玻璃轉化溫度（Tg）對非晶質(amorphous)有機半導體的熱穩定性和形態穩定性具有重要的影響，尤其在有機發光二極體（organic light-emitting diode ,OLED）元件中，擁有較高Tg的材料會有較好的熱穩定性以延長器件的使用壽命，如果我們能成功預測材料的Tg，可避免合成出的材料不符合足夠高Tg的標準，加速開發具有足夠熱穩定的材料。
我們改善林昆翰教授等人開發的方法，用分子動力學模擬(molecular dynamics simulation, MD)進行有機小分子Tg的預測，該方法已證明具有一定的準確性。然而此方法對於一個分子的計算成本很高，限制了其在高通量篩選中的應用，因此本研究的第一個目標是維持此方法的預測準確度並且降低其計算成本。
我們將系統的大小分別從3000個分子（依據林昆翰教授等人的研究）減少到1500、750和375個分子，結果顯示對於林昆翰教授等人所預測的24個有機小分子以375個分子系統對同一個分子進行4次相同的MD模擬，Tg預測平均值可達到一定準確度（實驗值與預測值相比的平均絕對誤差約為18.66°C），同時由於系統分子數量的減少（只有林昆翰教授等人方法的1/8），其計算成本也大幅降低。
除了較高的計算成本這個缺點外，林昆翰教授等人的方法還有另一個缺陷，即實施MD前的力場參數化過程非常耗時，每個分子平均需要花費六個小時的人力成本，而這種高人力成本的消耗無法有效率地實施高通量篩選。因此，我們開發了以分子積木為概念的半自動生成分子力場的程式，以減少人力成本，並使用此程式建立了39個有機小分子的力場，並進行降低成本後的MD模擬預測 Tg，其預測值與實驗值相比，線性修正過後的平均絕對誤差為26°C。
我們除了開發一套快速預測Tg的方法外，也建立了一套半自動化建立分子力場的工具，可以快速且可靠的建立分子力場，用於其他類型的MD模擬中。

The glass transition temperature (Tg) significantly influences the thermal and morphological stability of amorphous organic semiconductors. In an OLED device, the host material with a high Tg is crucial to its lifetime. If we can successfully predict Tg, we can establish a pre-screening process for the development of high Tg material
The objective of this research is to provide reasonably accurate and cost-effective predictions for organic small molecules using MD simulations. We adopted the approach developed by Kun-Han Lin et al for predicting Tg using molecular dynamics simulation, which has demonstrated satisfactory accuracy. However, the method is computationally demanding, which prevents its use for high-throughput screening. Hence, we aim to reduce its computational cost while retaining its prediction power.
We gradually reduced the system size from 3000 molecules (Lin’s work) to 1500, 750, and 375 molecules. Our results show that reasonable Tg predictions (MAE: ~22 °C vs exp. values) with MD simulations of 375-molecule system size can be achieved by conducting the same simulation four times for each of the 24 organic small molecules. Meanwhile, the computational cost is significantly reduced due to the much smaller system size (only ⅛ of Kun-Han Lin’s protocol).
In addition to the high computational cost, Kun-Han Lin’s protocol has another shortcoming– the labor-demanding force-field parameterization process that is crucial for accurate Tg prediction. This step requires six hours of manual labor per molecule, posing a significant obstacle when implementing it in high-throughput screening. Therefore, we developed a semi-automated force-field parameterization scheme based on the concept of molecular building blocks to alleviate the human labor cost. Using this scheme, we established force fields for 39 organic small molecules and conducted MD simulations to predict Tg values. After correction, the predicted Tg values showed an MAE of 26 °C compared to the experimental values.
In addition to developing a rapid method for predicting Tg, we have also established semi-automated force-field parameterization scheme. This tool enables the quick and reliable creation of molecular force fields for use in MD simulations

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