📣 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.

Cements and concretes materials characterisation using machine-learning-based reconstruction and 3D quantitative mineralogy via X-ray microscopy. (2024)

First Author: Mitchell RL

Attributed to: An X-ray Micro-Computed Tomography Facility with in-situ/in operando testing. funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1111/jmi.13278

PubMed Identifier: 38454801

Publication URI: http://europepmc.org/abstract/MED/38454801

Type: Journal Article/Review

Volume: 294

Parent Publication: Journal of microscopy

Issue: 2

ISSN: 0022-2720