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Register a new userFirst-principles energetics of water: a many-body analysis
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Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for solid, liquid and cluster forms of water. We use a many-body separation of the total energy into its 1-body, 2-body (2B) and beyond-2-body (B2B) components to analyze the deficiencies of two popular DFT approximations. We show how machine-learning methods make this analysis possible for ice structures as well as for water clusters. We find that the crucial energy balance between compact and extended geometries can be distorted by 2B and B2B errors, and that both types of first-principles error are important.
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Impressive advances in the field of molecular spintronics allow one to study electron transport through individual magnetic molecules embedded between metallic leads in the purely quantum regime of single electron tunneling. Besides fundamental interest, this experimental setup, in which a single molecule is manipulated by electronic means, provides the elementary units of possible forthcoming technological applications, ranging from spin valves to transistors and qubits for quantum information processing. Theoretically, while for weakly correlated molecular junctions established first-principles techniques do enable the system-specific description of transport phenomena, methods of similar power and flexibility are still lacking for junctions involving strongly correlated molecular nanomagnets. Here we propose an efficient scheme based on the ab initio construction of material-specific Hubbard models and on the master-equation formalism. We apply this approach to a representative case, the Ni$_2$ molecular spin dimer, in the regime of weak molecule-electrode coupling, the one relevant for quantum-information applications. Our approach allows us to study in a realistic setting many-body effects such as current suppression and negative differential conductance. We think that this method has the potential for becoming a very useful tool for describing transport phenomena in strongly correlated molecules.
Precipitation in Mg-Zn alloys was analyzed by means of first principles calculations. Formation energies of symmetrically distinct hcp Mg1-xZnx (0 < x < 1) configurations were determined and potential candidates for Guinier-Preston zones coherent with the matrix were identified from the convex hull. The most likely structures were ranked depending on the interface energy along the basal plane. In addition, the formation energy and vibrational entropic contributions of several phases reported experimentally (Mg4Zn7, MgZn2 cubic, MgZn2 hexagonal, Mg21Zn25 and Mg2Zn11) were calculated. The formation energies of Mg4Zn7, MgZn2 cubic, and MgZn2 hexagonal Laves phases were very close because they were formed by different arrangements of rhombohedral and hexagonal lattice units. It was concluded that beta_1^ precipitates were formed by a mixture of all of them. Nevertheless, the differences in the geometrical arrangements led to variations in the entropic energy contributions which determined the high temperature stability. It was found that the MgZn2 hexagonal Laves phase is the most stable phase at high temperature and, thus, beta_1^ precipitates tend to transform into the beta_2^ (MgZn2 hexagonal) precipitates with higher aging temperature or longer aging times. Finally, the equilibrium beta phase (Mg21Zn25) was found to be a long-range order that precipitates the last one on account of the kinetic processes necessary to trigger the transformation from a short-range order phase beta_2^ to beta .
The many-body polarization energy is the major source of non-additivity in strongly polar systems such as water. This non-additivity is often considerable and must be included, if only in an average manner, to correctly describe the physical properties of the system. Models for the polarization energy are usually parameterized using experimental data, or theoretical estimates of the many-body effects. Here we show how many-body polarization models can be developed for water complexes using data for the monomer and dimer only using ideas recently developed in the field of intermolecular perturbation theory and state-of-the-art approaches for calculating distributed molecular properties based on the iterated stockholder atoms (ISA) algorithm. We show how these models can be calculated, and validate their accuracy in describing the many-body non-additive energies of a range of water clusters. We further investigate their sensitivity to the details of the polarization damping models used. We show how our very best polarization models yield many-body energies that agree with those computed with coupled-cluster methods, but at a fraction of the computational cost.
We compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way, that a DNN model, trained on meta-GGA (SCAN) data, reduce the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.
We show how an embedded many-body expansion (EMBE) can be used to calculate accurate emph{ab initio} energies of water clusters and ice structures using wavefunction-based methods. We use the EMBE described recently by Bygrave emph{et al.} (J. Chem. Phys. textbf{137}, 164102 (2012)), in which the terms in the expansion are obtained from calculations on monomers, dimers, etc. acted on by an approximate representation of the embedding field due to all other molecules in the system, this field being a sum of Coulomb and exchange-repulsion fields. Our strategy is to separate the total energy of the system into Hartree-Fock and correlation parts, using the EMBE only for the correlation energy, with the Hartree-Fock energy calculated using standard molecular quantum chemistry for clusters and plane-wave methods for crystals. Our tests on a range of different water clusters up to the 16-mer show that for the second-order Mo{}ller-Plesset (MP2) method the EMBE truncated at 2-body level reproduces to better than 0.1 m$E_{rm h}$/monomer the correlation energy from standard methods. The use of EMBE for computing coupled-cluster energies of clusters is also discussed. For the ice structures Ih, II and VIII, we find that MP2 energies near the complete basis-set limit reproduce very well the experimental values of the absolute and relative binding energies, but that the use of coupled-cluster methods for many-body correlation (non-additive dispersion) is essential for a full description. Possible future applications of the EMBE approach are suggested.
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