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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 253 records · Page 14

Chitosan as a Canvas for Studies of Macromolecular Controls on CaCO 3 Biological Crystallization

A mechanistic understanding of how macromolecules, typically as an organic matrix, nucleate and grow crystals to produce functional biomineral structures remains elusive. Advances in structural biology indicate that polysaccharides (e.g., chitin) and negatively charged proteoglycans (due to carboxyl, sulfate, and phosphate groups) are ubiquitous in biocrystallization settings and play greater roles than currently recognized. This review highlights studies of CaCO 3 crystallization onto chitinous materials and demonstrates that a broader understanding of macromolecular controls on mineralization has not emerged. With recent advances in biopolymer chemistry, it is now possible to prepare chitosan-based hydrogels with tailored functional group compositions. By deploying these characterized compounds in hypothesis-based studies of nucleation rate, quantitative relationships between energy barrier to crystallization, macromolecule composition, and solvent structuring can be determined. Finally, this foundational knowledge will help researchers understand composition-structure-function controls on mineralization in living systems and tune the designs of new materials for advanced applications.

15 GEOTHERMAL ENERGY↗

Unveiling 3D Morphology of Multiscale Micro-Nanosilver Sintering for Advanced Electronics Manufacturing by Ptychographic X-ray Nanotomography

The sintering processing–structure–property relationship of a multiscale silver materials is investigated: microparticles with nanofeatures, particularly on their three-dimensional (3D) morphology. The target application is to replace conventional lead-based solders in advanced electronic manufacturing. Unlike lead-based solders, silver powders are suited to satisfy increasingly demanding mechanical, electrical, and thermal requirements, meanwhile being free of health effect. Sintering the material at a low temperature and without applied pressure are desirable conditions, which results in a preferred use of silver nanoparticles, as nanofeatures have higher driving force to sinter with the decrease in particle size. However, nanosized powders present potential health/environmental effects. To address the trade-off between the benefits and shortcomings of nano-versus microparticles, this work studies a novel multiscale silver paste, namely micron-sized powders with nanosized features. To get quantitative 3D visualization of micro- and nanoscale features, ptychographic X-ray computed nanotomography is applied. The correlations between conditions (thermal aging, pressure, and substrate metallization), mechanical properties, and morphological parameters are established. Finally, using novel 3D X-ray nanoimaging technique, it is demonstrated that one can design multiscale materials while balancing complex demands required in advanced electronics manufacturing and research directions in materials design and characterization.

36 MATERIALS SCIENCE↗

FLASSH 1.0: Thermal scattering law evaluation and cross section generation for reactor physics applications

The Full Law Analysis Scattering System Hub (FLASSH) is a modern, advanced code which evaluates the thermal scattering law (TSL) along with accompanying cross sections. FLASSH features generalized methods which accommodate any material structure. Historical approximations including the incoherent and cubic approximations have been removed. Instead, the latest release of FLASSH features advanced physics options including distinct corrections (1-phonon contributions) and non-cubic formulations. The non-cubic elastic and inelastic contributions are necessary to accurately evaluate 1-phonon contributions. Both non-cubic and 1-phonon calculations require high-density sampling of the various scattering directions. Optimization and parallelization of these routines were therefore necessary to produce results in a reasonable timeframe. With these notable improvements to the generalized TSL, FLASSH 1.0 meets benchmark requirements, demonstrating noticeable agreement with experiment for both TSLs and the resulting integrated cross sections. Additional features including a graphical user interface (GUI), plotting diagnostics, and formatted output options including ACE files allow users to complete a TSL evaluation with minimal input and maximum flexibility. The user GUI creates input files for FLASSH, reducing user error and also providing built-in error checks. Autofill options and suggested input values help make TSL evaluation accessible to novice users. The FLASSH code is compiled to run on both Windows and Linux platforms with automatic parallelization. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Influence of post deposition annealing on the microstructural evolution and tensile behavior of austenitic stainless-steel alloy 709 made by laser powder bed fusion

Structural materials used in the next generation nuclear reactors or other advanced energy systems are often required to withstand higher operating temperatures for a longer service life. Alloy 709 (A709), a Nb-containing and N-stabilized Fe-25Ni-20Cr austenitic stainless steel, has been recommended for high-temperature reactor constructions due to the better performance over the baseline Type 316H stainless steel. Here, in the current manuscript, for the first time, the microstructure evolution and tensile behavior of an A709 made by laser powder bed fusion (LPBF) is discussed. The as deposited and heat treated LPBF alloys are compared with a reference wrought alloy. Owing to the chemical segregation and a higher number of dislocations, the LPBF materials show a significantly higher density of precipitates formed during high temperature treatments when compared to the wrought samples. This is reflected when looking at the tensile properties, both at room and elevated temperatures, where LPBF samples show higher strengths compared to wrought materials.

