Structural Basis for the Regulation of Biofilm Formation and Iron Uptake in A. baumannii by the Blue-Light-Using Photoreceptor, BlsA
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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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To recycle the mixed plastic wastes (MPW), it is important to obtain the compositional information online in real time. We present a sensing framework based on a convolutional neural network (CNN) and mid-infrared spectroscopy (MIR) for the rapid and accurate characterization of MPW. The MPW samples are placed on a moving platform to mimic the industrial environment. The MIR spectra are collected at the rate of 100 Hz, and the proposed CNN architecture can reach an overall prediction accuracy close to 100%. Therefore, the proposed method paves the way toward the online MPW characterization in industrial applications where high throughput is needed.
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Past studies have indicated that El Nino-Southern Oscillation (ENSO) plays a major role in the interannual variability of Eastern Pacific hurricane activity. The primary mechanism being the eastward displacement of the warm pool during an El Nino, which carries warm water into that basin thereby creating favorable oceanic conditions. Despite this, the question of whether an accurate knowledge of ENSO enhances seasonal predictabiity of Eastern Pacific hurricanes has not been addressed specifically. In this study, we show that unlike traditional indices of ENSO, the ENSO Longitude Index (ELI) is able to predict Eastern Pacific hurricane activity at significant lead times. By capturing changes in the location of deep convection and associated thermocline processes more accurately, ELI explains the most variability in the upper-ocean heat content in the main development region of the Eastern Pacific basin compared to other ENSO indices. These results have substantial implications for operational seasonal forecasts of Eastern Pacific hurricanes.
The quality of the solid–electrolyte interphase is crucial for the performance of most battery chemistries, but its formation dynamics during operation are not well understood due to a lack of reliable operando characterization techniques. Herein, we report a dynamic, non-invasive, operando reflection interference microscope to enable the real-time imaging of the solid–electrolyte interphase during its formation and evolution processes with high sensitivity. The stratified structure of the solid–electrolyte interphase formed during four distinct steps includes the emergence of a permanent inner inorganic layer enriched in LiF, a transient assembly of an interfacial electrified double layer and a consequent emergence of a temporary outer organic-rich layer whose presence is reversible with electrochemical cycling. Reflection interference microscope imaging reveals an inverse correlation between the thicknesses of two interphasial subcomponents, implying that the permanent inorganic-rich inner layer dictates the organic-rich outer layer formation and lithium nucleation. In conclusion, the real-time visualization of solid–electrolyte interphase dynamics provides a powerful tool for the rational design of battery interphases.
Abstract Lattice and electronic structure interactions for f -electrons are fundamental challenges for lanthanide equation of state development. Difficulties in first-principles calculations, such as density functional theory (DFT), emphasize the need for well-characterized experimental data. Here, we measure in-situ x-ray diffraction of shocked samarium (Sm) and temperature along the Hugoniot for the first time, providing direct evidence for phase transitions. We report direct evidence of a distorted fcc (dfcc) phase at 23 GPa. Shocked samarium melts from the dfcc phase starting at 33 GPa (1333 K), with complete melt at 40 GPa (1468 K). Previous work indicated shock melt at 27 GPa (1200 K), underscoring the significance of x-ray measurements for detecting phase transitions. Interestingly, our observed melting is in sharp contrast with the melting reported by a diamond anvil cell study. These experimental data can tightly constrain first principles calculations and serve as key touchstones for equation of state modeling.
A quarter of Earth's land surface is covered by porous sedimentary silicate rocks, so silica–water interfaces are critical to the fate and transport of chemical species on a global-scale.
A protective tin oxide layer formed by atomic-layer deposition limits surface recombination at n-Si surfaces and produces ∼620 mV of photovoltage on planar n-Si photoanodes. The layer conformally coats structures such as Si microcone arrays.
A general synthesis method is demonstrated for producing PdM (M= Ag, Cu, Ni, and Y) nanowire networks. As a prototypical application, these nanowires are incorporated into polybenzimidazole to create mixed matrix membranes for H 2 /CO 2 separation.
Mitochondria are crucial regulators of the intrinsic pathway of cancer cell death. The high sensitivity of cancer cells to mitochondrial dysfunction offers opportunities for emerging targets in cancer therapy. Herein, magnetic nano-transducers, which convert external magnetic fields into physical stress, are designed to induce mitochondrial dysfunction to remotely kill cancer cells. Spindle-shaped iron oxide nanoparticles were synthesized to maximize cellular internalization and magnetic transduction. The magneto-mechanical transduction of nano-transducers in mitochondria enhances cancer cell apoptosis by promoting a mitochondrial quality control mechanism, referred to as mitophagy. Furthermore, in the liver cancer animal model, nano-transducers are infused into the local liver tumor via the hepatic artery. After treatment with a magnetic field, in vivo mitophagy-mediated cancer cell death was also confirmed by mitophagy markers, mitochondrial DNA damage assay, and TUNEL staining of tissues. This study is expected to contribute to the development of nanoparticle-mediated mitochondria-targeting cancer therapy and biological tools, such as magneto-genetics.
Organosolv treatment is an environmentally friendly fractionation method that affords a lignin stream with high purity.
Uniform size of Si nanowires (NWs) is highly desirable to enhance the performance of Si NW-based lithium-ion batteries.
Atomically dispersed Cu catalyst was designed for highly efficient hydroxylation of aryl iodides under mild conditions.
Characterization of metal centers in metal–organic frameworks (MOFs) is critical for rational design and further understanding of structure–property relationships. The short-range structure about Zr atoms is challenging to properly elucidate in many Zr MOFs, particularly when local disorder is present. Static 91 Zr solid-state NMR spectra of the seven zirconium MOFs UiO-66, UiO-66-NH 2 , UiO-67, MOF-801, MOF-808, DUT-68 and DUT-69 have been acquired at high magnetic fields of 35.2 T and 19.6 T, yielding valuable information on the local structure, site symmetry and order about Zr. 91 Zr NMR is very sensitive to differences in MOF short-range structure caused by guest molecules, linker substitution and post-synthetic treatment. Complementary density functional theory (DFT) calculations assist in the interpretation and assignment of 91 Zr solid-state NMR spectra, lend insight into structural origins of 91 Zr NMR parameters and enable determination of local Zr coordination environments. This approach can be extended to many other materials containing zirconium.
In the past few decades, prediction of macromolecular structures beyond the native conformation has been aided by the development of molecular dynamics (MD) protocols aimed at exploration of the energetic landscape of proteins. Yet, the computed structures do not always agree with experimental observables, calling for further development of the MD strategies to bring the computations and experiments closer together. Here, we report a scalable, efficient MD simulation approach that incorporates an x-ray solution scattering signal as a driving force for the conformational search of stable structural configurations outside of the native basin. We further demonstrate the importance of inclusion of the hydration layer effect for a precise description of the processes involving large changes in the solvent exposed area, such as unfolding. Utilization of the graphics processing unit allows for an efficient all-atom calculation of scattering patterns on-the-fly, even for large biomolecules, resulting in a speed-up of the calculation of the associated driving force. The utility of the methodology is demonstrated on two model protein systems, the structural transition of lysine-, arginine-, ornithine-binding protein and the folding of deca-alanine. We discuss how the present approach will aid in the interpretation of dynamical scattering experiments on protein folding and association.
The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.