Toward a robust and general molecular simulation method for computing solid-liquid coexistence.

David M Eike; Joan F Brennecke; Edward J Maginn

doi:10.1063/1.1823371

Home/Archive/PubMed

PubMed · 15638650

Toward a robust and general molecular simulation method for computing solid-liquid coexistence.

David M Eike·Joan F Brennecke·Edward J Maginn

View original source ↗Export metadata ↓

Abstract

A rigorous and generally applicable method for computing solid-liquid coexistence is presented. The method overcomes some of the technical difficulties associated with other solid-liquid simulation procedures and can be implemented within either a molecular dynamics or Monte Carlo framework. The method consists of three steps: First, relative Gibbs free energy curves are created for the solid and liquid phases using histogram reweighting. Next, the free energy difference between the solid and liquid phases is evaluated at a single state point by integrating along a pseudosupercritical transformation path that connects the two phases. Using this result, the solid and liquid free energy curves are referenced to a common point, allowing a single coexistence point to be determined. Finally, Gibbs-Duhem integration is used to determine the full coexistence curve. To evaluate its utility, this method is applied to the Lennard-Jones and NaCl systems. Results for solid-liquid coexistence agree with previous calculations for these systems. In addition, it is shown that the NaCl model does not correctly describe solid-liquid coexistence at high pressures. An analysis of the accuracy of the method indicates that the results are most sensitive to the transformation free energy calculation.

Explore related subjects

Computer Simulation Models, Chemical Models, Molecular Molecular Conformation Phase Transition Sodium Chloride Solutions Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

David M Eike, Joan F Brennecke, Edward J Maginn. 2005-01-01. Toward a robust and general molecular simulation method for computing solid-liquid coexistence.. https://doi.org/10.1063/1.1823371

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2025

Generating correlated data for omics simulation.

Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.

Computer Simulation↗

PubMed2017

Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour-immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development.

Computer Simulation↗

PubMed2007

Twin concordances test for ascertained trichotomous traits data.

In human genetics, twin studies are widely underwent for investigation of the genetic influence on diseases. There are several measures that had been proposed to evaluate the similarity between two twins for dichotomous traits when the twins are sampled at random. These measures include the correlations, odds ratios, and casewise and pairwise concordances. When data are sampled through an ascertainment procedure, truncated data are formed. Under this circumstance, odds ratio cannot be defined and correlations cannot be correctly estimated. However, concordance measures for dichotomous traits can still be estimated using the likelihood method. On the other hand, though theoretically concordance measures can be extended to trichotomous traits, how to define them and to derive their estimators for ascertained trichotomous traits data have not been thoroughly discussed. In this study, we aim to address several relevant issues for ascertained trichotomous traits data. We define two new (casewise and pairwise) concordance measures for trichotomous traits and demonstrate how to apply a so-called 'self-contained subsets method (SCSM)' to estimation of twin concordances for ascertained data. We show that this method can obtain the same estimates as the likelihood method in an easier way and derive the asymptotic variances of the SCSM estimates under ascertainment. We establish the testing procedure for test of the equality of concordance measures between monozygotic twin pairs and dizygotic twin pairs, and illustrate the methods with a real data set and conduct Monte Carlo simulation to investigate its power performance.

Computer Simulation↗