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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A contorted nanographene shelter

Nanographenes have kindled considerable interest in the fields of materials science and supramolecular chemistry as a result of their unique self-assembling and optoelectronic properties. Encapsulating the contorted nanographenes inside artificial receptors, however, remains challenging. Herein, we report the design and synthesis of a trigonal prismatic hexacationic cage, which has a large cavity and adopts a relatively flexible conformation. It serves as a receptor, not only for planar coronene, but also for contorted nanographene derivatives with diameters of approximately 15 Å and thicknesses of 7 Å. A comprehensive investigation of the host-guest interactions in the solid, solution and gaseous states by experimentation and theoretical calculations reveals collectively an induced-fit binding mechanism with high binding affinities between the cage and the nanographenes. Notably, the photostability of the nanographenes is improved significantly by the ultrafast deactivation of their excited states within the cage. Encapsulating the contorted nanographenes inside the cage provides a noncovalent strategy for regulating their photoreactivity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive manufacturing of strong silica sand structures enabled by polyethyleneimine binder

Abstract Binder Jet Additive Manufacturing (BJAM) is a versatile AM technique that can form parts from a variety of powdered materials including metals, ceramics, and polymers. BJAM utilizes inkjet printing to selectively bind these powder particles together to form complex geometries. Adoption of BJAM has been limited due to its inability to form strong green parts using conventional binders. We report the discovery of a versatile polyethyleneimine (PEI) binder for silica sand that doubled the flexural strength of parts to 6.28 MPa compared with that of the conventional binder, making it stronger than unreinforced concrete (~4.5 MPa) in flexural loading. Furthermore, we demonstrate that PEI in the printed parts can be reacted with ethyl cyanoacrylate through a secondary infiltration, resulting in an increase in flexural strength to 52.7 MPa. The strong printed parts coupled with the ability for sacrificial washout presents potential to revolutionize AM in various applications including construction and tooling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Solvent-driven fractional crystallization for atom-efficient separation of metal salts from permanent magnet leachates

Abstract This work reports a dimethyl ether-driven fractional crystallization process for separating rare earth elements and transition metals. The process has been successfully applied in the treatment of rare earth element-bearing permanent magnet leachates as an atom-efficient, reagent-free separation method. Using ~5 bar pressure, the solvent was dissolved into the aqueous system to displace the contained metal salts as solid precipitates. Treatments at distinct temperatures ranging from 20–31 °C enable crystallization of either lanthanide-rich or transition metal-rich products, with single-stage solute recovery of up to 95.9% and a separation factor as high as 704. Separation factors increase with solution purity, suggesting feasibility for eco-friendly solution treatments in series and parallel to purify aqueous material streams. Staged treatments are demonstrated as capable of further improving the separation factor and purity of crystallized products. Upon completion of a crystallization, the solvent can be recovered with high efficiency at ambient pressure. This separation process involves low energy and reagent requirements and does not contribute to waste generation.

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

Thermodynamics-guided alloy and process design for additive manufacturing

In conventional processing, metals go through multiple manufacturing steps including casting, plastic deformation, and heat treatment to achieve the desired property. In additive manufacturing (AM) the same target must be reached in one fabrication process, involving solidification and cyclic remelting. The thermodynamic and kinetic differences between the solid and liquid phases lead to constitutional undercooling, local variations in the solidification interval, and unexpected precipitation of secondary phases. These features may cause many undesired defects, one of which is the so-called hot cracking. The response of the thermodynamic and kinetic nature of these phenomena to high cooling rates provides access to the knowledge-based and tailored design of alloys for AM. Here, we illustrate such an approach by solving the hot cracking problem, using the commercially important IN738LC superalloy as a model material. The same approach could also be applied to adapt other hot-cracking susceptible alloy systems for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Observation of formation and local structures of metal-organic layers via complementary electron microscopy techniques

Abstract Metal-organic layers (MOLs) are highly attractive for application in catalysis, separation, sensing and biomedicine, owing to their tunable framework structure. However, it is challenging to obtain comprehensive information about the formation and local structures of MOLs using standard electron microscopy methods due to serious damage under electron beam irradiation. Here, we investigate the growth processes and local structures of MOLs utilizing a combination of liquid-phase transmission electron microscopy, cryogenic electron microscopy and electron ptychography. Our results show a multistep formation process, where precursor clusters first form in solution, then they are complexed with ligands to form non-crystalline solids, followed by the arrangement of the cluster-ligand complex into crystalline sheets, with additional possible growth by the addition of clusters to surface edges. Moreover, high-resolution imaging allows us to identify missing clusters, dislocations, loop and flat surface terminations and ligand connectors in the MOLs. Our observations provide insights into controllable MOL crystal morphology, defect engineering, and surface modification, thus assisting novel MOL design and synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accurate additive manufacturing of lightweight and elastic carbons using plastic precursors

