Predicting morphologies of solution processed polymer:fullerene blends.

Area of Science:

• Materials Science
• Organic Electronics
• Photovoltaics

Background:

• Polymer:fullerene thin films are key to organic photovoltaic cells.
• Morphology control during film drying is crucial for device performance but poorly understood.
• Predicting optimal processing conditions for high-performance devices remains a challenge.

Purpose of the Study:

• To develop a predictive model for morphology formation in polymer:fullerene blends.
• To understand the influence of drying processes on blend nanostructure.
• To correlate morphology with photovoltaic device performance.

Main Methods:

• Experimental study of polymer:fullerene blends (PDPP5T:[70]PCBM) cast from chloroform.
• Development of a thermodynamic model based on Flory-Huggins free energy and interfacial interactions.
• Analysis of spinodal liquid-liquid demixing during film drying.

Main Results:

• Spinodal liquid-liquid demixing during drying drives the observed blend morphologies.
• Model predicts increasing feature size with drying time.
• Model predicts decreasing fullerene concentration in the polymer matrix with increasing drying time.

Conclusions:

• The developed model accurately predicts morphology evolution during film drying.
• Understanding drying-induced demixing is critical for optimizing photovoltaic performance.
• This work represents a foundational step towards predictive modeling of morphology in organic electronics.