Publications

Here is a list of publication from the SCAMs@bristol group and Andrew.

kinisi: Bayesian analysis of mass transport from molecular dynamics simulations
Submitted, 2023 — Preprint | Code | Docs
Andrew R. McCluskey*, Alexander G. Squires, Samuel W. Coles, Benjamin J. Morgan*
A Python package for estimating diffusion properties from molecular dynamics simulations.

Accurate Estimation of Diffusion Coefficients and their Uncertainties from Computer Simulation
Submitted, 2023 — arXiv | ESI | Data
Andrew R. McCluskey*, Samuel W. Coles, Benjamin J. Morgan*
Using a physics-informed statistical model to efficiently estimate diffusion and accurately quantify uncertainty.

Is there still a place for linearization in the chemistry curriculum?
J. Chem. Educ., Accepted, 2023 — ChemRxiv | ESI | Data
Andrew R. McCluskey*
A commentary questioning the role of linearization in an undergraduate chemistry education.

Nature of the Superionic Transition of Lithium Nitride from Machine Learning Force Fields
Chem. Mater., 35 (15), 6133, 2023 — Paper | ChemRxiv
Gabriel Krenzer, Johan Klarbring, Kasper Tolborg, Hugo Rossignol, Andrew R. McCluskey, Benjamin J. Morgan*, Aron Walsh*
Investigations in superionic behaviour of lithiun nitride, quantified with non-Arrhenius diffusion.

Advice on describing Bayesian analysis of neutron and X-ray reflectometry
J. Appl. Crystallogr., 56 (1), 12, 2023 — Paper | ESI | Data | arXiv
Andrew R. McCluskey*, Andrew J. Caruana*, Christy J. Kinane, Alexander J. Armstrong, Thomas Arnold, Joshaniel F. K. Cooper, David L. Cortie, Arwel V. Hughes, Jean-Fran├žois Moulin, Andrew R. J. Nelson, Wojciech Potrzebowski, Vladimir Starostin
The opinion of the ORSO members on how best to share results from Bayesian sampling.

islatu: A Python package for the reduction of reflectometry data
J. Open Source Softw., 7 (77), 4397, 2022 — Paper | Code | Docs
Richard Brearton*, Andrew R. McCluskey, Tim Snow
Reflectometry data reduction at Diamond Light Source.

The 16th International Conference on Surface X-ray and Neutron Scattering (SXNS16)
Neutron News, 33 (2), 2, 2022 — Paper
Thomas Arnold*, Ann Terry, Elizabeth Blackburn, Uta Hejral, Zsuzsa Heles, Andrew R. McCluskey, Tommy Nylander, Max Wolff
A short description of the SXNS16 conference.

A Report on the Third Meeting of the Open Reflectivity Standards Organisation (ORSO)
Neutron News, 33 (1), 2, 2022 — Paper
Thomas Arnold*, Bridget Murphy, Andrew R. McCluskey, Jochen Stahn, Maximilian W. A. Skoda
Describing the third meeting of ORSO.

Overscreening and Underscreening in Solid-Electrolyte Grain Boundary Space-Charge Layers
Phys. Rev. Lett., 127 (13), 135502, 2021 — Paper | ESI | arXiv
Jacob M. Dean, Samuel W. Coles*, William R. Saunders, Andrew R. McCluskey, Matthew J. Wolf, Alison B. Walker, Benjamin J. Morgan*
Identifying liquid-state phenomena in solid electrolyte systems; using kinetic Monte Carlo and Bayesian inference.

FitBenchmarking: an open source Python package comparing data fitting software
J. Open Source Softw., 6 (62), 3127, 2021 — Paper | Code | Docs
Anders Markvardsen*, Tyronne Rees, Micheal Wathen, Andrew Lister, Patrick Odagiu, Atijit Anuchitanukul, Tom Farmer, Anthony Lim, Federico Montesino, Tim Snow, Andrew R. McCluskey
A tool to better understand the use of different optimisation approaches.

Disordered Filaments Mediate the Fibrillogenesis of Type-I Collagen in Solution
Biomacromolecules, 21 (9), 3611, 2020 — Paper
Andrew R. McCluskey, Kennes S. W. Hung, Bartosz Marzec, Julien O. Sindt, Nico A. J. M. Sommerdijk, Philip J. Camp, Fabio Nudelman*
Using cryogenic transmission electron microscopy and coarse-grained simulations to study the formation of collagen fibrils.

A general approach to maximise information density in neutron reflectometry analysis
Mach. Learn.: Sci Technol., 1 (3), 14850, 2020 — Paper | ESI | Data | arXiv
Andrew R. McCluskey*, Thomas Arnold, Joshanial F. K. Cooper, Tim Snow
Outlining and applying a Bayesian model selection framework for neutron reflectometry analysis.

uravu: Making Bayesian modelling easy(er)
J. Open Source Softw., 5 (50), 2214, 2020 — Paper | Code | Docs
Andrew R. McCluskey*, Tim Snow
A straightforward library for Bayesian data analysis.

Assessing molecular simulation for the analysis of lipid monolayer reflectometry
J. Phys. Comm., 3 (7), 31233, 2019 — Paper | ESI | Data | arXiv
Andrew R. McCluskey*, James Grant, Andrew J. Smith, Jonathan L. Rawle, David J. Barlow, M. Jayne Lawrence, Stephen C. Parker, Karen J. Edler*
Comparing different molecular dynamics potential models to improve reflectometry analysis.

Coarse-grained modelling for soft matter scattering
University of Bath, PhD Thesis, 2019 — Thesis | ESI
Andrew R. McCluskey
An investigation of different coarse-graining methods to develop the analysis of scattering from soft matter species.

An introduction to classical molecular dynamics simulation for experimental scattering users
J. Appl. Crystallogr., 52 (3), 655, 2019 — Paper | OER | arXiv
Andrew R. McCluskey*, James Grant, Adam R. Symington, Tim Snow, James Doutch, Benjamin J. Morgan*, Stephen C. Parker, Karen J. Edler
An open educational resource to engage users of scattering techniques in classical simulation.

Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers
Phys. Chem. Chem. Phys., 21 (11), 6133, 2019 — Paper | ESI | Data | arXiv
Andrew R. McCluskey*, Adrian Sanchez-Fernandez, Karen J. Edler, Stephen C. Parker, Andrew J. Jackson, Richard A. Campbell, Thomas Arnold*
A novel reflectometry analysis method reveals the structure of lipid monolayers at the air-DES interface.

pylj: A teaching tool for classical atomistic simulation
J. Open Source Educ., 1 (2), 19, 2018 — Paper | Code | Docs
Andrew R. McCluskey*, Benjamin J. Morgan, Karen J. Edler, Stephen C. Parker
pylj is an educational software to introduce students to classical atomistic simulation using a Lennnard-Jones potential model.

Model-dependent Small-angle Scattering for the Study of Complex Organic Material
Curr. Org. Chem., 22 (8), 750, 2018 — Paper
Andrew R. McCluskey, Karen J. Edler*
This review article introduces the method of model-dependent analysis of small angle scattering.