ISIS Neutron and Muon Source Data Journal

This is a page describing data taken during an experiment at the ISIS Neutron and Muon Source. Information about the ISIS Neutron and Muon Source can be found at https://www.isis.stfc.ac.uk.


Using contrast matching to understand multicomponent gels

Abstract: Gels can be formed when a molecule self-assembles into fibres that entangle to immobilise the solvent. These tgels are really useful for applications from cell culturing to optoelectronics. The range of properties can be extended using multicomponent systems. In our systems, two different molecules self-assemble independently into different fibres. Characterising and understanding this is difficult - both fibres scatter in SANS for example and so differentiating the different networks is extremely challenging. To get around this, here we will use hydrogenated and deuterated gelators. In a mixture of a hydrogenated and a deuterated molecule, only the fibres formed from the hydrogenated molecule will scatter and so we will be able to see whether the fibres and networks formed in single and multicomponent systems are the same. This will greatly add to our undertsanding of these systems.

Principal Investigator: Professor Dave Adams
Experimenter: Miss Lisa Thomson
Local Contact: Dr James Doutch
Experimenter: Professor Emily Draper
Experimenter: Miss Rebecca Randle
Experimenter: Miss Ana Maria Fuentes Caparrós

DOI: 10.5286/ISIS.E.RB2010039

ISIS Experiment Number: RB2010039

Part DOI Instrument Public release date Download Link
10.5286/ISIS.E.RB2010039-1 ZOOM 05 June 2024 Download

Publisher: STFC ISIS Neutron and Muon Source

Data format: RAW/Nexus
Select the data format above to find out more about it.

Data Citation

The recommended format for citing this dataset in a research publication is as:
[author], [date], [title], [publisher], [doi]

For Example:
Professor Dave Adams et al; (2021): Using contrast matching to understand multicomponent gels, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB2010039

Data is released under the CC-BY-4.0 license.



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