Enabling data-driven design of block copolymer self-assembly

Published

June 21, 2025

Author(s)

Chiara Magosso, Irdi Murataj, Michele Perego, Gabriele Seguini, Debra Audus, Gianluca Milano, Federico Ferrarese Lupi

Abstract

Abstract Here we present a database composed of scanning electron microscope images of self-assembled block copolymers. The fabrication process parameters, structural properties and microscope information are all contained in the image metadata, making a group of images a database on its own. This approach has numerous advantages including ease of sharing, reusability of information and resilience against user errors. This database follows the digital International System of Units principles and is complemented by a graphical user interface for process metadata insertion and an automated algorithm for image analysis to retrieve structural properties of the nanostructures. Databases such as this one, together with data-driven approaches, enable users to rationally design new materials with the desired properties by understanding the relationship between fabrication parameters and material structure. The here reported database, that contains around 1747 images of lamellar phase and lying down cylinders self-assembled block copolymers along with associated metadata, is structured so it can be continuously expanded by the research community including also samples with different block copolymers morphologies.

Citation

Scientific Data

Volume

12

Issue

1

Pub Type

Journals

Download Paper

https://doi.org/10.1038/s41597-025-05379-w

Local Download

Keywords

block copolymer, database, automation

Citation

Magosso, C. , Murataj, I. , Perego, M. , Seguini, G. , Audus, D. , Milano, G. and Ferrarese Lupi, F. (2025), Enabling data-driven design of block copolymer self-assembly, Scientific Data, [online], https://doi.org/10.1038/s41597-025-05379-w, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=958669 (Accessed August 24, 2025)