使用InGaAs NIR光谱预测预硫乳的交叉链密度
Suntaree Dachapan1, Khwantri Saengprachatanarug1, Arthit Phuphaphud1
1Department of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand.
ACS omega
|February 23, 2026
概括
近红外 (NIR) 光谱学可以预测预硫化 (PV) 乳中的交叉链密度. 将NIR数据与工艺变量结合起来,可显著提高精度,从而在光伏乳制造中实现更快,非破坏性的质量控制.
科学领域:
- 聚合物科学 聚合物科学
- 频谱学是一种光谱学.
- 材料科学 材料科学 材料科学
背景情况:
- 交叉链密度对于预硫化 (PV) 乳特性至关重要.
- 准确预测交叉链密度对于光伏乳制造质量控制至关重要.
研究的目的:
- 评估近红外 (NIR) 光谱法用于预测光伏乳交叉链密度的可行性.
- 为此应用评估基于InGaAs的NIR仪器.
- 为增强的预测模型集成过程变量.
主要方法:
- 在960-1700nm范围内使用了两个InGaAs NIR光谱仪 (MicroNIR和AvaSpec).
- 使用光谱数据和工业过程变量开发了部分最小平方回归 (PLSR) 模型.
- 使用托卢膨胀指数 (TSI) 和预硫化放松模块 (PRM) 方法验证的交叉链密度.
主要成果:
- 仅使用NIR光谱的模型显示预测能力有限.
- 整合过程变量 (保持时间,乳等级) 显著提高了模型准确性.
- 基于TSI的模型优于PRM模型,TSI-3h是最可靠的.
- 非接触式MicroNIR实现了高精度 (R2=0.96对于TSI-3h).
结论:
- 将InGaAs的NIR光谱与工艺变量相结合,可以准确,快速和非破坏性地预测基于STI的交叉链密度.
- 无接触的NIR测量对于光伏乳制造非常实用.
- 这种方法为光伏乳的实时质量控制提供了显著的进步.
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