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.


Fundamentals of molecular self-assembly in deep eutectic solvents (DES)

Abstract: Deep eutectic solvents (DES) are considered promising green solvents for future industrial formulations due to their biocompatibility, low cost, green production, and versatility as solvents. To fully unlock such potential, it is critical to understand molecular self-assembly of polymers and surfactants in DES, as they are ubiquitous in industrial formations - an area that is however currently little explored. Here, in collaboration with GSK Oral Health Division, we propose a first small-angle neutron scattering (SANS) study of self-assembled structures of ionic surfactants in glyceline, a DES. We will vary the surfactant molecular architecture (comparing cationic C12TAB and anionic SDS) as well as the surfactant concentration, and correlate these parameters with the structural information obtained.

Principal Investigator: Professor Wuge Briscoe
Experimenter: Miss Anna Slastanova
Experimenter: Miss Lauren Matthews
Experimenter: Miss Sarah Michel
Experimenter: Miss Zaneta Przybylowicz
Experimenter: Miss Silvia Ruscigno
Experimenter: Dr Robert Sochon
Local Contact: Dr Sarah Rogers

DOI: 10.5286/ISIS.E.RB1810629

ISIS Experiment Number: RB1810629

Part DOI Instrument Public release date Download Link
10.5286/ISIS.E.92922933 LOQ 21 April 2021 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 Wuge Briscoe et al; (2018): Fundamentals of molecular self-assembly in deep eutectic solvents (DES), STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB1810629

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



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