Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
173 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Rapid in-situ quantification of rheo-optic evolution for cellulose spinning in ionic solvents (2303.08573v1)

Published 15 Mar 2023 in physics.app-ph, physics.flu-dyn, and physics.optics

Abstract: It is critical to monitor the structural evolution during deformation of complex fluids for the optimization of many manufacturing processes, including textile spinning. However, in situ measurements in a textile spinning process suffer from paucity of non-destructive instruments and interpretations of the measured data. In this work, kinetic and rheo-optic properties of a cellulose/ionic liquid solution were measured simultaneously while fibers were regenerated in aqueous media from a miniature wet spinline equipped with a customized polarized microscope. This system enables to control key spinning parameters, while capturing and processing the geometrical and structural information of the spun fiber in a real-time manner. We identified complex flow kinematics of a deformed fiber during the coagulation process via feature tracking methods, and visualized its morphology and birefringent responses before and during regeneration at varying draw ratios and residence time. Meanwhile, a three-dimensional physical rheological model was applied to describe the non-linear viscoelastic behavior in a complex wet-spinning process incorporating both shear and extensional flows. We subsequently compared the birefringent responses of fibers under coagulation with the transient orientation inferred from the rheological model, and identified a superposed structure-optic relationship under varying spinning conditions. Such structural characterizations inferred from the flow dynamics of spinning dopes are readily connected with key mechanical properties of fully-regenerated fibers, thus enabling to predict the spinning performance in a non-destructive protocol.

Summary

We haven't generated a summary for this paper yet.