36 MATERIALS SCIENCE↗

AI-assisted discovery of high-temperature dielectrics for energy storage

Abstract Electrostatic capacitors play a crucial role as energy storage devices in modern electrical systems. Energy density, the figure of merit for electrostatic capacitors, is primarily determined by the choice of dielectric material. Most industry-grade polymer dielectrics are flexible polyolefins or rigid aromatics, possessing high energy density or high thermal stability, but not both. Here, we employ artificial intelligence (AI), established polymer chemistry, and molecular engineering to discover a suite of dielectrics in the polynorbornene and polyimide families. Many of the discovered dielectrics exhibit high thermal stability and high energy density over a broad temperature range. One such dielectric displays an energy density of 8.3 J cc −1 at 200 °C, a value 11 × that of any commercially available polymer dielectric at this temperature. We also evaluate pathways to further enhance the polynorbornene and polyimide families, enabling these capacitors to perform well in demanding applications (e.g., aerospace) while being environmentally sustainable. These findings expand the potential applications of electrostatic capacitors within the 85–200 °C temperature range, at which there is presently no good commercial solution. More broadly, this research demonstrates the impact of AI on chemical structure generation and property prediction, highlighting the potential for materials design advancement beyond electrostatic capacitors.

25 ENERGY STORAGE↗

Nanoparticle localization within chiral liquid crystal defect lines and nanoparticle interactions

Self-assembly of colloidal particles into predefined structures is a promising way to design inexpensive manmade materials with advanced macroscopic properties. Doping of nematic liquid crystals (LCs) with nanoparticles has a series of advantages in addressing these grand scientific and engineering challenges. It also provides a very rich soft matter platform for the discovery of unique condensed matter phases. The LC host naturally allows the realization of diverse anisotropic interparticle interactions, enriched by the spontaneous alignment of anisotropic particles due to the boundary conditions of the LC director. Here we demonstrate theoretically and experimentally that the ability of LC media to host topological defect lines can be used as a tool to probe the behavior of individual nanoparticles as well as effective interactions between them. LC defect lines irreversibly trap nanoparticles enabling controlled particle movement along the defect line with the use of a laser tweezer. Minimization of Landau–de Gennes free energy reveals a sensitivity of the ensuing effective nanoparticle interaction to the shape of the particle, surface anchoring strength, and temperature, which determine not only the strength of the interaction but also its repulsive or attractive character. Theoretical results are supported qualitatively by experimental observations. Furthermore, this work may pave the way toward designing controlled linear assemblies as well as one-dimensional crystals of nanoparticles such as gold nanorods or quantum dots with tunable interparticle spacing.

36 MATERIALS SCIENCE↗

Modularization of Ceramic Hollow Fiber Membrane Technology for Air Separation

This proposed project is aimed at studying high performance and economically competitive ceramic membrane technology for air separation and high-purity oxygen production using hollow fiber ceramic membrane stack and module technology. The design of the single permeate membrane is a hollow fiber substrate-supported thin tri-layer structure. Radially well-aligned micro-channels are embedded in the thick substrate and open at the inner surface of the substrate, enabling facile air/gas diffusion. The tri-layer structure of thin dense membrane layer (~ 10 µm) sandwiched by porous surface layer on either side is then built on the substrate using advanced fabrication process. The tri-layer structure design allows different materials to be used in different layers, where the materials of surface layers have high surface exchange coefficients while the material of dense layer has high bulk diffusivity. Such a synergetic combination leads to high permeation performance. The focus of the proposed project will be on membrane stack/module development using the developed single hollow fiber membranes, including: 1) fabrication and characterization of novel single hollow fiber membranes; 2) membrane stack design and assembly using fabricated single membranes; 3) stack modeling and analysis to guide membrane stack designs; 4) permeation performance testing and characterization of membrane stacks. The hollow fiber feature and simple sealing requirement enable very compact design of membrane stacks, which have excellent flexibility for further modularizations at different scales. The operations of such membrane stack and module may employ the exhaust heat from other components of Integrated Gasification Combined Cycle and oxy-combustion systems. Therefore, modularization of such an air separation membrane technology can be incorporated into the DOE’s REMS (radically engineered modular systems)-gasification skid and support the oxidant feed of an oxygen-blown REMS gasifier scaled to different ranges.

