2023-01-012024-05-17https://scholars.lib.ntu.edu.tw/handle/123456789/671899此計劃目的在開發高效檢測平台，以為機器學習快速獲取足夠的實驗數據。該平台的主題包含用於PVDF膜改性和功能化以及膜分析系統的電漿處理製程。以機器學習進行電漿處理材料製程的分析是新穎且很少研究報導的。我們將使用多種膜測試技術與數種電漿系統, 包括大氣電漿、低壓電漿與微電漿, 利用該平台獲取的數據，將測試各種演算法，例如主成分分析，支持向量機和卷積神經網絡等。總目標是以有效的方式獲得多種應用所需的電漿處理條件。 This subproject aims for the development of an efficient data acquisition platform to rapidly obtain sufficient experimental data for machine learning. The central theme of this platform contains plasma treatment processes for PVDF membrane modification and functionalization and membrane analytical systems. Development of such a platform for plasma-based processes is novel and extremely important yet very little has been explored. We will integrate several plasma systems, namely atmospheric pressure plasmas, low pressure plasmas, and microplasmas, with multiple membrane testing techniques. With the data acquired by this platform, various algorithms such as principal component analysis, support vector machine, and convolutional neural network will be tested. The goal is to obtain desired plasma treatment condition for multiple applications in an efficient manner.電漿處理;機器學習;分離程序; 高速檢測平台;plasma treatment; machine learning; separation process; rapid detection platform