five

Temperature-Dependent Pyrolysis of Polyamide–Polyethylene Multilayer Films: Yields, Monomer Recovery, and Product Boiling Range

收藏
Figshare2025-08-21 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Temperature-Dependent_Pyrolysis_of_Polyamide_Polyethylene_Multilayer_Films_Yields_Monomer_Recovery_and_Product_Boiling_Range/29964265
下载链接
链接失效反馈
官方服务:
资源简介:
Multilayer plastics (MLPs) are widely used in packaging due to their multifunctional properties. For example, PA (polyamide) offers excellent oxygen and mechanical barriers, which are critical for demanding applications. However, the complex structure makes MLP difficult to recycle conventionally, often leading to its disposal through incineration. This study focuses on the pyrolysis of PA-6 (polyamide-6)/LDPE (low-density polyethylene) multilayer film where blends in a range of 3–15 wt % PA-6 were experimentally tested in a temperature range of 500–600 °C in a laboratory-scale pyrolysis unit, with the aim to better understand how PA-6 in the feedstock behaves and affects properties such as yield, product composition, and boiling point distribution. Experimental study revealed that the presence of PA-6 had a small increase on the condensable yield (maximum yield (92.6 wt %) was achieved with PA-6 share of 15 wt % and 526 °C). In addition, PA-6 led to an increase in the CO yield and interacted with temperature with components such as methane and ethylene. As expected, increasing the PA-6 share led to a rise in nitrogen (up to 1.5 wt %) and a decrease in hydrogen concentrations in the products in a nonlinear manner. In addition, the main degradation product of PA-6, ε-caprolactam, was steadily increased as a function of PA (up to 5 wt %) but not affected by the change in temperature. The simulated distillation curve was modeled after the PCA-R method, which revealed that temperature and PA-6 square are key factors on dictating the boiling point distribution.
创建时间:
2025-08-21
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作