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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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Biosynthesis of polycyclopropanated high energy biofuels
Cyclopropane-functionalized hydrocarbons are excellent fuels due their high energy density. However, the organic synthesis of these molecules is challenging and harmful to the environment. In this work we produced polycyclopropanated fatty acids in bacteria. These molecules can be easily converted into renewable fuels for high energy applications such as shipping, long-haul transport, aviation, and rocketry. We explored the chemical diversity encoded in the genome of thousands of bacteria to identify and repurpose naturally occurring cyclopropanated molecules. We identified a set of candidate iterative polyketide synthases (iPKSs) predicted to produce polycyclopropanated fatty acids (POP-FAs), expressed these PKSs in Streptomyces coelicolor and produced the POP-FAs. We determined the structure of the molecules and increased their production 22-fold. Polycyclopropanated fatty acid methyl esters (POP-FAMEs) were obtained by methyl esterifying the POP-FAs. Finally, we calculated that our POP fuel candidates can have energy densities of more than 50 MJ/L. Our research shows that POP-FAMEs and other polyketide derived POPs have the energetic properties for energy-demanding applications for which sustainable alternatives are scarce.
Evolution of solid electrolyte interphase and active material in the silicon wafer model system
Alloying anode materials for lithium-ion batteries, such as silicon (Si), are an important focus of materials research due to the demand for increased energy density for electric vehicles and stationary grid storage. However, progress towards next generation anode materials has been hindered by poor capacity retention due to the instability of the Si active material and the solid electrolyte interphase (SEI). Herein, the evolution of the active Si material and the SEI are simultaneously investigated from the perspective of chemical, structural, morphological, and electronic evolution in the Si wafer model system through its cycling life, using time-of-flight secondary ion mass spectrometry (TOF-SIMS), scanning transmission electron microscopy (STEM), atomic force microscopy (AFM), and scanning spreading resistance microscopy (SSRM). The results illustrate a dynamic evolution of the SEI and active Si material through cycling. Through an improved understanding of evolution of SEI and Si active material within the Si wafer model system, mitigation strategies may be designed to extend the lifetime of Si anodes.
Local electrical degradations of solid-state electrolyte by nm-scale operando imaging of ionic and electronic transports
We report on degradation mechanisms of solid-state electrolyte (SSE) based on insights from nm-scale ionic conduction and electronic leakage for solid-state batteries. The significantly different local degradations revealed by nm-scale ionic and electronic transport imaging demonstrate the need for this nm-scale investigation. State-of-the-art lithium-ion conductive glass ceramic (Li 2 O–Al 2 O 3 –SiO 2 –P 2 O5–TiO2-GeO2) SSE shows at least two types of degradations spatially separated within the SSE, namely: (1) ionic conduction blocking and slight electronic leaking and (2) highly electronic shunting. Degradation was significantly suppressed by application of a Li-containing polyacrylonitrile thin coating on both sides of the ceramic SSE. With this coating, the ionic conduction was not reduced by the extensive cycling; instead, it improved slightly, although accompanied by a slight increase in electronic leaking. Our nm-scale transport imaging was achieved using an atomic force microscopy (AFM)-based half-cell setup and a logarithmic-scale amplifier with current sensitivity down to the fA (10-15 A) range. This half-cell setup consisting of an AFM-probe/SSE/Li structure can distinguish the ionic from the electronic current by flipping the bias-voltage polarity. This nm-scale operando imaging opens up novel characterization of ionic and electronic transport in the field of solid-state batteries.
A Safer, Wide-Temperature Liquefied Gas Electrolyte Based on Difluoromethane
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Shared micromobility as a first- and last-mile transit solution? Spatiotemporal insights from a novel dataset
The first- and last-mile (FM/LM) problem is a major deterrent to public transit use. With the rise of shared micromobility options such as shared e-scooters in recent years, there is a growing interest in understanding their potential to serve as a last-mile transit solution. However, empirical data regarding the integrated use of shared micromobility and public transit have been limited so far. As a result, much is unknown regarding the spatiotemporal patterns and characteristics of shared micromobility trips serving as an FM/LM connection to transit. Here, this paper addresses these knowledge gaps by leveraging a novel dataset (i.e., the Spin post-ride survey dataset) that records thousands of transit-connecting shared e-scooter trips in Washington DC. Specifically, we used the dataset to reveal the spatiotemporal patterns of transit-connecting shared e-scooter trips in Washington DC, resulting in some major policy insights regarding the integral use of shared e-scooters and public transit. We further leveraged the dataset to validate if and to what extent a commonly applied buffer-zone approach can infer FM/LM micromobility trips accurately. Statistical tests showed that the actual FM/LM Spin e-scooter trips differ from inferred FM/LM Spin e-scooter trips in both spatial and temporal dimensions. This indicates that the common practice of inferring FM/LM micromobility trips with a buffer-zone approach can lead to inaccurate estimates of transit-connecting micromobility trips.
