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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unraveling the Atomic Mechanism of the Crystalline Phase‐Dependent Structural Features and Special Spectral Design of α‐, β‐, and Ɛ‐Ga₂O₃

Atomic‐scale phase transformations profoundly influence the functional properties of Ga₂O₃ polymorphs. By combining irradiation experiments with microstructure characterization and theoretical approaches, phase‐specific energy‐dissipation pathways in α‐, β‐, and ε‐Ga₂O₃ are uncovered and strategies for targeted property design are outlined. Competing antiphase boundaries (APBs) and twin domain boundaries (TDBs) promote irreversible α→ε interconversion through domain fragmentation. In β‐Ga₂O₃, defect‐induced stress gradients drive two distinct local transformations: surface Ga‐aggregated β→δ that stabilizes transient states, and latent‐track‐confined β→κ phase transition with recoverable distortions via cation reordering. Under electronic excitation, β‐Ga₂O₃ forms nanohillocks via robust GaO₆ octahedra (high density/strong Ga─O bonds), while α/ε‐Ga₂O₃ generates nanopores from tetrahedral Ga looseness (low bonding energy), highlighting phase‐dependent surface dynamics shaped by atomic packing and bonding anisotropy. Defect‐regulated recombination suppresses visible photoluminescence in α/β‐Ga₂O₃, whereas in ε‐Ga₂O₃ bandgap narrowing of ΔE: 0.30 eV is observed, enhancing emission. Linking phase‐dependent defect‐carrier interactions and metastable‐phase engineering in Ga₂O₃ enables property optimization for power‐electronics and optoelectronics devices.

electronic state configuration↗
DOE OSTI2022

Effect of post-extrusion heat treatment on mechanical property of aluminum alloy 2024 tube produced using Shear Assisted Processing and Extrusion (ShAPE)

The present work deals with the Shear Assisted Processing and Extrusion (ShAPE) of aluminum alloy 2024 tubes and mechanical property optimization via post extrusion heat treatments (T3510 and T8510). The ShAPE process enables extruding AA2024 at an extrusion speed of 7.4 m/min and extrusion temperature of 480 °C, which is otherwise beyond the extrudability limit of this alloy using conventional extrusion techniques. The ultimate tensile strength reaches 466 MPa for ShAPE+T3510 condition and 503 MPa for ShAPE+T8510 condition, both of which exceed the corresponding ASTM/ASM (minimum/typical) values for the studied tube geometry. The yield strength reaches 382 MPa for ShAPE+T3510 condition and 481 MPa for ShAPE+T8510 condition, both of which surpass any reported values in the literature or the highest industrial values. In addition, the ductility of AA2024 tube fabricated from ShAPE+T3510 or ShAPE+T8510 are evidently improved by the grain size refinement, second phase refinement, and enhanced uniformity in second phase distribution due to the severe plastic deformation of ShAPE process.

Shear Assisted Processing and Extrusions (ShAPE), ↗
DOE OSTI2022

Phase Stability Through Machine Learning

Understanding the phase stability of a chemical system constitutes the foundation of materials science. Knowledge of the equilibrium state of a system under arbitrary thermodynamic conditions provides valuable information about the types of phases that are likely to be synthesized and how to get there. Accessing the phase diagram in a materials system provides one with the information necessary to design materials and microstructures with optimal properties. While the materials science community has long been focused on exploiting this knowledge to navigate the materials space, recent advances in machine learning (ML) and artificial intelligence (AI) have provided the community with novel ways of interrogating the materials thermodynamics space. Furthermore, this work presents some of the most recent advances in ML/AI applied to phase stability and thermodynamics of materials. Prof. John Morral always had a passion for understanding and teaching the fundamental characteristics of phase diagrams. This review is written to honor his memory.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phase Relationships in the Carbon–Titanium–Uranium System for Ultra-High Temperature Nuclear Fuels

Carbides of uranium have attracted interest as fuels for nuclear thermal propulsion (NTP) to drive deep-space exploration owing to their attractive thermal and neutronic properties. Optimization of NTP technology, however, requires ultra-high temperature reactor environments to maximize the ratio of thrust to propellant to achieve peak rocket engine efficiency. Incorporation of transition metals into uranium carbides offers a pathway to increase the melting point of carbide fuels to address the operational challenges posed by NTP. Here, a thermodynamic model has been developed to examine the phase relationships in the C–Ti–U system at NTP conditions. Calculated phase relationships at ultra-high temperatures predict a stable (U, Ti)C solid solution. Additionally, experimental work on C–Ti–U synthesis via arc melting has been carried out, providing data on phase constitution and compositions that can be used to further refine the thermodynamic model that has been developed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Rules for the crystallite size and dislocation density evolution in phases during α-ω transformation in Zr under high-pressure and severe plastic flow