Despite groundbreaking advances in the additive manufacturing of polymers, metals, and ceramics, scaled and accurate production of structured carbons remains largely underdeveloped. This work reports a simple method to produce complex carbon materials with very low dimensional shrinkage from printed to carbonized state (less than 4%), using commercially available polypropylene precursors and a fused filament fabrication-based process. The control of macrostructural retention is enabled by the inclusion of fiber fillers regardless of the crosslinking degree of the polypropylene matrix, providing a significant advantage to directly control the density, porosity, and mechanical properties of 3D printed carbons. Using the same printed plastic precursors, different mechanical responses of derived carbons can be obtained, notably from stiff to highly compressible. This report harnesses the power of additive manufacturing for producing carbons with accurately controlled structure and properties, while enabling great opportunities for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Grayscale projection two-photon lithography using sub-diffraction motifs for ultrafast and precise nanoscale 3D printing

Rapid and high-fidelity nanoscale 3D printing is highly desirable, but it is difficult due to the tradeoff between speed and accuracy. Although optical projection techniques can massively scale up printing, fidelity is compromised due to the difficulty in precisely controlling the light dosage over the entire field. This challenge is typically addressed by using multiple projections, but it slows down printing. Here, we present grayscale projection two-photon lithography to overcome this tradeoff. Despite using a binary mask, it enables projecting more than 15,000 focal spots, each with independently tunable intensity. It advantageously leverages constraints imposed by optical diffraction to achieve grayscale tuning over the entire field at once. By directly tuning the focal spot intensities, we demonstrate suppression of proximity effects, compensation of non-uniform illumination, compensation of stitching artefacts, and rapid 3D printing with a single femtosecond pulse per layer. We demonstrate printing of nanowires as thin as 55 nm and achieve rates of 1.7 billion voxels/s and 215 mm 3 /hr.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration

Observations of microstructural coarsening at cryogenic temperatures, as well as numerous simulations of grain boundary motion that show faster migration at low temperature than at high temperature, have been troubling because they do not follow the expected Arrhenius behavior. This work demonstrates that classical equations, that are not simplified, account for all these oddities and demonstrate that non-Arrhenius behavior can emerge from thermally activated processes. According to this classical model, this occurs when the intrinsic barrier energies of the processes become small, allowing activation at cryogenic temperatures. Additional thermal energy then allows the low energy process to proceed in reverse, so increasing temperature only serves to frustrate the forward motion. This classical form is shown to reconcile and describe a variety of diverse grain boundary migration observations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accurate and uncertainty-aware multi-task prediction of HEA properties using prior-guided deep Gaussian processes

Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys (HEAs), especially when integrating computational predictions with sparse experimental observations. This study systematically evaluates the training and testing performance of four prominent surrogate models—conventional Gaussian processes (cGP), Deep Gaussian processes (DGP), encoder-decoder neural networks for multi-output regression and eXtreme Gradient Boosting (XGBoost)—applied to a hybrid dataset of experimental and computational properties of the 8-component HEA system Al-Co-Cr-Cu-Fe-Mn-Ni-V. We specifically assess their capabilities in predicting correlated material properties, including yield strength, hardness, modulus, ultimate tensile strength, elongation, and average hardness under dynamic/quasi-static conditions, alongside auxiliary computational properties. The comparison highlights the strengths of hierarchical deep modeling approaches in handling heteroscedastic, heterotopic, and incomplete data commonly encountered in materials science. Our findings illustrate that combined surrogate models such as DGPs infused with machine-learned priors outperform other surrogates by effectively capturing inter-property correlations and by assimilating prior knowledge. This enhanced predictive accuracy positions the combined surrogate models as powerful tools for robust and data-efficient materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hardware-accelerated inference for real-time gravitational-wave astronomy

