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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tailoring Cu-Zr gradient nanoglass structures: Influence of nanoparticle size and cooling rates on glass-glass interfaces

The study of gradient nanoglasses (GNGs) has gained attention due to their unique mechanical properties and potential applications in advanced materials. This study employs molecular dynamics simulations to synthesize a GNG using Cu-Zr metallic glass nanoparticles (NPs) sized from 3 to 15 nm. The NPs were produced by melting and quenching metallic clusters at a relatively slow quench rate of 10 9 K/s. The synthesis of GNG is elucidated along with the characterization of its heterogeneous metallic glass nanostructure. A seamless GNG structure is formed through cold compression of Cu 64 Zr 36 amorphous NPs of varying sizes. The influence of NP size on the GNG structure is investigated, utilizing deeply relaxed NPs, which exhibit a characteristic Cu segregation pattern on their surfaces. The results highlight an increase in structural heterogeneity due to heterogeneous mass transport and the development of local composition and density variations caused by Cu segregation at glass-glass interfaces (GGIs). A reduction in NP size is correlated with decreased Cu atomic displacements and local density at GGIs, suggesting that larger NPs may produce stronger GGIs. This research presents a novel methodology for synthesizing heterogeneous metallic glasses, demonstrating the capacity to control and customize nanostructure heterogeneity through the manipulation of NP sizes and cooling rates. Furthermore, these findings enhance our understanding of structural evolution during nanoglass synthesis and lay the foundation for further exploration in nanomaterial synthesis and characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Li-ion battery design through microstructural optimization using generative AI

Lithium-ion batteries are used across various applications, necessitating tailored cell designs to enhance performance. Optimizing electrode manufacturing parameters is a key route to achieving this, as these parameters directly influence the microstructure and performance of the cells. However, linking process parameters to performance is complex, and experimental or modeling campaigns are often slow and expensive. This study introduces a fast computational optimization framework for electrode manufacturing parameters. A generative model, trained on a small dataset of microstructural images associated with different manufacturing parameters, efficiently generates representative microstructures for new parameters. This model is integrated into a Bayesian optimization loop that includes microstructure generation, characterization, and simulation, aiming to find optimal manufacturing parameters for a particular application. Significant improvement in the energy density of a 4680 cell is achieved through bespoke cell design, highlighting the importance of cell-scale normalization. The framework’s modularity allows its application to various advanced materials manufacturing scenarios.

batteries↗
DOE OSTI2021

AI-enabled Dynamic Finish Machining Optimization for Sustained Surface Integrity

While machining processes are typically leveraged to establish geometric features, many functional characteristics of advanced materials are directly determined by their machining-induced surface integrity (SI). Current modeling approaches struggle to predict surface integrity, and typically neglect the effects of progressive tool-wear, resulting in inefficient ‘static’ process parameters. We present a novel integrated approach based on model-informed artificial intelligence (AI), which optimizes ‘dynamic’ process parameters in real-time. Here, by maximizing the useful life of a cutting tool over which a required set of SI parameters can be maintained, our paradigm will enable significantly more efficient processing of next-generation materials and components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Post-build stress-relief optimization for laser powder bed fusion 316H stainless steel

Nuclear energy remains a critical component of a diversified and efficient energy portfolio, offering reliable, high-capacity, and low-carbon power. However, in the U.S., aging infrastructure and the slow qualification and deployment of advanced materials and manufacturing techniques hinder progress in next-generation reactor technologies. This study explores the application of laser powder bed fusion (LPBF) additive manufacturing for stainless steel 316H, with a focus on optimizing post-build heat treatments to enhance material properties for high-temperature nuclear applications. The research targets the optimization of stress-relief temperatures to alleviate postbuild residual stresses, ensuring improvements in the microstructural corelated properties. A series of microstructural and mechanical evaluations were performed on LPBF-printed SS-316H samples which were subjected to annealing at temperatures varying between 650 °C and 850 °C. X-ray diffraction, scanning electron microscopy, and transmission electron microscopy analyses revealed that increasing the heattreatment temperature accelerated dislocation recovery. Vickers microhardness measurements showed an initial reduction in values, followed by stabilization over extended durations at all the temperatures. While higher temperatures facilitated faster recovery, they also promoted carbide precipitation along grain and solidification cell boundaries, narrowing the safe processing window. In contrast, heat treatment at 650°C preserved the cellular substructure and enabled controlled carbide precipitation over time. In conclusion, these findings highlight the importance of time–temperature optimization and suggest that 650°C for up to 2 h provides the most favorable balance between recovery and carbide control for a stress-relief treatment.