The first in-situ X-ray diffraction (XRD) study of the evolution of the crystallite size and dislocation density in phases during plastic strain-induced phase transformation (PT) is performed utilizing α-ω PT in strongly pre-deformed commercially pure Zr as an important example. Rough diamond anvils (rough-DA) are introduced to intensify all occurring processes during heterogeneous compression of Zr in a diamond anvil cell (DAC). The main rule is found that during α-ω PT the crystallite size and dislocation density in ω-Zr depend solely on the volume fraction of ω-Zr and are independent of pressure, plastic strain tensor, its path, and initial nanostructure. Crystallite size in ω-Zr increases from 10 to 60 nm during the PT, while dislocation density reduces from 1.83×10 15 /m 2 to 0.6×10 15 /m 2 . Rough-DA produce a steady nanostructure in α-Zr before PT with smaller crystallite size and larger dislocation density than smooth-DA, leading to a reduction of the minimum pressure for α-ω PT to a record value 0.67 GPa, 9 times smaller than under hydrostatic loading and 5.1 times lower than the phase equilibrium pressure. In addition to strain, the kinetics of strain-induced PT unexpectedly depends on time. Also, strain-controlled part of kinetics is zero order, in contrast to the first-order kinetics with smooth-DA. The obtained results open a new window for understanding the mutual effects of nanostructure evolution and PT during severe plastic flow in various technological and natural processes. In conclusion, they may bring up economic strategies of producing nanocomposites and single-phase nanostructured materials with optimal properties.

Crystalline size↗
DOE OSTI2020

Spark plasma sintering (SPS) densified U 3 Si 2 pellets: Microstructure control and enhanced mechanical and oxidation properties

Dense U 3 Si 2 pellets with controlled grain structure and enhanced thermal-mechanical and oxidation properties are synthesized with spark plasma sintering (SPS). Microstructure and phase composition of the SPS densified pellets are characterized systematically using SEM, EDS, and XRD. Thermal-mechanical properties and oxidation behavior of the sintered silicide fuel pellets are analyzed by laser flash, indentation, and dynamic thermogravimetric analysis. Dense U 3 Si 2 pellets are consolidated by combining high energy ball milling and rapid sintering by SPS, and the microstructure structures are controlled from micron-sized (~5.7 μm grain size) for conventional silicide to a nanocrystalline matrix with an average grain size of ~280 nm. A dominant phase of distorted U 3 Si 2 was identified with lattice expansion due to residual thermal stress upon SPS consolidation and rapid cooling processes. Both micron-sized and nano-sized pellets show exceptional thermal transport properties, consistent with monolithic silicides reported in literature. The SPS-densified pellets possess simultaneously high hardness and fracture toughness. The SPS-densified silicide pellets also demonstrate exceptional oxidation performance with extended onset oxidation temperature above 500 °C and reduced oxidation kinetics, particularly for nano-sized pellets. A strong strain effect was proposed in which compressive stress in nano-sized pellets enhances the oxidation resistance of silicide fuels, as evidenced by the degradation of oxidation performance upon strain relaxation by isothermal annealing. The correlation among the sintering process – microstructure control – physical properties and fuel behavior is established. A new concept of strain engineering is proposed further properties optimization, enabling the development of potential oxidation and corrosion-resistant silicides with extended performance, the key technological challenge of U 3 Si 2 as the leading concept of accident tolerant fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Performance of hybridized bamboo-carbon fiber reinforced polypropylene composites processed using wet laid technique

The end-of-life vehicles (ELV) regulations motivate hybrid materials usage in automotive industries to optimize properties at reduced cost and increase eco-friendly designs. This research explores hybrid compositions of natural bamboo fiber and synthetic carbon fiber. The goal of hybridization was to synergistically benefit from each constituent– i.e., sustainability, energy absorption and superior damping from bamboo, and high strength and stiffness from carbon fiber. Carbon fibers (CF), bamboo fibers (BF) and polypropylene (PP) fibers were dispersed in water to produce wet-laid hybrid mats. The mats were compression molded into consolidated panels to obtain the hybrid composite(s) (BF-CF-PP). Four formulations with different fiber-resin weight percent were designed and produced including- BF-PP (30/70), BF-PP (50/50), BF-CF-PP (32/8/60), and BF-CF-PP (8/32/60). The effect of (a) fiber length, (b) surface treatment, (c) fiber content, and (d) consolidation pressure on the mechanical properties were examined. The improved mechanical (flexural strength 76.4 MPa, flexural modulus 4.1 GPa, ILSS 12.4 MPa and impact strength 49.9 KJ/m 2 ) and vibrational damping (1.05%) properties showed that the BF-CF-PP (8/32/60) provided higher properties compared to the other variants. The projected properties at various stoichiometric ratios of carbon and bamboo fiber revealed that the properties of hybrid composites could be tailored to produce desirable, cost-effective, and sustainable automotive components.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In-situ measurement and control of the tool-workpiece interface temperature during friction stir processing of 304/304L stainless steel

