Explanipedia

Uncertainty in MD-Derived Diffusion Coefficients Depends on Analysis Protocol, Not Just Simulation Data Open

Benjamin J. Morgan, Andrew R. McCluskey · 2025

Bonkowski and De Souza [Sol. Stat. Ionics 429, 116967 (2025)] provide a guide for performing molecular dynamics simulations of ion transport, including methods for estimating diffusion coefficients and their uncertainties from mean-squared…

Uncertainty in MD-Derived Diffusion Coefficients Depends on Analysis Protocol, Not Just Simulation Data Open

Benjamin J. Morgan, Andrew R. McCluskey · 2025

Bonkowski and De Souza [Sol. Stat. Ionics 429, 116967 (2025)] provide a guide for performing molecular dynamics simulations of ion transport, including methods for estimating diffusion coefficients and their uncertainties from mean-squared…

On the estimation of center of mass in periodic systems Open

Harvey Richardson, Josh Dunn, Andrew R. McCluskey · 2025

Calculation of the center of mass of a group of particles in a periodically repeating cell is an important aspect of chemical and physical simulations. One popular approach calculates the center of mass via the projection of the individual…

On the Estimation of Centre of Mass in Periodic Systems Open

Harry W. Richardson, Josh Dunn, Andrew R. McCluskey · 2025

Calculation of the centre of mass of a group of particles in a periodically-repeating cell is an important aspect of chemical and physical simulation. One popular approach calculates the centre of mass via the projection of the individual …

Accurate Estimation of Diffusion Coefficients and their Uncertainties from Computer Simulation Open

Andrew R. McCluskey, Samuel W. Coles, Benjamin J. Morgan · 2024

Self-diffusion coefficients, D*, are routinely estimated from molecular dynamics simulations by fitting a linear model to the observed mean squared displacements (MSDs) of mobile species. MSDs derived from simulations exhibit statis…

Digital Skills in Chemical Education Open

Andrew R. McCluskey, Miguel Rivera, Antonia S. J. S. Mey · 2024

The role of computing in the chemical sciences is changing. Previously the domain of the theoretical or computational chemist, advanced digital skills, including data analysis and simulation, are becoming extremely relevant to all. Here, w…

Diffusion Mechanisms and Preferential Dynamics of Promoter Molecules in ZSM-5 Zeolite Open

Josh Dunn, Joe Crossley-Lewis, Andrew R. McCluskey, Fiona Jackson, Corneliu Buda , et al. · 2024

The diffusion in ZSM-5 zeolite of methanol and of two series of promoters of the methanol to dimethyl ether reaction (linear methyl esters, benzaldehyde, 4-n-alkyl benzaldehydes) has been studied using classical molecular dynamics in the N…

Diffusion Mechanisms and Preferential Dynamics of Promoter Molecules in ZSM-5 Zeolite Open

Josh Dunn, Joe Crossley-Lewis, Andrew R. McCluskey, Fiona Jackson, Corneliu Buda , et al. · 2024

The diffusion in ZSM-5 zeolite of methanol and of two series of promoters of the methanol to dimethyl ether reaction (linear methyl esters, benzaldehyde, 4-n-alkyl benzaldehydes) has been studied using classical molecular dynamics in the N…

Investigating model influence on the analytical resolution of neutron reflectometry Open

Nicolas Shiaelis, Luke A. Clifton, Andrew R. McCluskey · 2024

Neutron reflectometry is a critical tool for investigating the structure of thin films and interfaces. However, the misapplication of the Born approximation to reflection geometry leads some to assume that the minimum thickness that may be…

kinisi: Bayesian analysis of mass transport frommolecular dynamics simulations Open

Andrew R. McCluskey, Alexander G. Squires, Josh Dunn, Samuel W. Coles, Benjamin J. Morgan · 2024

kinisi is a Python package for estimating transport coefficients-e.g., self-diffusion coefficients, * -and their corresponding uncertainties from molecular dynamics simulation data.It includes an implementation of the approximate Bayesian …

