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Register a new userHeat and charge transport in H$_2$O at ice-giant conditions from ab initio molecular dynamics simulations
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The impact of the inner structure and thermal history of planets on their observable features, such as luminosity or magnetic field, crucially depends on the poorly known heat and charge transport properties of their internal layers. The thermal and electric conductivities of different phases of water (liquid, solid, and super-ionic) occurring in the interior of ice giant planets, such as Uranus or Neptune, are evaluated from equilibrium ab initio molecular dynamics, leveraging recent progresses in the theory and data analysis of transport in extended systems. The implications of our findings on the evolution models of the ice giants are briefly discussed
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We develop a Python-based open-source package to analyze the results stemming from ab initio molecular-dynamics simulations of fluids. The package is best suited for applications on natural systems, like silicate and oxide melts, water-based fluids, various supercritical fluids. The package is a collection of Python scripts that include two major libraries dealing with file formats and with crystallography. All the scripts are run at the command line. We propose a simplified format to store the atomic trajectories and relevant thermodynamic information of the simulations, which is saved in UMD files, standing for Universal Molecular Dynamics. The UMD package allows the computation of a series of structural, transport and thermodynamic properties. Starting with the pair-distribution function it defines bond lengths, builds an interatomic connectivity matrix, and eventually determines the chemical speciation. Determining the lifetime of the chemical species allows running a full statistical analysis. Then dedicated scripts compute the mean-square displacements for the atoms as well as for the chemical species. The implemented self-correlation analysis of the atomic velocities yields the diffusion coefficients and the vibrational spectrum. The same analysis applied on the stresses yields the viscosity. The package is available via the GitHub website and via its own dedicated page of the ERC IMPACT project as open-access package.
The collective dynamics in liquid water is an active research topic experimentally, theoretically and via simulations. Here, ab initio molecular dynamics simulations are reported in heavy and ordinary water at temperature 323.15 K, or 50$^circ$C. The simulations in heavy water were performed both with and without dispersion corrections. We found that the dispersion correction (DFT-D3) changes the relaxation of density-density time correlation functions from a slow, typical of a supercooled state, to exponential decay behaviour of regular liquids. This implies an essential reduction of the melting point of ice in simulations with DFT-D3. Analysis of longitudinal (L) and transverse (T) current spectral functions allowed us to estimate the dispersions of acoustic and optic collective excitations and to observe the L-T mixing effect. The dispersion correction shifts the L and T optic (O) modes to lower frequencies and provides by almost thirty per cent smaller gap between the longest-wavelength LO and TO excitations, which can be a consequence of a larger effective high-frequency dielectric permittivity in simulations with dispersion corrections. Simulation in ordinary water with the dispersion correction results in frequencies of optic excitations higher than in D$_2$O, and in a long-wavelength LO-TO gap of 24 ps$^{-1}$ (127 cm$^{-1}$).
We present the results of first-principles molecular-dynamics simulations of molten silicates, based on the density functional formalism. In particular, the structural properties of a calcium aluminosilicate $ [$ CaO-Al$_2$O$_3$-SiO$_2$ $ ]$ melt are compared to those of a silica melt. The local structures of the two melts are in good agreement with the experimental understanding of these systems. In the calcium aluminosilicate melt, the number of non-bridging oxygens found is in excess of the number obtained from a simple stoichiometric prediction. In addition, the aluminum avoidance principle, which states that links between AlO$_4$ tetrahedra are absent or rare, is found to be violated. Defects such as 2-fold rings and 5-fold coordinated silicon atoms are found in comparable proportions in both liquids. However, in the calcium aluminosilicate melt, a larger proportion of oxygen atoms are 3-fold coordinated. In addition, 5-fold coordinated aluminum atoms are observed. Finally evidence of creation and anihilation of non-bridging oxygens is observed, with these oxygens being mostly connected to Si tetrahedra.
We investigated the structural and dynamical properties of a tetrahedrally coordinated crystalline ice from first principles based on density functional theory within the generalized gradient approximation with the projected augmented wave method. First, we report the structural behaviour of ice at finite temperatures based on the analysis of radial distribution functions obtained by molecular dynamics simulations. The results show how the ordering of the hydrogen bonding breaks down in the tetrahedral network of ice with entropy increase in agreement with the neutron diffraction data. We also calculated the phonon spectra of ice in a 3x1x1 supercell by using the direct method. So far, due to the direct method used in this calculation, the phonon spectra is obtained without taking into account the effect of polarization arising from dipole-dipole interactions of water molecules which is expected to yield the splitting of longitudinal and transverse optic modes at the Gamma-point. The calculated longitudinal acoustic velocities from the initial slopes of the acoustic mode is in a reasonable agreement with the neutron scatering data. The analysis of the vibrational density of states shows the existence of a boson peak at low energy of translational region a characteristic common to amorphous systems.
Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. We introduce a transferable high-fidelity neural network representation of such data in the form of tight-binding Hamiltonians for crystalline materials. This predictive representation of ab initio electronic structure, combined with machine-learning boosted molecular dynamics, enables efficient and accurate electronic evolution and sampling. When applied to a one-dimension charge-density wave material, carbyne, we are able to compute the spectral function and optical conductivity in the canonical ensemble. The spectral functions evaluated during soliton-antisoliton pair annihilation process reveal significant renormalization of low-energy edge modes due to retarded electron-lattice coupling beyond the Born-Oppenheimer limit. The availability of an efficient and reusable surrogate model for the electronic structure dynamical system will enable calculating many interesting physical properties, paving way to previously inaccessible or challenging avenues in materials modeling.
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