forked from refnx/refnx
-
Notifications
You must be signed in to change notification settings - Fork 0
/
testimonials.bib
127 lines (115 loc) · 10.5 KB
/
testimonials.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
% Encoding: UTF-8
@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},
volume = {3},
pages = {075001},
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},
}
@Article{Appel2019,
author = {Christian Appel and Björn Kuttich and Lukas Stühn and Robert W. Stark and Bernd Stühn},
title = {Structural Properties and Magnetic Ordering in 2D Polymer Nanocomposites: Existence of Long Magnetic Dipolar Chains in Zero Field},
journal = {Langmuir},
year = {2019},
volume = {35},
pages = {13180 - 12191},
abstract = {The existence of magnetic dipolar nanoparticle chains at zero field has been predicted theoretically for decades, but these structures are rarely observed experimentally. A prerequisite is a permanent magnetic moment on the particles forming the chain. Here we report on the observation of magnetic dipolar chains of spherical iron oxide nanoparticles with a diameter of 12.8 nm. The nanoparticles are embedded in an ultrathin polymer film. Due to the high viscosity of the polymer matrix, the dominating aggregation mechanism is driven by dipolar interactions. Smaller iron oxide nanoparticles (8 nm) show no permanent magnetic moment and do not form chains but compact aggregates. Mixed monolayers of iron oxide nanoparticles and polymer at the air−water interface are characterized by Langmuir isotherms and in situ X-ray reflectometry (XRR). The combination of the particles with a polymer leads to a stable polymer nanocomposite film at the air−water interface. XRR experiments show that nanoparticles are immersed in a thin polymer matrix of 2 nm. Using atomic force microscopy (AFM) on Langmuir−Blodgett films, we measure the lateral distribution of particles in the film. An analysis of single structures within transferred films results in fractal dimensions that are in excellent agreement with 2D simulations.},
doi = {10.1021/acs.langmuir.9b02094},
}
@misc{mccluskey2019using,
title={Using Bayesian model selection to advise neutron reflectometry analysis from Langmuir-Blodgett monolayers},
author={Andrew R. McCluskey and Thomas Arnold and Joshaniel F. K. Cooper and Tim Snow},
year={2019},
eprint={1910.10581},
archivePrefix={arXiv},
primaryClass={cond-mat.soft}
}
@article{Pospelov:ge5067,
author = "Pospelov, Gennady and Van Herck, Walter and Burle, Jan and Carmona Loaiza, Juan M. and Durniak, C{\'{e}}line and Fisher, Jonathan M. and Ganeva, Marina and Yurov, Dmitry and Wuttke, Joachim",
title = "{{\it BornAgain}: software for simulating and fitting grazing-incidence small-angle scattering}",
journal = "Journal of Applied Crystallography",
year = "2020",
volume = "53",
number = "1",
pages = "262--276",
month = "Feb",
doi = {10.1107/S1600576719016789},
url = {https://doi.org/10.1107/S1600576719016789},
abstract = {{\it BornAgain} is a free and open-source multi-platform software framework for simulating and fitting X-ray and neutron reflectometry, off-specular scattering, and grazing-incidence small-angle scattering (GISAS). This paper concentrates on GISAS. Support for reflectometry and off-specular scattering has been added more recently, is still under intense development and will be described in a later publication. {\it BornAgain} supports neutron polarization and magnetic scattering. Users can define sample and instrument models through Python scripting. A large subset of the functionality is also available through a graphical user interface. This paper describes the software in terms of the realized non-functional and functional requirements. The web site https://www.bornagainproject.org/ provides further documentation.},
keywords = {grazing-incidence small-angle scattering (GISAS), X-ray scattering, neutron scattering, simulation, software},
}
@article{freychetmorphology,
title={Morphology of poly (lactide)-block-poly (dimethylsiloxane)-block-polylactide high-$\chi$ triblock copolymer film studied by grazing incidence small-angle X-ray scattering},
author={Freychet, Guillaume and Maret, Mireille and Fernandez-Regulez, Marta and Tiron, Raluca and Gharbi, Ahmed and Nicolet, Celia and Gergaud, Patrice},
journal={Journal of Polymer Science},
publisher={Wiley Online Library}
}
@article{refId0,
author = {{Gerelli, Yuri}},
title = {Applications of neutron reflectometry in biology},
DOI= "10.1051/epjconf/202023604002",
url= "https://doi.org/10.1051/epjconf/202023604002",
journal = {EPJ Web Conf.},
year = 2020,
volume = 236,
pages = "04002",
}
@article{McCluskey_2020,
doi = {10.1088/2632-2153/ab94c4},
url = {https://doi.org/10.1088%2F2632-2153%2Fab94c4},
year = 2020,
month = {jul},
publisher = {{IOP} Publishing},
volume = {1},
number = {3},
pages = {035002},
author = {Andrew R McCluskey and Joshaniel F K Cooper and Tom Arnold and Tim Snow},
title = {A general approach to maximise information density in neutron reflectometry analysis},
journal = {Machine Learning: Science and Technology},
abstract = {Neutron and x-ray reflectometry are powerful techniques facilitating the study of the structure of interfacial materials. The analysis of these techniques is ill-posed in nature requiring the application of model-dependent methods. This can lead to the over- and under- analysis of experimental data when too many or too few parameters are allowed to vary in the model. In this work, we outline a robust and generic framework for the determination of the set of free parameters that are capable of maximising the information density of the model. This framework involves the determination of the Bayesian evidence for each permutation of free parameters; and is applied to a simple phospholipid monolayer. We believe this framework should become an important component in reflectometry data analysis and hope others more regularly consider the relative evidence for their analytical models.}
}
@article{simonne2019diffraction,
title={Diffraction investigation of the Half-Heusler to Full-Heusler transition in Ni2-xMnSb},
url = {http://dsimonne.eu/Documents/MasterThesisSimonne.pdf},
author={Simonne, David},
year={2019}
}
@Comment{jabref-meta: databaseType:bibtex;}