本文提出一種通過第一原理計算與分子動力學來模擬不同半導體光催化劑的性質，建立一套能夠觀察與分析微觀尺度下分子間作用情形之方法。近年來，光催化水分解技術因其能夠將豐富的太陽能轉化為零排放的氫氣，被廣泛地研究和關注。
在近期的研究中發現，透過主鏈工程策略將親水非共軛結構單元與疏水性共軛結構單元結合成主鏈工程型非連續共軛高分子，可成為一種有效改善傳統共軛高分子聚合物主鏈之疏水性的方法，進而提升光催化產氫系統之產氫效率。而在化學、材料和生物等許多領域，分子模擬是一種非常重要的方法，可以模擬和分析分子的結構和性質等物理量。通過分子模擬所獲得的數據，我們可以研究物質在微觀尺度上的作用機制，並將其應用於共軛高分子材料開發和性質預測等多種用途。
在本研究中，我們通過第一原理計算中的密度泛涵理論、Natural population analysis，計算出不同設計下的高分子光催化劑周圍的活性位點並觀察分子在基態和激發態下的電子分佈。然後透過分子動力學模擬中的動態模擬，分析軌跡文件以獲得徑向分佈函數與動態氫鍵密度。我們利用這些數據預測氫鍵形成的機率，並進一步驗證了主鏈工程可以增加水和聚合物之間相互作用的可能性。
本文通過第一原理計算與分子動力學來模擬不同高分子光催化劑的性質，透過多樣化的高分子光催化劑模型與不同模擬環境的設計，建立一套能夠觀察與分析微觀尺度下分子間作用情形之方法，提供一種能夠有效地設計和優化高分子光催化劑的方法，並為未來的相關研究提供了基礎。

This study combines first-principles calculations and molecular dynamics to simulate the properties of various semiconductor photocatalysts. This approach establishes a framework for observing and analyzing molecular interactions at the microscopic scale. In recent years, photocatalytic water-splitting technology has received extensive research and attention due to its ability to convert abundant solar energy into zero-emission hydrogen gas.
Previous studies have shown that employing a main-chain engineering strategy, which involves combining hydrophilic non-conjugated structural units with hydrophobic conjugated structural units, can effectively enhance the hydrophobicity of traditional conjugated polymer main chains, thereby improving the hydrogen production efficiency of photocatalytic systems. In various fields such as chemistry, materials science, and biology, molecular simulation plays a crucial role in enabling the simulation and analysis of molecular structures and properties. The data obtained through molecular simulations allow us to investigate the mechanisms of molecular interactions at the microscopic scale and apply them to the development and prediction of properties of conjugated polymer materials.
In this research, we utilized density functional theory and natural population analysis in first-principles calculations to determine the active sites surrounding various designs of polymeric photocatalysts. We also examined the electron distribution of molecules in their ground and excited states. Subsequently, molecular dynamics simulations were used to analyze trajectory files and obtain radial distribution functions and dynamic hydrogen bond densities. Based on this data, we predicted the probability of hydrogen bond formation and further validated the potential of main-chain engineering in enhancing the interactions between water and polymers. We have developed a method to observe and analyze molecular interactions at the microscopic scale. This approach provides an effective method for designing and optimizing polymeric photocatalysts, laying the groundwork for future research in this field.

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