01 COAL, LIGNITE, AND PEAT↗

MXene-Based Porous Monoliths

In the past decade, a thriving family of 2D nanomaterials, transition-metal carbides/nitrides (MXenes), have garnered tremendous interest due to its intriguing physical/chemical properties, structural features, and versatile functionality. Integrating these 2D nanosheets into 3D monoliths offers an exciting and powerful platform for translating their fundamental advantages into practical applications. Introducing internal pores, such as isotropic pores and aligned channels, within the monoliths can not only address the restacking of MXenes, but also afford a series of novel and, in some cases, unique structural merits to advance the utility of the MXene-based materials. Here, a brief overview of the development of MXene-based porous monoliths, in terms of the types of microstructures, is provided, focusing on the pore design and how the porous microstructure affects the application performance.

2D nanomaterials↗

Effect of Part Size, Displacement Rate, and Aging on Compressive Properties of Elastomeric Parts of Different Unit Cell Topologies Formed by Vat Photopolymerization Additive Manufacturing

Due to its ability to achieve geometric complexity at high resolution and low length scales, additive manufacturing (AM) has increasingly been used for fabricating cellular structures (e.g., foams and lattices) for a variety of applications. Specifically, elastomeric cellular structures offer tunability of compliance as well as energy absorption and dissipation characteristics. However, there are limited data available on compression properties for printed elastomeric cellular structures of different designs and testing parameters. In this work, the authors evaluate how unit cell topology, part size, the rate of compression, and aging affect the compressive response of polyurethane-based simple cubic, body-centered, and gyroid structures formed by vat photopolymerization AM. Finite element simulations incorporating hyperelastic and viscoelastic models were used to describe the data, and the simulated results compared well with the experimental data. Of the designs tested, only the parts with the body-centered unit cell exhibited differences in stress–strain responses at different part sizes. Of the compression rates tested, the highest displacement rate (1000 mm/min) often caused stiffer compressive behavior, indicating deviation from the quasi-static assumption and approaching the intermediate rate response. The cellular structures did not change in compression properties across five weeks of aging time, which is desirable for cushioning applications. This work advances knowledge on the structure–property relationships of printed elastomeric cellular materials, which will enable more predictable compressive properties that can be traced to specific unit cell designs.

36 MATERIALS SCIENCE↗

Materials in Extremes [Slides]

Goals: Realization of advanced predictive models that capture aspects of processing structure-properties-performance (PSPP) in ways that build on scale bridging, data science, and transformational physics insights from experiments; Based on a robust and seamless integration of sample manufacturing, characterization (pre- and post-mortem), theory and simulation, and novel experiments; Ultimately we want to be able to reliably predict performance, and control the functionality of materials in extreme environments.

36 MATERIALS SCIENCE↗

Machine learning potential assisted exploration of complex defect potential energy surfaces

Abstract Atomic-scale defects generated in materials under both equilibrium and irradiation conditions can significantly impact their physical and mechanical properties. Unraveling the energetically most favorable ground-state configurations of these defects is an important step towards the fundamental understanding of their influence on the performance of materials ranging from photovoltaics to advanced nuclear fuels. Here, using fluorite-structured thorium dioxide (ThO 2 ) as an exemplar, we demonstrate how density functional theory and machine learning interatomic potential can be synergistically combined into a powerful tool that enables exhaustive exploration of the large configuration spaces of small point defect clusters. Our study leads to several unexpected discoveries, including defect polymorphism and ground-state structures that defy our physical intuitions. Possible physical origins of these unexpected findings are elucidated using a local cluster expansion model developed in this work.

