Data and Code For: Closing the Loop Between Microstructure and Charge Transport in Conjugated Polymers by Combining Microscopy and Simulation.

This repository contains the datasets and scripts used in the article "Closing the Loop Between Microstructure and Charge Transport in Conjugated Polymers by Combining Microscopy and Simulation." 

Contents:

4D-STEM data of the polymer PBTTT, annealed at 180C for 2h, vapor doped with the molecule F4TCNQ

• 3_80x80_ss=10nm_spot9_alpha=p48_cl=480_RT_300kV_33ms_bin=4.zip ("Scan 3", Main case study)
• 05 CL480 alpha p48 300kV spot11 50ms 80x80 s10.zip

4D-STEM data of the polymer PBTTT, annealed at 180C for 2h, undoped

• 10 A1 CL480 alpha p48 300kV spot11 50ms 80x80 s10.zip
• 15 A1 CL480 alpha p48 300kV spot11 50ms 80x80 s10.zip

Preprocessed data from "Scan 3."  Images are centered, artifacts are removed, and images are binned and converted to radial coordinates.

• 4D-STEM Preprocessed.zip
  • sample_preprocessed_data_80x80_ss=10_cl=480__q 1.00 3.00 0.05 a 5.00.npy (medium resolution, wide range, used in paper)
  • sample_data_cube_q_1.0_2.0_0.1_angle_5.npy (low resolution, narrow range)

Grazing-Incidence Wide-Angle X-ray scattering (GIWAXs) scan of annealed PBTTT, supporting our interpretation of the 4D-STEM data.

• 3 raw images
• Calibration files
• Combined processed image

Spatially resolved diffraction intensity mapped onto a spherical harmonic basis set, for use as an input to structural simulations. One for each of the four 4D-STEM datasets.

• spherical_harmonics.zip

Simulated structures of polymer chains based on the processed 4D-STEM data, created using code at https://github.com/SpakowitzLab/wlcsim. Each simulation produced 15 structures using different levels of chain alignment.

• chain_geometries.zip
  • main_dataset_03 (main case study)
  • hi_align_03 (3.3x higher alignment factors than main dataset)
  • undoped_10
  • undoped_15

Simulations of charge transport through the structures

• transport_simulations.zip
  • ct_16_n100 (explores structural modifications and their effects on mobility)
  • ct_18_n1000 (explores transport in all 4 directions and is used for making GIFs of simulations)
  • ct_20_n1000 (explores the effect of degree of chain alignment)
  • ct_28_n1000 (explores the effect of electric field strength)
  • ct_29_n100 (tracks distances of individual on-chain moves)
  • ct_30_n10000 (uses a high sample size and varied start positions to sample both short-time and long-time mobility)

Code for 4D-STEM analysis and simulations of charge transport. (Code for structural simulations can be found at https://github.com/SpakowitzLab/wlcsim).

• code.zip
  • preprocess_4dstem.py: package for preprocessing 4D-STEM files
  • flow_fields.py: package for visualizing 4D-STEM data using director maps
  • autocorrelation.py: package for measuring correlation lengths in 4D-STEM data via multiple methods
  • spherical_harmonics.py: package for mapping diffraction intensity onto a spherical harmonic basis set.  The results can be used as an input for structural simulations.  
  • charge_transfer_assets.py: package for performing charge transfer simulation on simulated chain coordinates
• examples.zip
  • preprocess_demo: sample usage for preprocess_4dstem.py
  • visualization_demo: sample usage for flow_fields.py, autocorrelation.py, and spherical_harmonics.py
  • charge_tranpsort_demo: sample usage for charge_transfer_assets.py
  • paper_figures: shows the code for producing several figures from the paper, using the included simulation datasets.