316 stainless steel↗
DOE OSTI2021

Irradiation effects in tungsten—From surface effects to bulk mechanical properties

Advanced materials such as tungsten fibre-reinforced composites allow to overcome severe weaknesses of the baseline materials for plasma-facing components — copper and tungsten. The effect of the fusion environment on the mechanical properties of these materials, e.g. the embrittlement by neutron irradiation, plays a key role for the development of future fusion reactors. To simulate this effect, high-energy ions are used as a substitute for the displacement damage by neutrons. We propose the use of very fine tungsten wire as a possibility of studying the influence of irradiation damage on the mechanical properties. This is possible as they allow full-depth irradiation of almost the entire volume despite the limited penetration depth of ions. Geometrical size effects are mitigated due to the nanoscale microstructure of the wire. In addition, similar wire is used in tungsten fibre-reinforced composites. Thus, the investigation of irradiated wire can directly be used for the prediction of the bulk composite properties. For the proof of this concept tungsten wire with a diameter of 16 μm was electrochemically thinned to 5 μm and irradiated with 20.5 MeV W 6+ ions. The mechanical properties were subsequently determined by macroscopic tensile testing. Irradiation to 0.3, 1 and 9 dpa did not lead to a change of the mechanical behaviour. Both strength and ductility, the latter indicated by the reduction of area, were similar to the as-fabricated state.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A theoretical study of the bonding properties of R 4 Sb 3 compounds

Here, this study investigates the electronic structure and bonding properties of rare-earth antimonide compounds, specifically Yb 4 Sb 3 and La 4 Sb 3 , utilizing density functional theory calculations. The analysis reveals that Yb 4 Sb 3 exhibits a predominantly ionic character whereas La 4 Sb 3 displays a greater degree of covalent bonding. Moreover, the presence of divalent ytterbium leads to p-type conduction at high temperatures in Yb 4 Sb 3 . Conversely, La 4 Sb 3 displays n-type conduction because of a larger electronic transfer from the rare-earth metal towards antimony. These findings provide valuable insights into the structural and electronic properties that govern the performance of R 4 Sb 3 compounds, contributing to the development of advanced materials for thermoelectric energy conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Single-Molecule Tracking Measurements Reveal the Detailed Mechanisms of Molecular Diffusion in Solvent Mixtures under Nanoconfinement

Understanding mass transport mechanisms in nanopores is important for developing advanced materials for chemical separations, chemical sensing, and energy storage. This paper reports a novel imaging platform that is employed for the first time to investigate the detailed diffusion dynamics of single rhodamine B (RhB) dye molecules confined within solution-filled cylindrical anodic aluminum oxide (AAO) nanopores. The imaging platform relies on illumination of horizontally-oriented AAO nanopores in a highly inclined and laminated optical (HILO) light sheet microscopy geometry. The method was used to investigate the translational and orientational dynamics of single rhodamine B (RhB) molecules within horizontally-oriented 5- and 10-nm diameter AAO nanopores filled with water–ethanol mixtures. The established platform enabled the observation of one-dimensional motion along the pore axis involving occasional short- or long-term immobilization at the single-molecule level. Analysis of cumulative squared-displacement distributions revealed fast (5 – 30 µm²/s), intermediate (1 – 5 µm²/s), and slow (< 1 µm²/s) diffusion components. From the effects of mixture composition and pore size on the contributions of these three components, we inferred that the fast, intermediate, and slow components could be assigned to desorption-mediated hopping, crawling, and wiggling motions, respectively. The platform based on the horizontally-oriented AAO nanopores also permitted single-molecule emission polarization measurements that revealed the negligible steric confinement of individual diffusing RhB molecules within the AAO nanopores. The imaging platform based on AAO membranes and HILO microscopy provided a unique means to investigate how solvation-mediated surface interactions and nanoconfinement govern molecular transport in nanoporous environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields

Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Progress, Challenges, and Opportunities in the Synthesis, Characterization, and Application of Metal-Boride-Derived Two-Dimensional Nanostructures