The field of transient astronomy has seen a revolution with the first gravitational-wave detections and the arrival of multi-messenger observations they enabled. Transformed by the first detection of binary black hole and binary neutron star mergers, computational demands in gravitational-wave astronomy are expected to grow by at least a factor of two over the next five years as the global network of kilometer-scale interferometers are brought to design sensitivity. With the increase in detector sensitivity, real-time delivery of gravitational-wave alerts will become increasingly important as an enabler of multi-messenger followup. In this work, we report a novel implementation and deployment of deep learning inference for real-time gravitational-wave data denoising and astrophysical source identification. This is accomplished using a generic Inference-as-a-Service model that is capable of adapting to the future needs of gravitational-wave data analysis. Overall, our implementation allows seamless incorporation of hardware accelerators and also enables the use of commercial or private (dedicated) as-a-service computing. Based on our results, we propose a paradigm shift in low-latency and offline computing in gravitational-wave astronomy. Such a shift can address key challenges in peak-usage, scalability and reliability, and provide a data analysis platform particularly optimized for deep learning applications. The achieved sub-millisecond scale latency will also be relevant for any machine learning-based real-time control systems that may be invoked in the operation of near-future and next generation ground-based laser interferometers, as well as the front-end collection, distribution and processing of data from such instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Eliminating dissolution of platinum-based electrocatalysts at the atomic scale

Deployment of proton-exchange membrane fuel cells is limited by the durability of Pt-nanoscale catalysts during cathodic oxygen reduction reactions. Dissolution processes on single crystalline and thin film surfaces are now correlated leading to the design of PtAu catalysts with suppressed dissolution. A remaining challenge for the deployment of proton-exchange membrane fuel cells is the limited durability of platinum (Pt) nanoscale materials that operate at high voltages during the cathodic oxygen reduction reaction. In this work, atomic-scale insight into well-defined single-crystalline, thin-film and nanoscale surfaces exposed Pt dissolution trends that governed the design and synthesis of durable materials. A newly defined metric, intrinsic dissolution, is essential to understanding the correlation between the measured Pt loss, surface structure, size and ratio of Pt nanoparticles in a carbon (C) support. It was found that the utilization of a gold (Au) underlayer promotes ordering of Pt surface atoms towards a (111) structure, whereas Au on the surface selectively protects low-coordinated Pt sites. Finally, this mitigation strategy was applied towards 3 nm Pt 3 Au/C nanoparticles and resulted in the elimination of Pt dissolution in the liquid electrolyte, which included a 30-fold durability improvement versus 3 nm Pt/C over an extended potential range up to 1.2 V.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Robotic four-dimensional pixel assembly of van der Waals solids

Van der Waals (vdW) solids can be engineered with atomically precise vertical composition through the assembly of layered two-dimensional materials. However, the artisanal assembly of structures from micromechanically exfoliated flakes is not compatible with scalable and rapid manufacturing. Further engineering of vdW solids requires precisely designed and controlled composition over all three spatial dimensions and interlayer rotation. Here, we report a robotic four-dimensional pixel assembly method for manufacturing vdW solids with unprecedented speed, deliberate design, large area and angle control. We used the robotic assembly of prepatterned 'pixels' made from atomically thin two-dimensional components. Wafer-scale two-dimensional material films were grown, patterned through a clean, contact-free process and assembled using engineered adhesive stamps actuated by a high-vacuum robot. We fabricated vdW solids with up to 80 individual layers, consisting of 100 x 100 μm 2 areas with predesigned patterned shapes, laterally/vertically programmed composition and controlled interlayer angle. This enabled efficient optical spectroscopic assays of the vdW solids, revealing new excitonic and absorbance layer dependencies in MoS 2 . Furthermore, we fabricated twisted $N$-layer assemblies, where we observed atomic reconstruction of twisted four-layer WS 2 at high interlayer twist angles of >= 4°. In conclusion, our method enables the rapid manufacturing of atomically resolved quantum materials, which could help realize the full potential of vdW heterostructures as a platform for novel physics and advanced electronic technologies.

42 ENGINEERING↗
DOE OSTI2023

Spontaneous assembly of hierarchical phases

We report the grand promise of self-assembly is the creation of target nanostructures through spontaneous molecular organization, a process that is — in principle — simpler and more scalable than laborious top-down nanofabrication methods. Yet self-assembly faces a fundamental challenge: the structures that form thermodynamically tend to minimize surface area and maximize symmetry; the most readily-accessible structures are thus quite simple. Block copolymer (BCP) self-assembly, for example, takes advantage of the chemical incompatibility along a polymer backbone to drive local phase separation; frustrated assembly leads to a nanoscale morphology whose unit cell is dictated by chain architecture. Canonical BCPs (linear chains with two blocks) form alternating lamellae and hexagonally-packed cylinders in a straightforward manner; but more exotic phases require additional control, for example directing the assembly using external forces, such as shear or chemical templates. An elegant alternative is to use synthetic methods to design more sophisticated chain architectures, which may give rise to new morphologies. An outstanding challenge is to achieve morphological control without undue synthetic burden. Sun et al. now report in Nature Nanotechnology the design and synthesis of novel triblock copolymers that give rise to structural order at multiple length scales, thereby forming complex and hierarchical nanoscale phases.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Microstrain screening towards defect-less layered transition metal oxide cathodes