The First European Spallation Source Data Management and Software Centre Summer School Open

Andrew R. McCluskey, Petra Aulin, Fredrik Bolmsten, Mads Bertelsen, Carina M. C. Lobley , et al. · 2024

Diffusion mechanisms and preferential dynamics of promoter molecules in ZSM-5 zeolite Open

Josh Dunn, Joe Crossley-Lewis, Andrew R. McCluskey, Fiona Jackson, Corneliu Buda , et al. · 2024

Molecular 3-point turns are seen in molecular dynamics simulations of methanol and promoters of the CH 3 OH to CH 3 OCH 3 reaction. The more catalytically active aromatic aldehydes limit methanol diffusion less than other promoters.

Is There Still a Place for Linearization in the Chemistry Curriculum? Open

Andrew R. McCluskey · 2023

The use of mathematical transformations to reduce nonlinear functions to linear problems, which can be tackled with analytical linear regression, is commonplace in the chemistry curriculum. The linearization procedure, however, assumes an …

Is there still a place for linearization in the chemistry curriculum? Open

Andrew R. McCluskey · 2023

The use of mathematical transformations to reduce non-linear functions to linear problems, which can be tackled with analytical linear regression, is commonplace in the chemistry curriculum. The linearization procedure, however, assumes an…

Nature of the Superionic Phase Transition of Lithium Nitride from Machine Learning Force Fields Open

Gabriel Krenzer, Johan Klarbring, Kasper Tolborg, Hugo Rossignol, Andrew R. McCluskey , et al. · 2023

Superionic conductors have great potential as solid-stateelectrolytes,but the physics of type-II superionic transitions remains elusive.In this study, we employed molecular dynamics simulations, using machinelearning force fields, to inves…

Nature of the Superionic Phase Transition of Lithium Nitride from Machine Learning Force Fields Open

Gabriel Krenzer, Johan Klarbring, Kasper Tolborg, Hugo Rossignol, Andrew R. McCluskey , et al. · 2023

Superionic conductors have great potential as solid-state electrolytes, but the physics of type-II superionic transitions remains elusive. In this study, we employed molecular dynamics simulations, using machine learning force fields, to i…

Accurate Estimation of Diffusion Coefficients and their Uncertainties from Computer Simulation Open

Andrew R. McCluskey, Samuel W. Coles, Benjamin J. Morgan · 2023

Self-diffusion coefficients, $D^*$, are routinely estimated from molecular dynamics simulations by fitting a linear model to the observed mean-squared displacements (MSDs) of mobile species. MSDs derived from simulation exhibit statistical…

Is there still a place for linearization in the chemistry curriculum? Open

Andrew R. McCluskey · 2023

The use of mathematical transformations to reduce non-linear functions to linear problems, which can be tackled with analytical linear regression, is commonplace in the chemistry curriculum. The linearization procedure, however, assumes an…

Advice on describing Bayesian analysis of neutron and X-ray reflectometry Open

Andrew R. McCluskey, Andrew J. Caruana, C. J. Kinane, Alexander J. Armstrong, Thomas Arnold , et al. · 2022

As a result of the availability of modern software and hardware, Bayesian analysis is becoming more popular in neutron and X-ray reflectometry analysis. The understandability and replicability of these analyses may be harmed by inconsisten…

Closing report including report from summer school Open

Andrew R. McCluskey, Thomas H. Rod, Peter Kjær Willendrup · 2022

This report encompasses Deliverable D.8.4 “Closing report including report from summer school, task 8.8” where task 8.8 is “PaNOSC schools for students”.

islatu: A Python package for the reduction ofreflectometry data Open

Richard Brearton, Andrew R. McCluskey, Tim Snow · 2022

The interaction between light and matter provides a sensitive probe of the electronic structure of materials, on length scales determined by the difference between the incident and outgoing wavevector of the light.Reflectometry techniques …

PaNOSC Summer School QENS Data Open