability to deliver charges to the catalytic sites and/or external electrode. These two properties are typically at odds with each other and call for new molecular materials with sufficient conjugation to improve charge conductivity but not as much conjugation as to overly compromise the optical band gap. In this work, we developed a semiconducting metal-organic framework (MOF) prepared explicitly through metal-carbodithioate"(-CS 2 ) n M" linkage chemistry, entailing augmented metal-linker electronic communication. The stronger ligand field and higher covalent character of metal-carbodithioate linkages-when combined with spirofluorene-derived organic struts and nickel-(II) ion-based nodes-provided a stable, semiconducting 3D-porous MOF, Spiro-CS 2 Ni. This MOF lacks long-range ordering and is defined by a flexible structure with non-aggregated building units, as suggested by reverse Monte Carlo simulations of the pair distribution function obtained from total scattering experiments. The solvent-removed "closed pore"material recorded a Brunauer-Emmett-Teller area of similar to 400m 2 /g, where the "open pore" form possesses90 wt % solvent-accessible porosity. Electrochemical measurements suggest that Spiro-CS 2 Ni possesses a band gap of 1.57 eV(sigma = 10 -7 S/cm at -1.3 V bias potential),which can be further improved by manipulating the d-electron configuration through an axial coordination (ligand/substrate), the latter of which indicates usefulness as an electrocatalyst and/or a photoelectrocatalyst(upon substrate binding). Transient-absorption spectroscopy reveals a long-lived photo-generated charge-transfer state (τ CR = 6.5 mu s) capable of chemical transformation under a biased voltage. Spiro-CS 2 Ni can endure a compelling range of pH(1-12 for weeks) and hours of electrochemical and photoelectrochemical conditions in the presence of water and organic acids. We believe this work provides crucial design principles for low-density, porous,light-energy-conversion materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Combining Chemistry, Material Science, Inspiration from nature, and Serendipity to Develop Stimuli-responsive Polymeric Materials

Neither of us can remember people talking about stimuli-responsive polymers when we were students. Even though this was still in the last century, it was almost 70 years after Staudinger's seminal paper "uber Polymerisation"![1] By the time we entered graduate school in the early 1990 s, the first papers on polymer light emitting diodes appeared, while research on electrically conducting, nonlinear optical, and other "functional" polymers was already in full swing. Looking back, there were some stimuli-responsive materials that were around at the time, but it took the better part of the last 30 years until the field had developed into what we think is one of the most vibrant areas of polymer science. Before the potential usefulness of this class of materials was recognized, researchers were focused on developing polymeric materials that would not respond to external influences, and in fact maintain (in particular) their mechanical properties in a wide range of environments. This has led to the development of many environmentally robust polymers, which have come to impact basically every aspect of our daily life. Ironically, this long-sought stability now comes back to haunt us in the form of plastic pollution, but this is another story. The concept of materials that adapt their properties in response to changing environmental conditions might appear like a complete reversal with respect to the original goals of creating stable materials. However, eventually a) it was recognized that materials that respond to a specific stimulus in a predictable and useful manner would significantly broaden the potential usefulness of polymers, and b) the field of polymer science had developed to the point where the rational design, preparation, and characterization of such materials became possible. The expression 'stimuli-responsive polymer' had been first used in the 1980's, however its use really only gained popularity a few decades later. In the early days, terms such as environmentally-sensitive or environmentally-responsive polymers, stimuli-reversible or stimuli-sensitive polymers, or polymers with phase transitions have also been used.

Rowan, Stuart J.↗
DOE OSTI2020

Viscoelastic Material Characterization and Modeling of Photovoltaic Module Packaging Materials for Direct Finite-Element Method Input

Numerical tools, such as the finite-element method, are increasingly used to design and evaluate the photovoltaic (PV) modules, providing for the reduction of development time and improved performance and reliability. However, high-fidelity material models are necessary to accurately model the complex structural behavior of the involved packaging materials. A common simplification used in recent years is to model the polymer materials (i.e., encapsulant and backsheet) as linear elastic, which will lead to inaccurate results. Therefore, in this work, we present a thorough characterization of the time- and temperature-dependent mechanical response of predominant PV module encapsulant and backsheet materials. Based on this material characterization, we developed and experimentally validated generalized Maxwell models to describe each material's viscoelastic response. In addition, we included measurements of the coefficient of thermal expansion and presented all material models in such a fashion for direct input into commercial finite-element method modeling software.

FEM↗
DOE OSTI2024

In-Silico Analysis of High Refractive Index Materials Through Principles of Materials Design

The intent of the paper is to use specific principles of Materials Design that were developed and applied in the electronics industry for enabling understanding and design of improved high refractive index materials. Further, by combining first-principle based ab-initio, semiempirical interatomic potential methods, and machine learning approaches in conjunction with experimental data, we identified specific determinants of high refractive index materials, which can be critically applied for informing materials design and accelerating discovery. Specifically, it was demonstrated that chalcogenides and perovskites as bulk materials can exhibit higher refractive indices with appropriate engineering of specific aspects of the materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Alternative Materials Literature Review: A Review of Alternative Materials for Xenon Capture in Comparison to AgZ-PAN

A collaborative literature review between Idaho National Laboratory (INL) and Pacific National Laboratory (PNNL) was conducted to research alternative metals/materials for xenon adsorption in gaseous effluents generated from used nuclear fuel (UNF) reprocessing. The review was conducted to research sorbents that could outperform silver mordenite (AgZ) at ambient temperature. The use of silver requires complex and expensive waste disposal processes due to it being an RCRA metal, therefore alternative materials need to be researched and evaluated. The report details two different types of sorbent material: alternative zeolite materials and non-zeolite-based materials (i.e., MOFs, COFs, etc.). This report documents a brief history of the materials, what testing has been conducted on them, and what results suggest the possibility of outperforming the silver-based materials. Sorbent performance characteristics such as durability, capacity, and operating temperatures were evaluated. The simplicity of the sorbents was also evaluated, meaning how they are acquired (synthesized vs. naturally abundant). Recommendations were made for the most promising sorbents based on available research in the subject area and these recommended sorbents will be tested in the upcoming fiscal year. The recommended sorbents that are zeolite based are CHA zeolites, ZIF-69, and Na-ETS-10. The recommended sorbents that are non-zeolite based are SBMOF-1 and CC3.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Self-accelerated corrosion of nuclear waste forms at material interfaces

The US plan for high-level nuclear waste includes the immobilization of long-lived radionuclides in glass or ceramic waste forms in stainless-steel canisters for disposal in deep geological repositories. Here we report that, under simulated repository conditions, corrosion could be significantly accelerated at the interfaces of different barrier materials, which has not been considered in the current safety and performance assessment models. Severe localized corrosion was found at the interfaces between stainless steel and a model nuclear waste glass and between stainless steel and a ceramic waste form. The accelerated corrosion can be attributed to changes of solution chemistry and local acidity/alkalinity within a confined space, which significantly alter the corrosion of both the waste-form materials and the metallic canisters. The corrosion that is accelerated by the interface interaction between dissimilar materials could profoundly impact the service life of the nuclear waste packages, which, therefore, should be carefully considered when evaluating the performance of waste forms and their packages. Moreover, compatible barriers should be selected to further optimize the performance of the geological repository system.

Guo, Xiaolei↗
DOE OSTI2023

A materials data framework and dataset for elastomeric foam impact mitigating materials

The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimization of Source Material for in-situ Arsenic Doping via Vapor Transport Deposition of CdTe Films

In-situ doping of CdTe/CdSeTe films with arsenic is performed using pre-doped source material prepared by high pressure Bridgman (HPB) melt growth. Arsenic level in the source material is varied from 1018-1020 cm-3. Correspondingly, dopant incorporation in the films prepared using vapor transport deposition (VTD) varied from 3x1017 cm-3–1x1018cm-3. In this range, dopant activation is found to inversely correlate with the dopant incorporation, suggesting compensation. The results from this study indicate film properties can be adjusted by source material.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Alternative Materials Literature Review: A Review of Alternative Materials for Xenon Capture in Comparison to AgZ-PAN

A collaborative literature review between Idaho National Laboratory (INL) and Pacific National Laboratory (PNNL) was conducted to research alternative metals/materials for xenon adsorption in gaseous effluents generated from used nuclear fuel (UNF) reprocessing. The review was conducted to research sorbents that could outperform silver mordenite (AgZ) at ambient temperature. The use of silver requires complex and expensive waste disposal processes due to it being an RCRA metal, therefore alternative materials need to be researched and evaluated. The report details two different types of sorbent material: alternative zeolite materials and non-zeolite-based materials (i.e., MOFs, COFs, etc.). This report documents a brief history of the materials, what testing has been conducted on them, and what results suggest the possibility of outperforming the silver-based materials. Sorbent performance characteristics such as durability, capacity, and operating temperatures were evaluated. The simplicity of the sorbents was also evaluated, meaning how they are acquired (synthesized vs. naturally abundant). Recommendations were made for the most promising sorbents based on available research in the subject area and these recommended sorbents will be tested in the upcoming fiscal year. The recommended sorbents that are zeolite based are CHA zeolites, ZIF-69, and Na-ETS-10. The recommended sorbents that are non-zeolite based are SBMOF-1 and CC3.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