本研究針對球形蛋白質溶菌酶(lysozyme)溶液，在固定鹽類濃度(2wt% NaCl)及緩衝溶液濃度(0.1M)下研究其聚集行為。首先，先利用平均場理論進行相圖的模擬，並使用光學顯微鏡觀測其形態及曇點測定儀量測其曇點溫度，最終將曇點與理論相圖進行對應。結果明顯指出，利用理論式來描述的biondal 曲線與實驗數據有相當大的落差。而在液-固共存區裡，不同蛋白質濃度在25°C隨著濃度的增加其結構由初始的單晶轉變成為海膽型與單晶並存的情況。
此外在小角光散射分析中，我們固定蛋白質濃度15g/dl且溫度選定為0°C及-4°C。藉由小角光散射的實驗分析結果發現，0°C下，散射pattern由初始的mono-decay轉而在q = 1.3左右有散射環產生；而在-4°C下，則發現了散射環，且隨著時間增加，peak的強度不斷上升且位置不斷的朝low q位移，這種行為相當類似於Spinodal Decomposition中後期規則。經進一步分析後，結果指出，並無法使用相分離動力學來針對聚集行為進行描述，系統行為傾向為利用分形聚集來形成最終結構。我們藉由Chan的線性理論來求得25秒前系統初始形成cluster的尺寸，且系統特徵尺寸隨時間的變化關係為q_m~t^(-d_f )，利用此式外推至t=25s，亦符合線性理論的預測。利用散射數據分析的結果，推測在當達到實驗溫度後，蛋白質分子由於屏蔽作用而產生大量的cluster，導致系統背景強度不斷的上升，隨著cluster彼此間不斷的碰撞而形成更大的集團，直至系統中已形成網路結構後，特徵尺寸的成長關係轉向為q_m~t^(-0.5)。在強度分析部份，初始強度的貢獻來自於cluster不斷的形成以及cluster不斷的碰撞成長，因此在一開始強度隨時間增加相當快速，當系統主要結構形成後，散射強度的貢獻來自於網路結構的粗化，因此成長緩慢。

In this study, we investigated aggregation phenomenon in protein solution which is fixed salt concentration (2wt% NaCl) and buffer solution concentration (0.1M). We establish complete composition-temperature phase diagram and used small angle light scattering to investigate the aggregate kinetics. Liquid-solid phase transition was recorded by POM and liquid-liquid phase separation was investigated through measuring cloud point temperature. We used van’t Hoff equation to fit supersaturated curve. Our result implies that the binodal curve which is simulated by mean-field theory was not suitable in our system because in critical region, the binodal curve was more likely toward Ising model.
Small angle light scattering results show that the scattering patterns changed in 0°C. The scattering intensity profile initially appeared mono-decay distribution until 500s.Then the scattering peak which did not shift in high q region emerged between 500s and 1500s. However, the scattering intensity in low q region increased with time, and finally it was too high to cover up the scattering peak; the peak disappeared. In -4°C, we find that the scattering pattern exhibits a finite-q-vector peak, whose intensity and position qm changed with time and the intensity distributions scale according to F(q/qm)=qm(t)-dfF(q/qm). This relationship is in agreement with dynamic scaling law for spinodal decomposition. While d=3 for spinodal decomposition, and d=df for the fractal dimension of the clusters. Finally, we create a aggregate model to describe this system.

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