Two-dimensional (2D) metal-boride-derived nanostructures have been a focus of intense research for the past decade, with an emphasis on new synthetic approaches, as well as on the exploration of possible applications in next-generation advanced materials and devices. Their unusual mechanical, electronic, optical, and chemical properties, arising from low dimensionality, present a new paradigm to the science of metal borides that has traditionally focused on their bulk properties. This Perspective discusses the current state of research on metal-boride-derived 2D nanostructures, highlights challenges that must be overcome, and identifies future opportunities to fully utilize their potential.

metals↗
DOE OSTI2021

Ultrafast and Controllable Phase Evolution by Flash Joule Heating

Flash Joule heating (FJH), an advanced material synthesis technique, has been used for the production of high-quality carbon materials. Direct current discharge through the precursors by large capacitors has successfully converted carbon-based starting materials into bulk quantities of turbostratic graphene by the FJH process. However, the formation of other carbon allotropes, such as nanodiamonds and concentric carbon materials, as well as the covalent functionalization of different carbon allotropes by the FJH process, remains challenging. Here, we report the solvent-free FJH synthesis of three different fluorinated carbon allotropes: fluorinated nanodiamonds, fluorinated turbostratic graphene and fluorinated concentric carbon. This is done by millisecond flashing of organic fluorine compounds and fluoride precursors. Spectroscopic analysis confirms the modification of the electronic states and the existence of various short-range and long-range orders in the different fluorinated carbon allotropes. As a result, the flash time-dependent relationship is further demonstrated to control the phase evolution and product compositions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Robust Interfacial Effect in Multi-interface Environment through Hybrid Reconstruction Chemistry for Enhanced Energy Storage

Electrochemical-oxidation-driven reconstruction has emerged as an efficient approach for developing advanced materials, but the reconstructed microstructure still faces challenges including inferior conductivity, unsatisfying intrinsic activity, and active-species dissolution. In this report we present hybrid reconstruction chemistry that synergistically couples electrochemical oxidation with electrochemical polymerization (EOEP) to overcome these constraints. During the EOEP process, the metal hydroxides undergo rapid reconstruction and dynamically couple with polypyrrole (PPy), resulting in an interface-enriched microenvironment. We observe that the interaction between PPy and the reconstructed metal center (i.e., Mn > Ni, Co) is strongly correlated. Theoretical calculation results demonstrate that the strong interaction between Mn sites and PPy breaks the intrinsic limitation of MnO 2 , rendering MnO 2 with a metallic property for fast charge transfer and enhancing the ion-adsorption dynamics. Operando Raman measurement confirms the promise of EOEP-treated Mn(OH) 2 (E-MO/PPy) to stably work under a 1.2 V potential window. The tailored E-MO/PPy exhibits a high capacitance of 296 F g –1 at a large current density of 100 A g –1 . Here our strategy presents breakthroughs in upgrading the electrochemical reconstruction technique, which enables both activity and kinetics engineering of electrode materials for better performance in energy-related fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Scattering-type Scanning Near-Field Optical Microscopy of Polymer-Coated Gold Nanoparticles

Scattering-type scanning near-field optical microscopy (s-SNOM) has emerged over the past years as a powerful characterization tool that can probe important properties of advanced materials and biological samples in a label-free manner, with spatial resolutions lying in the nanoscale realm. In this work, we explore such usefulness in relationship with an interesting class of materials: polymer-coated gold nanoparticles (NPs). As thoroughly discussed in recent works, the interplay between the Au core and the polymeric shell has been found to be important in many applications devoted to biomedicine. We investigate bare Au NPs next to polystyrenesulfonate (PSS) and poly(diallyldimethylammonium chloride) (PDDA) coated ones under 532 nm laser excitation, an wavelength matching the surface plasmon band of the custom-synthesized nanoparticles. We observe consistent s-SNOM phase signals in the case of bare and shallow-coated Au NPs, whereas for thicker shell instances, these signals fade. For all investigated samples, the s-SNOM amplitude signals were found to be very weak, which may be related to reduced scattering efficiency due to absorption of the incident beam. We consider these observations important, as they may facilitate studies and applications in nanomedicine and nanotechnology where the precise positioning of polymer-coated Au NPs with nanoscale resolution is needed besides their dielectric function and related intrinsic optical properties, which are also quantitatively available with s-SNOM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Molecular H 2 as the Reducing Agent in Low-Temperature Oxide Reduction Using Calcium Hydride

