Long Term Goals

• Establish a data structure for the quantification of Poly-3-hexylthiophene (P3HT) thin film morphology

Data

1. AFM <– Structure
2. UV-Vis absorbance spectra
3. Electrron Mobility <– Property

Thresholding to 1. Identify fibers

The thresholding post discusses our algorithm for finding the perfect thresholding value to isolate individual fibers. The following image shows a brief example of our work.

Spatial Statistics

##Work Flow: For each of the 16 stuctures:

1. Created a binary image with thresholding (amorphous or crystaline fiber…no orientation information)
2. Applied the SpatialStatsFFt Matlab function.

An exapmle of the above AFM image autocorrelation result: with a reasonable volume fraction of ~0.32

1. Perform PCA using matlab functions.

An example of our sanity check:

Digging into the data a little bit: Here are the coefficients of the 1st PC

1. Perform perliminary analysis of electron mobility and 1st PC scores.

What have we learned?

• Longer and wider fibers are favorable for charge transport
• More fibers are not necessarily a good thing if they are small and siconnected

Why this matters?

• co-solvent addition is scalable processing method to achieve better charge transport
• we should study how and why fibers space themselves out: what is happening in teh space between? can we achieve morphologies that explore this domain?

Still in progress and future work

-Developing a method for obtaining orientations and need to incorparate into the spatial statistics and PCA.

-Possibly incoorparate degree of crytallinity.

-We have incorparated UV-Vis absorbance spectra in the PCA but need to better undestand this.