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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

Cross-field and parallel dynamics of SOL filaments in TCV

Using recently installed scrape-off layer diagnostics on the tokamak à configuration variable, we characterise the poloidal and parallel properties of turbulent filaments. We access both attached and detached divertor conditions across a wide range of core densities (f G ϵ [0.09, 0.66]) in diverted L-mode plasma configurations. With a gas puff imaging (GPI) diagnostic at the outer midplane we observed filaments with a monotonic increase in radial velocity (from 390 m s –1 to 800 m s –1 ) and cross-field radii (from 8.5 mm to 13.4 mm) with increasing core density. Interpreting the filament behaviour in the context of the two-region model, we find that they populate the ideal-interchange regime (C i ) in discharges at very low densities, and the resistive X (RX)-point regime for all other discharges. The scaling of filament velocity versus size shows good agreement with this interpretation. These results are discussed and compared with previous probe-based measurements for similar conditions, which mostly placed filaments in TCV in the resistive ballooning (RB) regime. In addition, for the first time in TCV, the parallel filament extension is studied by magnetically aligning the GPI measurements at the outboard midplane with a reciprocating probe in the divertor. In agreement with the filaments being in the ideal-interchange and the RX-point regimes, they are found to extend beyond the X-point into the outer divertor leg.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Fast and Scalable Synthesis of LiNi 0.5 Mn 1.5 O 4 Cathode by Sol–Gel-Assisted Microwave Sintering

High-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) is a promising cathode material for high-energy-density and high-power-density lithium-ion batteries (LIBs). The high cost of the currently available LIBs needs to be addressed urgently for wide application in the transport sector (electric vehicles, buses) and large-scale energy storage systems (ESS). Of significance, herein, novel fast and scalable microwave-assisted synthesis of LNMO is reported, which leads to a production cost cut. X-ray diffraction (XRD) analysis confirms the formation of the desired phase with high crystallinity. Field emission scanning (FE-SEM) and transmission electron microscopy (TEM) analyses indicate that the synthesized phase is of nanometric size (50–150 nm) due to an extremely short sintering time (20 min). The material synthesized at 750 °C shows a higher initial discharge capacity (130 mA h g -1 ) than that synthesized at 650 °C (115 mA h g -1 ). The materials heat treated at higher temperatures show better electrochemical performance in terms of initial capacity, rate capability, and improved cycling. The improved electrochemical performance of LNMO at 750 °C is attributed to the formation of a stable crystal structure, low charge transfer resistance at the electrode/electrolyte interface, high electrical conductivity due to the presence of a disorder structure, and improved ionic diffusivity.

25 ENERGY STORAGE↗
DOE OSTI2022

Sol-gel processing of a covalent organic framework for the generation of hierarchically porous monolithic adsorbents

Covalent organic frameworks (COFs) have emerged as a versatile material platform for such applications as chemical separations, chemical reaction engineering, and energy storage. Their inherently low mechanical stability, however, frequently renders existing methods of pelletization ineffective, contributing to pore collapse, pore blockage, or insufficient densification of crystallites. Here, we present a process for the shaping and densifying of COFs into robust centimeter-scale porous monoliths without the need for templates, additives, or binders. This process minimizes mechanical damage from shear-induced plastic deformation and further provides a network of interparticle mesopores that we exploit in accessing analyte capacities above those achievable from the intrinsic COF structure. Using a lattice-gas model, we accurately capture the monolithic structure across the mesoporous range and tie pore architecture to performance in both gas-storage and -separation applications. Collectively, these results represent a substantial step in the practical applicability of COFs and other mechanically weak porous materials.

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

Chemical Amplification of Subthreshold Base Triggers To Drive Sol–Gel Transitions in Polymers

Chemical amplification has been widely applied in applications ranging from stimuli sensing to advanced photoresists, but it is rarely utilized to drive productive mechanical property changes. Here, we demonstrate the use of a base amplifier to drive the gelation of a functional polymer solution, in response to a subthreshold base trigger through a mechanism whereby the trigger drives a dramatic increase in the base concentration driven by base amplification, resulting in complexation of Fe(III) and polymer-bound catechol groups and subsequent gelation of the polymer solution. Furthermore, the concomitant crystallization of dibenzofulvene, which is a byproduct of base amplification, led to significant stiffening of the resultant gel and an unexpected temperature-sensitive change of gel stiffness.

Aromatic compounds↗
DOE OSTI2026

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