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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 199 records · Page 11

A physically based mechanical model for Mullins effect in thermoplastic polyurethanes

Despite decades of research, connecting the chemical and physical structure of thermoplastic polyurethanes to their mechanical properties remains highly challenging. Of particular note are their large-deformation and rate-dependent behaviors, which vary greatly with molecular chemistry, including the type and relative content of soft and hard segments. In this work, we develop a physically motivated mechanical theory for predicting the behavior of thermoplastic polyurethanes. The theory incorporates a representation of microstructural evolution during mechanical deformation, which captures the signatures of stress softening over cyclic loading (commonly referred to as the Mullins effect). There are only eight physically motivated fitting parameters, including a direct dependence on the hard segment fraction. The model predicts that increasing the hard segment fraction leads to higher stiffness and greater energy dissipation, in quantitative agreement with published experimental data. Furthermore, we provide a comprehensive analysis of the model and validate its predictions across several independent datasets focused on mechanical characterization. Direct comparisons to experimental data demonstrate its predictive capability on the effect of loading rate, cyclic deformations, and applied tension or compression. Altogether, this work establishes a predictive framework that connects polymer chemistry and microstructure to emergent mechanical behaviors.

36 MATERIALS SCIENCE↗

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Abstract Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

36 MATERIALS SCIENCE↗

Separation of Kondo lattice coherence from crystal electric field in CeIn 3 with Nd substitutions

The Ce m M n In 3m+2n (m=1,2;n=0,1) family has been one of the most studied families of heavy fermion compounds. This family has revealed many interesting low-temperature physics phenomena, like quantum critical points, heavy fermion superconductivity, and non-Fermi liquid behavior, when these materials are exposed to pressure, magnetic fields, and/or chemical substitution. In this work, we provide a thorough investigation of the Ce 1-x Nd x In 3 phase diagram through single crystal synthesis, x-ray diffraction, energy-dispersive spectroscopy, magnetic susceptibility, and electrical resistivity measurements. Previous electrical resistivity measurements on CeIn 3 reveal a broad maximum, T max ~50 K, which has been associated with the Kondo lattice coherence crossover and/or the crystal electric field depopulation effect as the 4f electrons condense from the high-energy quartet down to the ground state doublet. Our findings show that in the most disordered substitution region, x=0.4–0.5, these features disjoin to reveal two distinct broad humps in electrical resistivity measurements. Magnetic susceptibility and electrical resistivity data on Ce 1-x Nd x In 3 also reveal the antiferromagnetic ordering competition between CeIn 3 and NdIn 3 , where the T N of CeIn 3 is linearly suppressed to a critical concentration of x Nd ~0.6. This concentration is slightly lower than what was previously reported in nonmagnetically substituted Ce 1-x La x In 3 . Our magnetic susceptibility measurements and subsequent simulations show that in the CeIn 3 antiferromagnetic regime, x Nd ≤0.4, the Nd ions act as free paramagnets. The large magnitude of the associated paramagnetic response then masks the overlapping antiferromagnetic ordering signature of the Ce ions. Overall our study further sheds light on the underlying crystal electric field and Kondo lattice coherence interactions within the Ce m M n In 3m+2n family and could stimulate further studies of these systems via neutron diffraction or under applied pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

From wide to ultrawide-bandgap semiconductors for high power and high frequency electronic devices

Abstract Wide and ultrawide-bandgap (U/WBG) materials have garnered significant attention within the semiconductor device community due to their potential to enhance device performance through their substantial bandgap properties. These exceptional material characteristics can enable more robust and efficient devices, particularly in scenarios involving high power, high frequency, and extreme environmental conditions. Despite the promising outlook, the physics of UWBG materials remains inadequately understood, leading to a notable gap between theoretical predictions and experimental device behavior. To address this knowledge gap and pinpoint areas where further research can have the most significant impact, this review provides an overview of the progress and limitations in U/WBG materials. The review commences by discussing Gallium Nitride, a more mature WBG material that serves as a foundation for establishing fundamental concepts and addressing associated challenges. Subsequently, the focus shifts to the examination of various UWBG materials, including AlGaN/AlN, Diamond, and Ga 2 O 3 . For each of these materials, the review delves into their unique properties, growth methods, and current state-of-the-art devices, with a primary emphasis on their applications in power and radio-frequency electronics.

Materials Science↗

Tailoring physical properties of crystals through synthetic temperature control: A case study for new polymorphic NbFeT e 2 phases

Growth parameters play a significant role in the crystal quality and physical properties of layered materials. Here we present a case study on a van der Waals magnetic NbFeTe 2 material. Two different types of polymorphic NbFeTe 2 phases, synthesized at different temperatures, display significantly different behaviors in crystal symmetry, electronic structure, electrical transport, and magnetism. While the phase synthesized at low temperature showing behavior consistent with previous reports, the new phase synthesized at high temperature, has completely different physical properties, such as metallic resistivity, long-range ferromagnetic order, anomalous Hall effect, negative magnetoresistance, and distinct electronic structures. Neutron diffraction reveals out-of-plane ferromagnetism below 70 K, consistent with the electrical transport and magnetic susceptibility studies. Finally, our work suggests that simply tuning synthetic parameters in a controlled manner could be an effective route to alter the physical properties of existing materials potentially unlocking new states of matter, or even discovering new materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗

Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber‘s characteristics and biocomposite‘s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young‘s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

36 MATERIALS SCIENCE↗

Colloidal Gelation-2 and Colloidal Disorder-Order Transition-2 Investigations Conducted on STS-95

The Colloidal Gelation-2 (CGEL 2) and Colloidal Disorder-Order Transition-2 (CDOT 2) investigations flew on Space Shuttle Discovery mission STS-95 (also known as the John Glenn Mission). These investigations were part of a series of colloid experiments designed to help scientists answer fundamental science questions and reduce the trial and error involved in developing new and better materials. Industries dealing with semiconductors, electro-optics, ceramics, and composites are just a few that may benefit from this knowledge. The goal of the CGEL 2 investigation was to study the fundamental properties of colloids to help scientists better understand their nature and make them more useful for technology. Colloids consist of very small (submicron) particles suspended in a fluid. They play a critical role in the technology of this country, finding uses in materials ranging from paints and coatings to drugs, cosmetics, food, and drink. Although these products are routinely produced and used, there are still many aspects of their behavior about which scientists know little. Understanding their structures may allow scientists to manipulate the physical properties of colloids (a process called "colloidal engineering") to produce new materials and products. Colloid research may even improve the processing of known products to enhance their desirable properties.

Hoffmann, Monica T.↗

Cluster-Spin-Glass Magnetic Behavior and Morphology in the Coordination Polymer Alloys Fe y Co 1– y BTT

We report the synthesis of a series of pseudo-1D coordination polymer (CP) materials with the formula Fe y Co 1–y BTT (BTT = 1,3,5-benzenetrithiolate). These materials were structurally characterized by PXRD Rietveld, EXAFS, and PDF analyses, revealing that the CP superstructure enables a continuous and isomorphous alloy between the two homometallic compounds. Lower Fe loadings exhibit emergent spin glass magnetic behavior, such as memory effects and composition-dependent spin glass response time constants ranging from 6.9 × 10 –9 s to 1.8 × 10 –6 s. These data are consistent with the formation of spin clusters within the lattice. The magnetic behavior in these materials was modeled via replica exchange Monte Carlo simulation, which provides a good match for the experimentally measured spin glassing and magnetic phase transitions. Furthermore, these findings underscore how the rigid superstructure of CP and MOF scaffolds can enable the systematic tuning of physical properties, such as the spin glass behavior described here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microscopic Imprints of Learned Solutions in Tunable Networks

In physical networks trained using supervised learning, physical parameters are adjusted to produce desired responses to inputs. An example is an electrical contrastive local learning network of nodes connected by edges that adjust their conductances during training. When an edge conductance changes, it upsets the current balance of every node. In response, physics adjusts the node voltages to minimize the dissipated power. Learning in these systems is therefore a coupled double-optimization process, in which the network descends both a cost landscape in the high-dimensional space of edge conductances and a physical landscape—the power dissipation—in the high-dimensional space of node voltages. Because of this coupling, the physical landscape of a trained network contains information about the learned task. Here, we derive a structure-function relation for trained tunable networks and demonstrate that all the physical information relevant to the trained input-output relation can be captured by a tuning susceptibility, an experimentally measurable quantity. We supplement our theoretical results with simulations to show that the tuning susceptibility is correlated with functional importance and that we can extract physical insight into how the system performs the task from the conductances of highly susceptible edges. Our analysis is general and can be applied directly to mechanical networks, such as networks trained for protein-inspired function such as allostery.

36 MATERIALS SCIENCE↗

Frictional and Lithological Controls on Shallow Slow Slip at the Northern Hikurangi Margin

Slow slip events (SSEs) have been identified at subduction zones globally as an important link in the continuum between elastodynamic ruptures and stable creep. The northern Hikurangi margin is home to shallow SSEs which propagate to within 2 km of the seafloor and possibly to the trench, providing insights into the physical conditions conducive to SSE behavior. We report on a suite of friction experiments performed on protolith material entering the SSE source region at the Hikurangi margin, collected during the International Ocean Discovery Program Expedition 375. We performed velocity stepping and slide-hold-slide experiments over a range of fault slip rates, from plate rate (5 cm/yr or 1.6 × 10 –9 m/s) to ~1 mm/s (10 –3 m/s) and quantified the frictional velocity dependence and healing rates for a range of lithologies atdifferent stresses. The frictional velocity dependence (a-b) and critical slip distance DC increase with fault slip rate in our experiments. We observe atransition from velocity weakening to strengthening at slip rates of ~0.3 µm/s. This velocity dependence of DC could be due to a combination of dilatant strengthening and a widening of the active shear zone at higher slip rates. We document low healing rates in the clay-rich volcaniclastic conglomerates, which lie above the incoming plate basement at least locally, and relatively higher healing rates in the chalk lithology. Finally, our experimental constraints on healing rates in different input lithologies extrapolated to timescales of 1–10 years are consistent with the geodetically inferred low stress drops and healing rates characteristic of the Hikurangi SSEs.

