GRATEV2.0: Computational Tools for Real-time Analysis of High-throughput High-resolution TEM (HRTEM) Images of Conjugated Polymers

TL;DR

GRATEV2.0 is an open-source, real-time computational framework that automates high-throughput analysis of HRTEM images of conjugated polymers, enhancing efficiency and reproducibility in nanoscale material characterization.

Contribution

It introduces a novel, GPU-compatible, Gaussian process-optimized analysis tool with a Wasserstein distance-based stopping criterion for high-throughput TEM data processing.

Findings

Enables rapid extraction of structural features from TEM images.

Reduces manual parameter tuning through Gaussian process optimization.

Optimizes data collection time with a Wasserstein distance-based stopping rule.

Abstract

Automated analysis of high-resolution transmission electron microscopy (HRTEM) images is increasingly essential for advancing research in organic electronics, where precise characterization of nanoscale crystal structures is crucial for optimizing material properties. This paper introduces an open-source computational framework called GRATEV2.0 (GRaph-based Analysis of TEM), designed for real-time analysis of HRTEM data, with a focus on characterizing complex microstructures in conjugated polymers, illustrated using Poly[N-9'-heptadecanyl-2,7-carbazole-alt-5,5-(4',7'-di-2-thienyl-2',1',3'-benzothiadiazole)] (PCDTBT), a key material in organic photovoltaics. GRATEV2.0 employs fast, automated image processing algorithms, enabling rapid extraction of structural features like d-spacing, orientation, and crystal shape metrics. Gaussian process optimization rapidly identifies the user-defined parameters in the approach, reducing the need for manual parameter tuning and thus enhancing reproducibility and usability. Additionally, GRATEV2.0 is compatible with high-performance computing (HPC) environments, allowing for efficient, large-scale data processing at near real-time speeds. A unique feature of GRATEV2.0 is a Wasserstein distance-based stopping criterion, which optimizes data collection by determining when further sampling no longer adds statistically significant information. This capability optimizes the amount of time the TEM facility is used while ensuring data adequacy for in-depth analysis. Open-source and tested on a substantial PCDTBT dataset, this tool offers a powerful, robust, and accessible solution for high-throughput material characterization in organic electronics.