ISIS Neutron and Muon Source Data Journal

Self-assembly of detergent molecules below ambient temperature: SANS to determine the micellar structures from model binary mixtures

Abstract: Although surfactant detergency is well understood above 30 C, actions of surfactants below 30 C are not well established. In the era of energy saving and environment caring, we must understand how to optimise detergency in what are increasingly hostile environments. Existing surfactant mixing theories such as regular solution theory are not validated at low temperatures, and other factors such as being closer to the solubility limit of the surfactants, and perhaps proximate to phase boundaries also need to be taken into account. It is hence vital that industry is supported with both data and a thermodynamic description of the behaviour of detergent components at ambient and below ambient temperatures. This work proposes to study how model surfactants behave in model binary mixtures below ambient temperatures using SANS.

Principal Investigator: Professor Jian Lu
Experimenter: Miss Daniela Ciumac
Experimenter: Dr John Webster
Experimenter: Mr Zhiming Lu
Experimenter: Dr Mario Campana
Experimenter: Dr Zongyi Li
Experimenter: Dr Ian Tucker
Experimenter: Mr Charles Smith
Local Contact: Dr Richard Heenan

DOI: 10.5286/ISIS.E.RB1510047

ISIS Experiment Number: RB1510047

Publisher: STFC ISIS Neutron and Muon Source

Data format: RAW/Nexus
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Data Citation

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

For Example:
Professor Jian Lu et al; (2015): Self-assembly of detergent molecules below ambient temperature: SANS to determine the micellar structures from model binary mixtures, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB1510047

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