58 GEOSCIENCES↗

Investigating the mechanism of copper–carbon interactions in ultraconductor materials via in situ thermal X-ray and Raman spectroscopy

Improving energy transfer efficiency is critical to advancing technologies for a more sustainable future. Nanoscale materials, specifically metal–carbon composites such as ultraconductors, have shown promise in this field due to their enhanced electrical and thermal conductivities. However, the origin of the enhancement has yet to be determined. Prior research has primarily explored these materials at room temperature in an attempt to explain this phenomenon, but these materials have not yet been examined under enhanced thermal conditions. This study probes ultraconductor materials during the heating process to uncover the origins of their enhanced thermal conductivity. Understanding the mechanism underpinning the enhanced properties of the material could lead to increased property enhancement and therefore improved performance in energy transfer technologies. In this work we employ in situ thermal X-ray absorption near edge spectroscopy (XANES) and Raman spectroscopy to characterize copper-based covetic materials, revealing how thermal conditions influence the bonding environment and interaction between the copper and infused carbon. Our findings suggest that heating the materials does not result in the formation of chemical bonds between the carbon and copper framework of the material but rather points to a primarily physical interaction within the sample. Furthermore, we hypothesize possible mechanisms underlying the nature of the physical interaction leading to enhanced properties. These insights contribute to a deeper understanding of the material's behavior under relevant thermal conditions and highlight its potential for integration into next-generation energy systems.

36 MATERIALS SCIENCE↗

Low barrier height in a ZnO nanorods/NbSe 2 heterostructure prepared by van der Waals epitaxy

Two-dimensional (2D) materials as contacts for semiconductor devices have attracted much attention due to minimizing Fermi level pinning. Schottky–Mott physics has been widely employed to design 2D material-based electrodes and to elucidate their contact behavior. In this study, we revealed that charge transfer across a 2D/semiconductor heterointerface and materials characteristics besides work function should be accounted for in fabrication of electrodes based on 2D materials. Our density functional theory (DFT) calculations predicted that charge transfer between ZnO and NbSe 2 lowers the barrier height at the heterojunction and that conductive surface states of ZnO provide an additional conduction channel in the ZnO/NbSe 2 heterostructures. Crystalline ZnO/NbSe 2 heterostructures were prepared by the hydrothermal method. Electrical characterizations of the ZnO/NbSe 2 heterostructures showed Ohmic-like behavior as predicted by the DFT calculations, opposed to the prediction based on the Schottky–Mott model.

2D materials↗

Physics-based model of irradiation creep for ferritic materials under fusion energy operation conditions

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this paper, we develop a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. Here, we carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum with average recoil energies of 20 keV and a damage dose rate of ≈3×10 –7 dpa/s at temperatures between 300 and 800 K.

36 MATERIALS SCIENCE↗

Vulnerabilities in Artificial Intelligence and Machine Learning Applications and Data

Artificial intelligence (AI) applications driven by machine learning (ML) are transformational technologies within the international nuclear security regime. Advancements realized by AI—faster and improved data insights, more efficient and automated processes, reductions in human error—enable nuclear security applications such as behavior analysis for insider threat mitigation, source tracking of stolen nuclear material, and facial recognition software for physical protection. In addition to the advantages, however, there are also inherent vulnerabilities and threats associated with its use and risk mitigations must be built into any AI/ML-enabled systems. This work provides a background on AI and ML and different data types used in the field, including open-source intelligence information (OSINT) that is discoverable by AI tools and application data that are used by AI tools for decision-making and automation. Current and potential AI applications and vulnerabilities related to their use within the nuclear security regime are also discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Accelerated Aging Scoping Study of Additively Manufactured Coupons

Additive manufacturing (AM) is a relatively new technological advancement that allows for rapid prototyping, development of intricate shapes, and reduction in manufacturing time. The materials of interest for this project are Ultem 1010, ABS M30, FDM Nylon 12, PC, and PPSF. However, little is known regarding the aging behavior of these AM materials. The limited aging study outlined herein was designed to compare the chemical, physical, and mechanical properties of AM parts as they experience accelerated aging at 70 °C for a total of 24 weeks. In general, ABS M30 stood out as it appeared to undergo chemical and physical changes leading to increase in density and an overall more brittle material, making this commonly used material not attractive for long-term use.

36 MATERIALS SCIENCE↗

Chemistry of vaporization of refractory materials

A discussion is given of the principles of physical chemistry important in vaporization studies, notably the concepts of equilibrium, phase behavior, thermodynamics, solid solution, and kinetics. The important factors influencing equilibrium vaporization phenomena are discussed and illustrated. A proper course of a vaporization study consisting of 9 stages is proposed. The important experimental techniques of Knudsen effusion, Langmuir vaporization and mass spectrometry are discussed. The principles, the factors, the course of a study and the experimental techniques and procedures are illustrated by recent work on the Ti-O system.

Gilles, P. W.↗