Robust non-adiabatic molecular dynamics for metals and insulators

We present a new formulation of the correlated electron-ion dynamics (CEID) scheme, which systematically improves Ehrenfest dynamics by including quantum fluctuations around the mean-field atomic trajectories. We show that the method can simulate models of non-adiabatic electronic transitions, and test it against exact integration of the time-dependent Schroedinger equation. Unlike previous formulations of CEID, the accuracy of this scheme depends on a single tunable parameter which sets the level of atomic fluctuations included. The convergence to the exact dynamics by increasing the tunable parameter is demonstrated for a model two level system. This algorithm provides a smooth description of the non-adiabatic electronic transitions which satisfies the kinematic constraints (energy and momentum conservation) and preserves quantum coherence. The applicability of this algorithm to more complex atomic systems is discussed.Comment: 36 pages, 5 figures. Accepted for publication in Journal of Chemical Physic

Power dissipation in nanoscale conductors: classical, semi-classical and quantum dynamics

Modelling Joule heating is a difficult problem because of the need to introduce correct correlations between the motions of the ions and the electrons. In this paper we analyse three different models of current induced heating (a purely classical model, a fully quantum model and a hybrid model in which the electrons are treated quantum mechanically and the atoms are treated classically). We find that all three models allow for both heating and cooling processes in the presence of a current, and furthermore the purely classical and purely quantum models show remarkable agreement in the limit of high biases. However, the hybrid model in the Ehrenfest approximation tends to suppress heating. Analysis of the equations of motion reveals that this is a consequence of two things: the electrons are being treated as a continuous fluid and the atoms cannot undergo quantum fluctuations. A means for correcting this is suggested

Accelerating GW calculations through machine learned dielectric matrices

The GW approach produces highly accurate quasiparticle energies, but its application to large systems is computationally challenging due to the difficulty in computing the inverse dielectric matrix. To address this challenge, we develop a machine learning approach to efficiently predict density–density response functions (DDRF) in materials. An atomic decomposition of the DDRF is introduced, as well as the neighborhood density–matrix descriptor, both of which transform in the same way under rotations. The resulting DDRFs are then used to evaluate quasiparticle energies via the GW approach. To assess the accuracy of this method, we apply it to hydrogenated silicon clusters and find that it reliably reproduces HOMO–LUMO gaps and quasiparticle energy levels. The accuracy of the predictions deteriorates when the approach is applied to larger clusters than those in the training set. These advances pave the way for GW calculations of complex systems, such as disordered materials, liquids, interfaces, and nanoparticles

Block bond-order potential as a convergent moments-based method

The theory of a novel bond-order potential, which is based on the block Lanczos algorithm, is presented within an orthogonal tight-binding representation. The block scheme handles automatically the very different character of sigma and pi bonds by introducing block elements, which produces rapid convergence of the energies and forces within insulators, semiconductors, metals, and molecules. The method gives the first convergent results for vacancies in semiconductors using a moments-based method with a low number of moments. Our use of the Lanczos basis simplifies the calculations of the band energy and forces, which allows the application of the method to the molecular dynamics simulations of large systems. As an illustration of this convergent O(N) method we apply the block bond-order potential to the large scale simulation of the deformation of a carbon nanotube.Comment: revtex, 43 pages, 11 figures, submitted to Phys. Rev.

Inelastic quantum transport: the self-consistent Born approximation and correlated electron-ion dynamics

A dynamical method for inelastic transport simulations in nanostructures is compared with a steady-state method based on non-equilibrium Green's functions. A simplified form of the dynamical method produces, in the steady state in the weak-coupling limit, effective self-energies analogous to those in the Born Approximation due to electron-phonon coupling. The two methods are then compared numerically on a resonant system consisting of a linear trimer weakly embedded between metal electrodes. This system exhibits enhanced heating at high biases and long phonon equilibration times. Despite the differences in their formulation, the static and dynamical methods capture local current-induced heating and inelastic corrections to the current with good agreement over a wide range of conditions, except in the limit of very high vibrational excitations, where differences begin to emerge.Comment: 12 pages, 7 figure

Histological and transcriptomic effects of 17α-methyltestosterone on zebrafish gonad development.

BACKGROUND: Sex hormones play important roles in teleost ovarian and testicular development. In zebrafish, ovarian differentiation appears to be dictated by an oocyte-derived signal via Cyp19a1a aromatase-mediated estrogen production. Androgens and aromatase inhibitors can induce female-to-male sex reversal, however, the mechanisms underlying gonadal masculinisation are poorly understood. We used histological analyses together with RNA sequencing to characterise zebrafish gonadal transcriptomes and investigate the effects of 17α-methyltestosterone on gonadal differentiation. RESULTS: At a morphological level, 17α-methyltestosterone (MT) masculinised gonads and accelerated spermatogenesis, and these changes were paralleled in masculinisation and de-feminisation of gonadal transcriptomes. MT treatment upregulated expression of genes involved in male sex determination and differentiation (amh, dmrt1, gsdf and wt1a) and those involved in 11-oxygenated androgen production (cyp11c1 and hsd11b2). It also repressed expression of ovarian development and folliculogenesis genes (bmp15, gdf9, figla, zp2.1 and zp3b). Furthermore, MT treatment altered epigenetic modification of histones in zebrafish gonads. Contrary to expectations, higher levels of cyp19a1a or foxl2 expression in control ovaries compared to MT-treated testes and control testes were not statistically significant during early gonad development (40 dpf). CONCLUSION: Our study suggests that both androgen production and aromatase inhibition are important for androgen-induced gonadal masculinisation and natural testicular differentiation in zebrafish