Friction stir processing of 304/304L stainless steel is an area of interest for repair of spent nuclear fuel canisters. To enable repair without canister deflection or fracture, it is necessary to define the limitations for the depth of the processing zone which will be critically dependent on the thermal history of the material. Here, this work provides the first direct measurement of the interface temperature for friction stir processing of steel. The measured temperature is in the range of 850–1050 °C which is 20–30 % higher than previously reported values. Notably, the peak temperature occurs at the pin tip which is attributed to a higher sticking fraction and subsequently higher strain rate near the tool axis of rotation. Furthermore, a clear correlation between the temperature, grain size, and hardness is established within a single weld nugget and across different processing conditions. In the future, this data may lead to improved process modelling through direct validation and allow for property optimization through direct microstructure control.

304 stainless steel↗
DOE OSTI2024

Tuning austenite stability through prior microstructure control in a low-alloy Q&P steel

Quenching and partitioning (Q&P) processing is a widely accepted heat treatment methodology for creating high strength steels consisting of ferrite, martensite, and austenite, while maintaining relatively low manufacturing costs. Though the research on effects of prior microstructure is limited, an understanding of the heat treatment response of different starting microstructures is critical to processing and creating steels with complex microstructures that contain retained austenite and may afford opportunities to further optimize properties. This study investigates the influence of starting microstructure (ferrite/pearlite versus martensite) and prior levels of cold work (38 verses 58 %) on the microstructural development and mechanical properties of a 0.2 C-2.0 Mn-1.5 Si (wt.%) steel exposed to Q&P processing. Samples with a starting martensitic microstructure resulted in higher retained austenite fractions and a more homogeneous microstructure after Q&P processing compared to a starting microstructure of ferrite-pearlite. Starting martensitic microstructures also displayed higher work hardening rates and higher uniform elongations. Larger cold reductions saw accelerated dissolution kinetics and austenite formation during intercritical annealing, resulting in more similar final microstructures from the ferrite-pearlite and martensitic starting microstructures. Finally, the results presented here indicate that varying prior processing can be a route to manipulate and control austenite stability in a Q&P processed steel.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Origin of strain softening in a nanograined Al alloy

Here, one-step and multi-step nanoindentation experiments were conducted to investigate the mechanical response of an Al-Mg-Li alloy. Opposite to the strain hardening effect observed in the coarse-grained (CG) alloy, the nanograined (NG) alloy exhibits strain softening. Compared with multi-step nanoindentation experiments, the ultralow dislocation density and the grain boundary (GB) segregation promote a higher stress level during one-step nanoindentation experiments. Residual perfect dislocations induced by a previous loading and unloading during multi-step nanoindentation experiments lower the stress required for further plastic deformation. In addition, the storage of partial dislocations also serves to render plastic flow to commence at lower stresses. This work provides new insights for the fabrication and property optimization of NG alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predicting short-range order evolution in WTaCrVHf refractory high-entropy alloys

Short-range order (SRO) in multicomponent concentrated alloys affects their mechanical response. Hence, is paramount to understand how composition modifies the chemical ordering in the system to design materials with optimal properties. Here, in this work, we present a methodology to predict the SRO and thermodynamic properties in chemically complex systems and apply it to the WTaCrVHf quinary alloy. We observe that the addition of Hf significantly modifies the SRO, mainly at intermediate to low temperatures, matching experimental observations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Molecular Lignin Solubility and Structure in Organic Solvents

Lignin, a polymer found in the secondary plant cell wall of terrestrial plants, is the single largest source of renewable aromatics and has attracted considerable attention as a feedstock for potential industrial use. However, the secondary plant cell wall is a crowded environment, and lignin in its native form interacts with other biomass components within a larger network. Application of some organic solvents is known to liberate lignin from this network and creates lignin-rich streams suitable for conversion into target products. Through molecular-scale lignin simulation, we analyze how diverse lignin polymers change their structure in response to varying organic solvent environments. We quantify the relationship between solvent polarity and lignin polymer extension, observing maximum polymer expansion and solvation for solvents with polarity near those of dimethyl sulfoxide. From our observations at the nanoscale, increasing syringyl content within lignin polymers reduces the expansion of the polymer in organic solvent environments and decreases the free energy difference compared to aqueous solvent environments, thereby reducing solubility for high syringyl lignin polymers. The conformational transition rates between lignin polymer shapes increased through a combination of the solvent diffusion constant and polymer extension. The molecular simulations indicate that there is likely no single optimal organic solvent for lignin. Different solvent mixtures have optimal or near-optimal properties in solubilizing lignin polymers, thereby disrupting interactions with other biopolymers.