Heparan sulfate selectively inhibits the collagenase activity of cathepsin K
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Dynamic and Programmable Cellular-Scale Granules Enable Tissue-like Materials
Living tissues are an integrated, multiscale architecture consisting of dense cellular ensembles and extracellular matrices (ECMs). The cells and ECMs cooperate to enable specialized mechanical properties and dynamic responsiveness. However, the mechanical properties of living tissues are difficult to replicate. A particular challenge is identification of a cell-like synthetic component, which is tightly integrated with its matrix and also responsive to external stimuli. Here, we demonstrate that cellular-scale hydrated starch granules, an underexplored component in materials science, can turn conventional hydrogels into tissue-like materials when composites are formed. By using several synchrotron-based X-ray techniques, we reveal the mechanically induced organization and training dynamics of the starch granules in the hydrogel matrix. These dynamic behaviors enable multiple tissue-like properties such as programmability, anisotropy, strain-stiffening, mechanochemistry, and self-healability.
Kinetics and mechanism of light-induced phase separation in a mixed-halide perovskite
Halide ion phase separation is a barrier to the application of mixed-halide perovskites, whereby the presence of large populations of photo-generated or injected carriers causes undesirable changes in the local band gap. Here, we investigate the mechanism of phase separation in CsPbI x Br 3-x perovskite single crystals driven by light. The phase separation process and its dynamics are visualized at the nanometer scale at cryogenic temperatures using in-situ scanning transmission electron microscopy and cathodoluminescence. Combined with phase field modeling that accounts for the coupling between electronic and chemical driving forces, our observations point to a spinodal decomposition mechanism in which both the amplitude of composition fluctuation and the characteristic length scale grow non-linearly with time. Our findings provide microscopic insights that can assist in further engineering mixed-halide perovskites either for stability or for intentional programming of the local halide ion composition, opening pathways to a wide range of applications.
Designing complex concentrated alloys with quantum machine learning and language modeling
Designing novel complex concentrated alloys (CCAs) is an essential topic in materials science. However, due to the complicated high-dimensional component-property relationship, tuning material properties by researchers’ experience is challenging, even when guided by physical or empirical rules. Here, we adopt quantum computing (QC) technology and machine learning models to provide a proof-of-concept application of QC in physical metallurgy. We propose a quantum support vector machine (QSVM) model to predict single-phase CCAs. We show that fine-tuned quantum kernels with entanglement deliver promising performance, with a maximum accuracy of 89.4%. The QSVM model is then used to identify 1,741 lightweight CCAs jointly with a new text-mining-based method. Meanwhile, we devise a controllable approach to study the effect of noise on model performance and find that the noise level needs to be minimized for high-performance QSVM models. Finally, this study provides a practical and general approach to designing CCAs based on quantum technologies.
A structural underpinning of the lower critical solution temperature (LCST) behavior behind temperature-switchable liquids
In this work, we use state-of-the-art X-ray scattering and molecular dynamics to analyze amine-water mixtures that show the unusual lower critical solution temperature (LCST) behavior. The goal is to provide direct experimental evidence for the entropy-lowering molecular cluster formation hypothesized as necessary for LCST behavior. Differential wide-angle X-ray scattering and pair distribution analysis and small-angle X-ray scattering measurements were combined with molecular modeling and liquid-liquid equilibrium measurements, revealing direct experimental evidence for the hypothesis. However, the response of the amine phase to accommodating water is even more subtle than the simple hypothesis suggests, with the formation of robust nanoscale reverse micelles. The techniques developed in this paper can be expected to yield insights in the use of temperature-switchable liquids in solvent extraction and other separations, and the stabilization of organelles in living cells that do not have physical membranes but do require compositional gradients to operate.