Low-temperature synthesis is crucial for advancing sustainable manufacturing and accessing novel metastable phases. Metal hydrides have shown great potential in facilitating the reduction of oxides at low temperatures, yet the underlying mechanism—whether driven by H - , H 2 , or atomic H—remains unclear. Here, in this study, we employ in situ electrical transport measurements and first- principles calculations to investigate the CaH 2 -driven reduction kinetics in epitaxial α-Fe 2 O 3 thin films. Intriguingly, samples in direct contact with or separated from CaH 2 powders exhibit similar apparent activation energies for H 2 reduction, although direct contact significantly increases the reduction rate. These findings indicate that molecular H 2 is the dominant reducing species in the low-temperature reduction of oxides using CaH 2 , with a key aspect of the hydrides' superior reducing power attributed to their ability to eliminate residual moisture. This work underscores the critical role of moisture control in enabling effective low-temperature oxide reduction for advanced material synthesis.

Wang, Jiayue [SLAC National Accelerator Laboratory↗
DOE OSTI2020

Porous cage-derived nanomaterial inks for direct and internal three-dimensional printing

The convergence of 3D printing techniques and nanomaterials is generating a compelling opportunity space to create advanced materials with multiscale structural control and hierarchical functionalities. While most nanoparticles consist of a dense material, less attention has been payed to 3D printing of nanoparticles with intrinsic porosity. Here, we combine ultrasmall (about 10 nm) silica nanocages with digital light processing technique for the direct 3D printing of hierarchically porous parts with arbitrary shapes, as well as tunable internal structures and high surface area. Thanks to the versatile and orthogonal cage surface modifications, we show how this approach can be applied for the implementation and positioning of functionalities throughout 3D printed objects. Furthermore, taking advantage of the internal porosity of the printed parts, an internal printing approach is proposed for the localized deposition of a guest material within a host matrix, enabling complex 3D material designs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Valence-free open nanoparticle superlattices

A cornerstone of advanced materials design is establishing a framework for assembling nanoparticle superstructures with tailored symmetries. A longstanding challenge has been assembling diamond-like superstructures for photonic devices. Traditionally, such open superstructures require functionalized nanoparticles with directional or anisotropic interactions, reminiscent of valence bonding in a diamond. Here, we present a robust strategy for assembling valence-free nanoparticles into a broad array of cubic superstructures. By grafting nanoparticles with oppositely charged, end-functionalized water-soluble polymers of adjustable molecular weight, we gain control over electrostatic interactions and conformational constraints. This unified approach yields lattices analogous to rock salt, CsCl, zinc-blende, diamond, and the rare simple cubic phase, with tunable lattice constants. Theoretical models and simulations elucidate the underlying interactions, providing a framework for engineering valence-free nanoparticle superlattices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

3D nanolithography with metalens arrays and spatially adaptive illumination

The growing demand for advanced materials, miniaturized devices and integrated microsystems calls for the reliable fabrication of complex, multiscale, three-dimensional (3D) architectures, a need increasingly addressed through light-based and laser-based processes. However, owing to the field-of-view (FOV) limitations of conventional imaging optics, existing 3D laser nanofabrication techniques face fundamental challenges in throughput, proximity error and stitching defects on the path to scaling. Here, in this study, we present a scalable 3D nanofabrication platform that uses a metalens-generated focal spot array to parallelize two-photon lithography (TPL) beyond centimetre-scale write field areas. Metalenses are ideally suited for producing submicron-scale focal spots for high-throughput nanolithography, as they uniquely feature large numerical apertures (NAs), immersion media compatibility and large-scale manufacturability. We experimentally demonstrate a printing system that uses a 12-cm 2 metalens array to produce more than 120,000 cooperative focal spots, corresponding to a throughput exceeding 10 8 voxels s −1 . By programmatically patterning the focal spot array using a spatial light modulator (SLM), an adaptive parallel printing strategy is developed for precise greyscale linewidth modulation and choreographed printing of semiperiodic and fully aperiodic 3D geometries. We demonstrate parallel printing of replicated microstructures (>50 M microparticles per day), centimetre-scale 3D architectures with feature sizes down to 113 nm, and photonic and mechanical metamaterials. This work demonstrates the potential of 3D nanolithography towards wafer-scale production, showing how TPL could be used at scale for applications in microelectronics, biomedicine, quantum technology and high-energy laser targets.

Materials science↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