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

Mechanical adaptation of brachiopod shells via hydration-induced structural changes

The function-optimized properties of biominerals arise from the hierarchical organization of primary building blocks. Alteration of properties in response to environmental stresses generally involves time-intensive processes of resorption and reprecipitation of mineral in the underlying organic scaffold. Here, we report that the load-bearing shells of the brachiopod Discinisca tenuis are an exception to this process. These shells can dynamically modulate their mechanical properties in response to a change in environment, switching from hard and stiff when dry to malleable when hydrated within minutes. Using ptychographic X-ray tomography, electron microscopy and spectroscopy, we describe their hierarchical structure and composition as a function of hydration to understand the structural motifs that generate this adaptability. Key is a complementary set of structural modifications, starting with the swelling of an organic matrix on the micron level via nanocrystal reorganization and ending in an intercalation process on the molecular level in response to hydration.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electronic structure factors and the importance of adsorbate effects in chemisorption on surface alloys

The chemisorption energy is an integral aspect of surface chemistry, central to numerous fields such as catalysis, corrosion, and nanotechnology. Electronic-structure-based methods such as the Newns-Anderson model are therefore of great importance in guiding the engineering of material surfaces with optimal properties. However, existing methods are inadequate for interpreting complex, multi-metallic systems. Herein, we introduce a physics-based chemisorption model for alloyed transition metal surfaces employing primarily metal d-band properties that accounts for perturbations in both the substrate and adsorbate electronic states upon interaction. Importantly, we show that adsorbate-induced changes in the adsorption site interact with its chemical environment leading to a second-order response in chemisorption energy with the d-filling of the neighboring atoms. We demonstrate the robustness of the model on a wide range of transition metal alloys with O, N, CH, and Li adsorbates yielding a mean absolute error of 0.13 eV versus density functional theory reference chemisorption energies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurement of moisture-dependent ion diffusion constants in wood cell wall layers using time-lapse micro X-ray fluorescence microscopy

Our future bioeconomy depends on increased utilization of renewable lignocellulosic biomass. Controlling the diffusion of chemicals, such as inorganic ions, within secondary plant cell walls is central to many biomass applications. However, insufficient understanding of intra-cell-wall diffusion within secondary plant cell walls is hindering the advancement of many lignocellulosic biomass applications. In this work, X-ray fluorescence microscopy was used to measure diffusion constants of K + , Cu 2+ , and Cl - diffusing through loblolly pine (Pinus taeda) cell wall layers under 70%, 75%, or 80% relative humidity (RH). Results revealed that diffusion constants increased with RH, the larger Cu 2+ diffused more slowly than the K + , and the Cl - diffusion constant was the same as that for the counter cation, indicating cations and anions diffused together to maintain charge neutrality. Comparison with electrical conductivity measurements showed that conductivity is being controlled by ion mobility over these RH. The results further support that intra-cell-wall diffusion of inorganic ions is a Fickian diffusion process occurring through rubbery amorphous polysaccharides, which contradicts previous assertions that intra-cell-wall diffusion is an aqueous process occurring through water pathways. Researchers can now utilize polymer science approaches to engineer the molecular architecture of lignocellulosic biomass to optimize properties for specific end uses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Gapped metals as thermoelectric materials revealed by high-throughput screening

The typical strategy to design high performance thermoelectric materials is to dope a semiconducting material until optimal properties are obtained. However, some known thermoelectric materials such as La 3 Te 4 , Mo 3 Sb 7 , Yb 14 MnSb 11 , and NbCoSb are actually gapped metals,i.e., their band structure displays a gap slightly above or below the band crossed by the Fermi level. This key feature makes these metals comparable to degenerate semiconductors and thus suitable for thermoelectric applications. In this work, we perform a computational high-throughput search for such gapped metals exhibiting attractive thermoelectric properties. Several thousands of metals are found to present this key feature, and about one thousand of them show decent thermoelectric properties as evaluated by a computed zT. We present the different chemistry of gapped metals we discovered such as clathrates, Chevrel phases, or transition metal dichalcogenides and discuss their previous studies as thermoelectric and their potential as new thermoelectric materials.

36 MATERIALS SCIENCE↗