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.
Surface composition in the physical developer process for latent fingerprint visualization
Abstract: Physical developer (PD) is a latent fingerprint development technique that is highly effective on paper and related surfaces, notably banknotes. The process exploits a redox reaction in which Ag(I) ions in solution are reduced by Fe(II), resulting in deposition of metallic silver on fingerprint residue on the surface. The standard formulation includes a cationic surfactant, whose presence is critical to formulation stability and efficacy, but whose role is poorly understood. By analogy with additives used in electrodeposition processes, surfactant adsorption can be expected to play a significant role. Here, we seek to determine the extent and composition of the surfactant layer on a silver surface using specular neutron reflectivity. Contrast variation of both solvent and surfactant will be exploited. The outcomes will guide optimization of the PD and derivative processes.
Principal Investigator: Professor Arthur Hillman
Experimenter: Professor Karl Ryder
Experimenter: Dr Rachel Sapstead
Experimenter: Dr Andrew Ballantyne
Local Contact: Dr Robert Dalgliesh
Experimenter: Dr Jodie Coulston
Experimenter: Dr Virginia Ferreira
Experimenter: Dr Rob Barker
DOI: 10.5286/ISIS.E.RB1610432
ISIS Experiment Number: RB1610432
Part DOI | Instrument | Public release date | Download Link |
---|---|---|---|
10.5286/ISIS.E.79112250 | INTER | 21 April 2019 | Download |
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 Arthur Hillman et al; (2016): Surface composition in the physical developer process for latent fingerprint visualization, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB1610432
Data is released under the CC-BY-4.0 license.