📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Extreme heterogeneity in the microrheology of lamellar surfactant gels analyzed with neural networks (2023)

First Author: Moore O

Attributed to: The Centre in Advanced Fluid Engineering for Digital Manufacturing (CAFE4DM) funded by UUI

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.48550/arxiv.2311.11941

Publication URI: https://arxiv.org/abs/2311.11941

Type: Preprint