Issue 27, 2025

Hacktive matter: data-driven discovery through hackathon-based cross-disciplinary coding

Abstract

The past decade has seen unprecedented growth in active matter and autonomous biomaterials research, yielding diverse classes of materials capable of flowing, contracting, bundling, de-mixing, and coalescing. These innovations promise revolutionary applications such as self-healing infrastructure, dynamic prosthetics, and self-sensing tissue implants. However, inconsistencies in metrics, definitions, and analysis algorithms across research groups, as well as the high-dimensionality of experimental data streams, has hindered the identification of performance intersections among such dynamic systems. Progress in this arena demands multi-disciplinary team approaches to discovery, with scaffolded training and cross-pollination of ideas, and requires new methods for learning and collaboration. To address this challenge, we have developed a hackathon platform to train future scientists and engineers in ‘big data’, interdisciplinary collaboration, and community coding; and to design and beta-test high-throughput (HTP) biomaterials analysis software and workflows. We enforce a flat hierarchy, pairing participants ranging from high school students to faculty with varied experiences and skills to collectively contribute to data acquisition and processing, ideation, coding, testing and dissemination. With clearly-defined goals and deliverables, participants achieve success through a series of tutorials, small group coding sessions, facilitated breakouts, and large group report-outs and discussions. These modules facilitate efficient iterative algorithm development and optimization; strengthen community and collaboration skills; and establish teams, benchmarks, and community standards for continued productive work. Our hackathons provide a powerful model for the soft matter community to educate and train students and collaborators in cutting edge data-driven analysis, which is critical for future innovation in complex materials research.

Graphical abstract: Hacktive matter: data-driven discovery through hackathon-based cross-disciplinary coding

Supplementary files

Transparent peer review

To support increased transparency, we offer authors the option to publish the peer review history alongside their article.

View this article’s peer review history

Article information

Article type
Tutorial Review
Submitted
21 Apr 2025
Accepted
17 Jun 2025
First published
18 Jun 2025

Soft Matter, 2025,21, 5381-5392

Hacktive matter: data-driven discovery through hackathon-based cross-disciplinary coding

M. T. Valentine and R. M. Robertson-Anderson, Soft Matter, 2025, 21, 5381 DOI: 10.1039/D5SM00401B

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements