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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Squeezing the periodicity of Néel-type magnetic modulations by enhanced Dzyaloshinskii-Moriya interaction of 4d electrons

In polar magnets, such as GaV 4 S 8 , GaV 4 Se 8 and VOSe 2 O 5 , modulated magnetic phases namely the cycloidal and the Néel-type skyrmion lattice states were identified over extended temperature ranges, even down to zero Kelvin. Our combined small-angle neutron scattering and magnetization study shows the robustness of the Néel-type magnetic modulations also against magnetic fields up to 2 T in the polar GaMo 4 S 8 . In addition to the large upper critical field, enhanced spin-orbit coupling stabilize cycloidal, Néel skyrmion lattice phases with sub-10 nm periodicity and a peculiar distribution of the magnetic modulation vectors. Moreover, we detected an additional single-q state not observed in any other polar magnets. Thus, our work demonstrates that non-centrosymmetric magnets with 4d and 5d electron systems may give rise to various highly compressed modulated states.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Squeezing the box: isoreticular contraction of pyrene-based linker in a Zr-based metal–organic framework for Xe/Kr separation

Isoreticular synthesis is a powerful tool to enhance specific attributes of a metal–organic framework (MOF). While the isoreticular expansion of MOF structure are prevalent in the literature, the compression of a topology holds great promise for separations due to the contracted pore apertures and/or cavities. Herein, we report the synthesis, characterization and Xe/Kr separation capability of a new Zr-based MOF, NU-1106, connected by the tetratopic linker 1,3,6,8-pyrene tetracarboxylate, which exhibits a compressed ftw topology compared to the extended ones reported previously. NU-1106 showed selective uptake of Xenon over Krypton, providing the potential for use for separations.

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

Nanoscale dynamics of Dynamin 1 helices reveals squeeze-twist deformation mode critical for membrane fission

Dynamin 1 (Dyn1) GTPase, a principal driver of membrane fission during synaptic endocytosis, self-assembles into short mechanoactive helices cleaving the necks of endocytic vesicles. While structural information about Dyn1 helix is abundant, little is known about the nanoscale dynamics of the helical scaffolding at the moment of fission, complicating mechanistic understanding of Dyn1 action. To address the role of the helix dynamics in fission, we used High-Speed Atomic Force Microscopy (HS-AFM) and fluorescence microscopy to track and compare the spatiotemporal characteristics of the helices formed by wild-type Dyn1 and its K44A mutant impaired in GTP hydrolysis on minimal lipid membrane templates. In the absence of nucleotide, membrane-bound WT Dyn1 and K44A Dyn1 self-assembled into tubular protein scaffolding of similar diameter encaging the lipid bilayer. In both cases, the GTP addition caused scaffold constriction coupled with formation of 20 to 30 nm nanogaps in the protein coverage. While both proteins reached scaffold diameters characteristic for membrane superconstriction causing fission, the fission was detected only with WT Dyn1. We associated the fission activity with the dynamic evolution of the nanogaps: K44A Dyn1 gaps were static, while WT Dyn1 gaps actively evolved via repetitive nonaxisymmetric constriction-bending deformations caused by localized GTP hydrolysis. Modeling of the deformations implicated filament twist as an additional deformation mode which combines with superconstriction to facilitate membrane fission. Our results thus show that the dynamics of the Dyn1 helical scaffold goes beyond radial constriction and involves nonaxisymmetric deformations, where filament twist emerges as a critical driver of membrane fission.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Utilizing machine learning to improve the precision of fluorescence imaging of cavity-generated spin squeezed states

We present a supervised learning model to calibrate the photon collection rate during the fluorescence imaging of cold atoms. The linear regression model finds the collection rate at each location on the sensor such that the atomic population difference equals that of a highly precise optical cavity measurement. This 192 variable regression results in a measurement variance 27% smaller than our previous single variable regression calibration. The measurement variance is now in agreement with the theoretical limit due to other known noise sources. This model efficiently trains in less than a minute on a standard personal computer's CPU and requires less than 10 min of data collection. Furthermore, the model is applicable across a large change in population difference and across data collected on different days.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