36 MATERIALS SCIENCE↗

Metastable Materials Discovery in the Age of Large-Scale Computation

Computational materials discovery has been successful in predicting novel, technologically relevant materials. However, it has remained focused almost exclusively on finding ground-state structures. Now that the lower-hanging fruit has been found in many fields of application, materials exploration is moving toward metastable materials: higher energy phases that are stable at practical time scales. Because of the challenges associated with predicting which phases are realistic, this class of materials has remained relatively unexplored, despite numerous examples of metastable structures with unmatched properties (e.g., diamond). This article highlights recent advances in developing computational and theoretical methods for predicting useful and realizable metastable materials. Topics discussed cover (1) the latest strategies for identifying potential metastable phases, (2) methodologies for assessing which phases can be realized experimentally, and (3) current approaches to estimate the lifetime of metastable materials.

amorphous materials↗

Pressure‐Induced Structural and Optoelectronic Modulations in 2D Dion‐Jacobson Hybrid Lead Iodide Perovskites With a Rigid Spacer

2D hybrid organic-inorganic perovskites (HOIPs) are known for their superior chemical and thermal stability over 3D variants, positioning them as promising materials for advanced optoelectronic applications. Applying external high pressure is an effective strategy to modify their structures and tune their optoelectronic properties. This study examines the high-pressure behavior of a Dion-Jacobson type 2D HOIP, DPDAPbI 4 , which incorporates the rigid organic spacer N,N-dimethylphenylene-p-diammonium (DPDA). Utilizing photoluminescence, UV–visible absorption, vibrational spectroscopy, and in situ synchrotron powder X-ray diffraction, an isostructural phase transition is identified near 1.5 GPa, marked by a notable shift in photoluminescence intensity linked to free exciton emission. Synchrotron X-ray diffraction reveals significant anisotropic compression along the c-axis, while structural analysis indicates the rare phenomenon of reduced lead-iodide octahedral distortion below 2 GPa, contrasting with the increased octahedral distortion reported in most previous studies on lead-based 2D HOIPs. Density functional theory calculations elucidate the structural origins and mechanisms driving the pressure-induced phase transition and optoelectronic tuning. These findings underscore the critical interplay between rigid organic spacers and inorganic octahedra in modulating high-pressure optoelectronic properties, offering valuable insights for designing future 2D HOIPs with tailored functionalities.

14 SOLAR ENERGY↗

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↗

A multimodal large language model for materials science

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.

Tang, Yingheng [Lawrence Berkeley National Laborat↗

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Characterization and Analytical Technique↗

Emerging Modification Technologies of Lignin-based Activated Carbon toward Advanced Applications

Lignin-based activated carbon (LAC) is a promising high-quality functional material due to high surface area, abundant porous structure, and various functional groups. Modification is the most important step to functionalize LAC by altering its porous and chemical properties. Here, this Review summarizes the state-of-the-art modification technologies of LAC toward advanced applications. Promising modification approaches are reviewed to display their effects on the preparation of LAC. The multiscale changes in the porosity and the surface chemistry of LAC are fully discussed. Advanced applications are then introduced to show the potential of LAC for supercapacitor electrode, catalyst support, hydrogen storage, and carbon dioxide capture. Finally, the mechanistic structure-function relationships of LAC are elaborated. These results highlight that modification technologies play a special role in altering the properties and defining the functionalities of LAC, which could be a promising porous carbon material toward industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanical behaviour of additively manufactured metals

Additive manufacturing is reshaping the production of engineering components in diverse industries, such as the automotive, aerospace, defense, and biomedical sectors, by offering unprecedented design flexibility. The non-equilibrium processing conditions of additive manufacturing generate materials with unique microstructures and tailored mechanical properties that are often unattainable through conventional routes. This review focuses on recent advances in additively manufactured metals that demonstrate distinctive mechanical behaviors, including strength-ductility synergy, microstresses and gradient plasticity, fracture and fatigue resistance, and high-temperature creep performance. Here, we examine the mechanisms and micromechanical effects arising from the heterogeneous microstructures fabricated by additive manufacturing, to guide the design of a wide range of high-performance structural materials. Furthermore, we discuss critical research needs and emerging opportunities in process control, alloy design, advanced characterization, high-fidelity computational modeling, and machine learning aimed at achieving exceptional mechanical properties in additively manufactured metals.

Additive Manufacturing↗