Microstrain and the associated surface-to-bulk propagation of structural defects are known to be major roadblocks to developing high-energy and long-life batteries. However, the origin and effects of microstrain during the synthesis of battery materials remain largely unknown. Here, in this study, we perform microstrain screening during real-time and realistic synthesis of sodium layered oxide cathodes. Evidence gathered from multiscale in situ synchrotron X-ray diffraction and microscopy characterization collectively reveals that the spatial distribution of transition metals within individual precursor particles strongly governs the nanoscale phase transformation, local charge heterogeneity and accumulation of microstrain during synthesis. This unexpected dominance of transition metals results in a counterintuitive outward propagation of defect nucleation and growth. These insights direct a more rational synthesis route to reduce the microstrain and crystallographic defects within the bulk lattice, leading to significantly improved structural stability. The present work on microstrain screening represents a critical step towards synthesis-by-design of defect-less battery materials.

25 ENERGY STORAGE↗
DOE OSTI2020

Exploiting Chemistry and Molecular Systems for Quantum Information Science

The power of chemistry to prepare new compositions of matter has driven the quest for new approaches to solve problems having global societal impact, such as renewable energy, healthcare, and information science. In the latter case, the intrinsic quantum nature of molecules offers intriguing new possibilities to advance the emerging field of Quantum Information Science (QIS). In this Perspective, we discuss how chemical systems and reactions can impact quantum computing, communication, and sensing. Hierarchical molecular design and synthesis, from small molecules to supramolecular assemblies, combined with new spectroscopic probes of quantum coherence and theoretical modeling of complex systems, offer a broad range of possibilities to realize practical QIS applications.

quantum computing, Spectrocopy, computational chem↗
DOE OSTI2024

Non-classical crystallization in soft and organic materials

Classical nucleation and crystal growth theories describe how nuclei form, become stable after reaching a critical size and then enlarge through monomer attachment. More than two decades ago, non-classical pathways have been proposed for various types of (bio)molecules and materials, which can substantially alter the crystallization kinetics and outcomes. Direct observation of non-classical crystallization of inorganic nanomaterials, including metastable structure-mediated and particle attachment-based pathways that usually occur on the nanoscale, was enabled by in situ liquid-phase electron microscopy. However, it was not until recently that the crystallization dynamics of beam-sensitive soft materials were directly imaged with sufficient spatial resolution, and a level of microstructural understanding of defects and interfaces emerged. This article provides a high-level review of the non-classical crystallization pathways discovered in soft and organic materials and a forward-looking guide for future research. We first analyse how the characteristics of soft materials affect their crystallization pathways and kinetics. We then identify technical approaches to studying the crystallization trajectories of soft materials and discuss strategies to properly select and apply them to different systems. Breakthroughs made in understanding the crystallization of small organic molecules, (bio)macromolecules, colloids and reticular framework materials are examined. Lastly, we provide an outlook on the challenges in elucidating soft material crystallization pathways and the opportunities for assisting the design and synthesis of new materials and structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cellular fluidics

The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas–liquid–solid interfaces and capillary phenomena in porous media. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering. In this paper, we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures—enabled by emerging 3D printing methods—for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be ‘programmed’ through architected design of cell type, size and relative density. We demonstrate gas–liquid transport processes such as transpiration and absorption, using evaporative cooling and CO 2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.

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

Discovery of chalcogenides structures and compositions using mixed fluxes

Advancements in many modern technologies rely on the continuous need for materials discovery. However, the design of synthesis routes leading to new and targeted solid-state materials requires understanding of reactivity patterns. Advances in synthesis science are necessary to increase efficiency and accelerate materials discovery. We present a highly effective methodology for the rational discovery of materials using high-temperature solutions or fluxes having tunable solubility. This methodology facilitates product selection by projecting the free-energy landscape into real synthetic variables: temperature and flux ratio. We demonstrate the effectiveness of this technique by synthesizing compounds in the chalcogenide system of A(Ba)-Cu-Q(O) (Q = S or Se; A = Na, K or Rb) using mixed AOH/AX (A = Li, Na, K or Rb; X = Cl or I) fluxes. We present 30 unreported compounds or compositions, including more than ten unique structural types, by systematically varying the temperature and flux ratios without requiring changing the proportions of starting materials. Additionally, we found that the structural dimensionality of the compounds decreases with increasing reactant solubility and temperature. This methodology serves as an effective general strategy for the rational discovery of inorganic solids.

36 MATERIALS SCIENCE↗