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testimonials.bib
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testimonials.bib
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@Article{C9CP00203K,
author = {McCluskey, Andrew R. and Sanchez-Fernandez, Adrian and Edler, Karen J. and Parker, Stephen C. and Jackson, Andrew J. and Campbell, Richard A. and Arnold, Thomas},
title = {Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers},
journal = {Phys. Chem. Chem. Phys.},
year = {2019},
volume = {21},
pages = {6133-6141},
abstract = {In this work{,} we present the first example of the self-assembly of phospholipid monolayers at the interface between air and an ionic solvent. Deep eutectic solvents are a novel class of environmentally friendly{,} non-aqueous{,} room temperature liquids with tunable properties{,} that have wide-ranging potential applications and are capable of promoting the self-assembly of surfactant molecules. We use a chemically-consistent Bayesian modelling of X-ray and neutron reflectometry measurements to show that these monolayers broadly behave as they do on water. This method allows for the monolayer structure to be determined{,} alongside the molecular volumes of the individual monolayer components{,} without the need for water-specific constraints to be introduced. Furthermore{,} using this method we are able to better understand the correlations present between parameters in the analytical model. This example of a non-aqueous phospholipid monolayer has important implications for the potential uses of these solvents and for our understanding of how biomolecules behave in the absence of water.},
doi = {10.1039/C9CP00203K},
issue = {11},
publisher = {The Royal Society of Chemistry},
url = {http://dx.doi.org/10.1039/C9CP00203K},
}
@Article{McCluskey2019,
author = {{McCluskey}, Andrew R. and {Grant}, James and {Smith}, Andrew J. and {Rawle}, Jonathan L. and {Barlow}, David J. and {Lawrence}, M. Jayne and {Parker}, Stephen C. and {Edler}, Karen J.},
title = {{Assessing molecular simulation for the analysis of lipid monolayer reflectometry}},
journal = {Journal of Physics Communications},
year = {2019},
month = Jan,
doi = {https://doi.org/10.1088/2399-6528/ab12a9},
keywords = {Condensed Matter - Soft Condensed Matter},
}
@Article{Nelson2019,
author = {Andrew R. J. Nelson and Stuart W. Prescott},
title = {refnx: neutron and X-ray reflectometry analysis in Python},
journal = {Journal of Applied Crystallography},
year = {2019},
volume = {52},
number = {1},
pages = {193-200},
month = feb,
abstract = {refnx is a model-based neutron and X-ray reflectometry data analysis package written in Python. It is cross platform and has been tested on Linux, macOS and Windows. Its graphical user interface is browser based, through a Jupyter notebook. Model construction is modular, being composed from a series of components that each describe a subset of the interface, parameterized in terms of physically relevant parameters (volume fraction of a polymer, lipid area per molecule etc.). The model and data are used to create an objective, which is used to calculate the residuals, log-likelihood and log-prior probabilities of the system. Objectives are combined to perform co-refinement of multiple data sets and mixed-area models. Prior knowledge of parameter values is encoded as probability distribution functions or bounds on all parameters in the system. Additional prior probability terms can be defined for sets of components, over and above those available from the parameters alone. Algebraic parameter constraints are available. The softwares offers a choice of fitting approaches, including least-squares (global and gradient-based optimizers) and a Bayesian approach using a Markov-chain Monte Carlo algorithm to investigate the posterior distribution of the model parameters. The Bayesian approach is useful for examining parameter covariances, model selection and variability in the resulting scattering length density profiles. The package is designed to facilitate reproducible research; its use in Jupyter notebooks, and subsequent distribution of those notebooks as supporting information, permits straightforward reproduction of analyses.},
doi = {10.1107/S1600576718017296},
}
@Article{Johnson2019,
author = {E. Johnson and T. Murdoch and I. Gresham and B. Humphreys and S. W. Prescott and A. Nelson and G. B. Webber and E. Wanless},
title = {Temperature dependent specific ion effects in mixed salt environments on a thermoresponsive poly(oligoethylene glycol methacrylate) brush},
journal = {Physical Chemistry Chemical Physics},
year = {2019},
volume = {21},
pages = {4650 - 4662},
doi = {10.1039/C8CP06644B},
}
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