Electron-vibrational renormalization in fullerenes through and machine learning methods.

The effect of nuclear vibrations on the electronic eigenvalues and the HOMO-LUMO gap is known for several kinds of carbon-based materials, like diamond, diamondoids, carbon nanoclusters, carbon nanotubes and others, like hydrogen-terminated oligoynes and polyyne. However, it has not been widely analysed in another remarkable kind which presents both theoretical and technological interest: fullerenes. In this article we present the study of the HOMO, LUMO and gap renormalizations due to zero-point motion of a relatively large number (163) of fullerenes and fullerene derivatives.

Correction: An Exact Expression to Calculate the Derivatives of Position-Dependent Observables in Molecular Simulations with Flexible Constraints.

[This corrects the article DOI: 10.1371/journal.pone.

A survey of the parallel performance and accuracy of Poisson solvers for electronic structure calculations.

We present an analysis of different methods to calculate the classical electrostatic Hartree potential created by charge distributions. Our goal is to provide the reader with an estimation on the performance-in terms of both numerical complexity and accuracy-of popular Poisson solvers, and to give an intuitive idea on the way these solvers operate. Highly parallelizable routines have been implemented in a first-principle simulation code (Octopus) to be used in our tests, so that reliable conclusions about the capability of methods to tackle large systems in cluster computing can be obtained from our work.

Exact and efficient calculation of Lagrange multipliers in biological polymers with constrained bond lengths and bond angles: proteins and nucleic acids as example cases.

To accelerate molecular dynamics simulations, it is common to impose holonomic constraints on the hardest degrees of freedom. In this way, the time step used to integrate the equations of motion can be increased, thereby allowing longer total simulation times. The imposition of such constraints results in an aditional set of N(c) equations (the equations of constraint) and unknowns (their associated Lagrange multipliers), whose solution is closely related to any algorithm implementing the constraints in Euclidean coordinates.