离子溶剂中纤维素纺丝流变光学演化的快速原位定量
Rapid in-situ quantification of rheo-optic evolution for cellulose spinning in ionic solvents
AI总结：
本研究针对纺织纺丝原位测量难题，搭建带偏振显微镜的微型湿法纺丝系统，结合特征追踪与三维流变模型，实现纤维素/离子液体溶液纺丝过程的流变光学演化原位定量，可无损预测纺丝性能。
摘要：
监测复杂流体形变过程中的结构演化对优化包括纺织纺丝在内的众多制造工艺至关重要。然而，纺织纺丝过程的原位测量面临着无损检测仪器匮乏以及测量数据难以解读的问题。本研究中，在配备定制偏振显微镜的微型湿法纺丝线上，当纤维在水相介质中再生时，同时测量了纤维素/离子液体溶液的动力学与流变光学特性。该系统可控制关键纺丝参数，同时实时采集并处理纺制纤维的几何与结构信息。我们通过特征追踪方法识别出凝固过程中形变纤维的复杂流动运动学，并可视化了不同拉伸比和停留时间下，纤维再生前及再生过程中的形貌与双折射响应。同时，本研究采用三维物理流变模型来描述包含剪切流与拉伸流的复杂湿法纺丝过程中的非线性粘弹性行为。随后，我们将凝固过程中纤维的双折射响应与流变模型推断出的瞬态取向进行对比，明确了不同纺丝条件下存在叠加的结构-光学关系。从纺丝原液流动动力学推断出的此类结构表征，可与完全再生纤维的关键力学性能直接关联，从而能够以无损方案预测纺丝性能。
英文摘要：
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.
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