April 22 - 26, 2024
Seattle, Washington
May 7 - 9, 2024 (Virtual)
Symposium Supporters
2024 MRS Spring Meeting
MT03.01.03

High-Throughput Structural Investigation of Block Copolymer and Conjugated Polymer Co-Assemblies

When and Where

Apr 23, 2024
11:30am - 11:45am
Room 322, Level 3, Summit

Presenter(s)

Co-Author(s)

Kiran Vaddi1,Karen Li1,Lilo Pozzo1

University of Washington1

Abstract

Kiran Vaddi1,Karen Li1,Lilo Pozzo1

University of Washington1
Conjugated polymers (CPs) have garnered much interest as semi-conducting materials for organic electronics. The properties of conducting polymers can be affected from induced long-range order. Block copolymers (BCPs) are commonly used as templating materials due to their ability to self-assemble into many crystalline structures. Blending structure directing BCPs and relatively rigid CPs may lead to materials with enhanced properties due to the formation of highly ordered structures. Thus, it is essential to understand the phase behavior of these co-assembled blends. The shape and order of these structures are also affected by many parameters including temperature, concentration, molecular weight, side chains, shear, etc. High-throughput characterization and analysis will be required to effectively investigate these factors. To demonstrate this, hydrogel blends of BCP polyethylene oxide-polypropylene oxide-polyethylene oxide and conjugated polyelectrolyte poly[3-(potassium-4-butanoate)thiophene-2,5-diyl] were prepared at varying concentrations with an open-source liquid handling robot. The polymer blends were structurally characterized through high-throughput small angle x-ray scattering (HT-SAXS), utilizing a custom cartridge system that can enable thousands of measurements per day at a synchrotron. In addition, various temperatures and shear conditions were applied to the polymer blends to produce monolithic oriented gels and measured via small angle neutron scattering (SANS). A statistical analysis tool, <i>autophasemap</i>, was developed in our group to automatically generate phase maps that provide a hierarchical summary of the HT-SAXS experiments. This is accomplished by measuring the similarity between sampled profiles and data-based template functions and clustering the profiles based on this similarity. Multiple ordered phases of the polymer blends were then identified through the presence and position of Bragg peaks in 1D profiles and Bragg spots in 2D profiles.

Keywords

polymer

Symposium Organizers

Keith Butler, University College London
Kedar Hippalgaonkar, Nanyang Technological University
Shijing Sun, University of Washington
Jie Xu, Argonne National Laboratory

Symposium Support

Bronze
APL Machine Learning
SCIPRIOS GmbH

Session Chairs

Chibueze Amanchukwu
Jie Xu

In this Session