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.
Mapping of Liquid Formulation Stability and Structure using Machine-Learning Driven Autonomous Experimentation
Abstract: We will use our recently developed platform, the "Autonomous Formulations Laboratory" (AFL), to map the phase behavior of several commercially important soft material systems. Our system uses machine learning to intelligently select which compositions to measure, autonomously prepares samples using a pipetting robot, pumps them into a neutron beam, and then processes the data in a closed loop. Using the AFL, we will be able to more accurately and quickly map complex phase spaces enabling the study of complex mixtures with many components.
Principal Investigator: Dr Tyler Martin
Local Contact: Dr Robert Dalgliesh
Experimenter: Dr Peter Beaucage
DOI: 10.5286/ISIS.E.RB2210352
ISIS Experiment Number: RB2210352
| Part DOI | Instrument | Public release date | Download Link |
|---|---|---|---|
| 10.5286/ISIS.E.RB2210352-1 | LARMOR | 09 May 2025 | 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:
Dr Tyler Martin et al; (2022): Mapping of Liquid Formulation Stability and Structure using Machine-Learning Driven Autonomous Experimentation, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB2210352
Data is released under the CC-BY-4.0 license.
