Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion

In this work, an extension to the standard iterative Boltzmann inversion (IBI) method to derive coarse-grained potentials is proposed. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodynamic states than the standard IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying potential interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the standard method. Additionally, through the examination of alkane monolayers, it is shown that the relative weight given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of reference atomistic and/or experimental systems

Is there a role for citizen science in death and dying research?

The COVID-19 pandemic has brought conversations about death and dying to the fore in a way not experienced for generations. This raises questions around perceptions of death and dying; the role of healthcare and the community in care; and the use of digital media for information and support. Public engagement can provoke a two-way conversation between researchers and the public and includes techniques that can engage the community not only with the topic but also in research. This perspective article considers the potential role of citizen science in death and dying research, including considerations around its potential benefits and constraints

On the Behavior of Solutions of Xenon in Liquid n-Alkanes: Solubility of Xenon in n-Pentane and n-Hexane

The solubility of xenon in liquid n-pentane and n-hexane has been studied experimentally, theoretically, and by computer simulation. Measurements of the solubility are reported for xenon + n-pentane as a function of temperature from 254 to 305 K. The uncertainty in the experimental data is less than 0.15%. The thermodynamic functions of solvation such as the standard Gibbs energy, enthalpy, and entropy of solvation have been calculated from Henry’s law coefficients for xenon + n-pentane solutions and also for xenon + n-hexane, which were reported in previous work. The results provide a further example of the similarity between the xenon + n-alkane interaction and the n-alkane + n-alkane interactions. Using the SAFT-VR approach we were able to quantitatively predict the experimental solubility for xenon in n-pentane and semiquantitatively that of xenon in n-hexane using simple Lorentz−Berthelot combining rules to describe the unlikely interaction. Henry’s constants at infinite dilution for xenon + n-pentane and xenon + n-hexane were also calculated by Monte Carlo simulation using a united atom force field to describe the n-alkane and the Widom test particle insertion method

The oscillatory damped behaviour of incommensurate double-walled carbon nanotubes

Abstract The mechanical properties of sliding carbon nanotubes have been investigated by classical molecular dynamics simulations in the canonical ensemble. In particular we have studied damped oscillations in the separation between the centres of mass of the inner and outer tubes of double-walled carbon nanotubes (DWCN). Incommensurate DWCNs forming (7, 0)@(9, 9) structures were simulated for systems at 298.15 K with axial lengths from 12.21 to 98.24 nm. The oscillations exhibited frequencies in the range of gigahertz with the frequency decreasing as the length of the system increases. The time until oscillations become negligible exhibited a nearly linear dependence on the length of the system. Two macroscopic models were developed in order to understand the forces involved in terms of macroscopic properties like friction and shear. The first model considered constant restoring forces during the whole event, while in the second the value of these constant restoring forces depended on the initial conditions of each oscillation. Both models reproduced the oscillations quite well, while the second model allows us to predict the dynamic shear strength in terms of the axial length of the system for tubes with the same diameters. The calculated dynamic shear strength exhibited monotonic behaviour with an inverse dependence on the length of the system. For systems with unequal axial lengths, the restoring force, which drives the oscillation, is reduced compared to the system with equal lengths, regardless of whether the outer nanotube is longer or shorter. M This article contains online multimedia enhancement

Viscosity of Liquid Perfluoroalkanes and Perfluoroalkylalkane Surfactants

As part of a systematic study of the thermophysical properties of two important classes of fluorinated organic compounds (perfluoroalkanes and perfluoroalkylalkanes), viscosity measurements of four n-perfluoroalkanes and five perfluoroalkylalkanes have been carried out at atmospheric pressure and over a wide range of temperatures (278–353 K). From the experimental results the contribution to the viscosity from the CF2 and CF3 groups as a function of temperature have been estimated. Similarly, the contributions for CH2 and CH3 groups in n-alkanes have been determined using literature data. For perfluoroalkylalkanes, the viscosity results were interpreted in terms of the contributions of the constituent CF2, CF3, CH2, and CH3 groups, the deviations from ideality on mixing hydrogenated and fluorinated chains, and the contribution due to the formation of the CF2–CH2 bond. A standard empirical group contribution method (Sastri–Rao method) has also been used to estimate the viscosities of the perfluoroalkylalkanes. Finally, to obtain molecular level insight into the behavior of these molecules, all-atom molecular dynamics simulations have been performed and used to calculate the densities and viscosities of the perfluoroalkylalkanes studied. Although both quantities are underestimated compared to the experimental data, with the viscosities showing the largest deviations, the trends observed in the experimental viscosities are captured

Identifying Candidate Spaces for Advert Implantation

Virtual advertising is an important and promising feature in the area of online advertising. It involves integrating adverts onto live or recorded videos for product placements and targeted advertisements. Such integration of adverts is primarily done by video editors in the post-production stage, which is cumbersome and time-consuming. Therefore, it is important to automatically identify candidate spaces in a video frame, wherein new adverts can be implanted. The candidate space should match the scene perspective, and also have a high quality of experience according to human subjective judgment. In this paper, we propose the use of a bespoke neural net that can assist the video editors in identifying candidate spaces. We benchmark our approach against several deep-learning architectures on a large-scale image dataset of candidate spaces of outdoor scenes. Our work is the first of its kind in this area of multimedia and augmented reality applications, and achieves the best results.Comment: Published in Proc. IEEE 7th International Conference on Computer Science and Network Technology, 201