半晶体热塑性树脂的结晶形态模拟和力学性能预测方法
By combining an improved cellular automata algorithm with a fast Fourier transform method, efficient prediction of the crystallization morphology and mechanical properties of semi-crystalline thermoplastic resins is achieved. This solves the problem of unclear relationship between crystallization conditions and mechanical properties in existing technologies and provides guidance for material design.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG ZHUJI NEW MATERIAL TECH CO LTD
- Filing Date
- 2022-06-20
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot efficiently and accurately establish the relationship between the crystallization conditions of semi-crystalline thermoplastic resins and their structure and mechanical properties after crystallization, thus failing to achieve a deep understanding of the material's mechanical properties.
An improved cellular automata algorithm was used to establish a semi-crystalline resin crystal growth model, and the mechanical properties of spherulite structures were numerically simulated using the fast Fourier transform method. The crystal structure and mechanical properties after crystallization were predicted by the spherulite growth rate and nucleation rate.
This paper presents an efficient and accurate numerical calculation method that can predict the mechanical properties of semi-crystalline resins under different crystallization conditions. It is low-cost, simple to operate, and can guide material design.
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Figure CN115203901B_ABST