📣 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.

Ground-Based Remote Sensing and Machine Learning for in Situ and Noninvasive Monitoring and Identification of Salts and Moisture in Historic Buildings (2025)

First Author: Kogou S

Attributed to: AI for DIGILAB: A New Concept in Digital Infrastructure for Heritage Materials Research funded by FIC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1021/acs.analchem.4c05581

Publication URI: http://dx.doi.org/10.1021/acs.analchem.4c05581

Type: Journal Article/Review

Parent Publication: Analytical Chemistry