DeepDFT: Neural Message Passing Network for Accurate Charge Density Prediction

We introduce DeepDFT, a deep learning model for predicting the electronic charge density around atoms, the fundamental variable in electronic structure simulations from which all ground state properties can be calculated. The model is formulated as neural message passing on a graph, consisting of interacting atom vertices and special query point vertices for which the charge density is predicted. The accuracy and scalability of the model are demonstrated for molecules, solids and liquids. The trained model achieves lower average prediction errors than the observed variations in charge density obtained from density functional theory simulations using different exchange correlation functionals.Comment: Workshop paper presented at Machine Learning for Molecules Workshop at NeurIPS 2020. Implementation and pretrained model are available at https://github.com/peterbjorgensen/DeepDF

[Transitional strength under plasma] Precise estimations of astrophysically relevant electromagnetic transitions of Ar7+^{7+}, Kr7+^{7+}, Xe7+^{7+}, and Rn7+^{7+} under plasma atmosphere

The growing interest in atomic structures of moderately-stripped alkali-like ions in diagnostic study and modeling of astrophysical and laboratory plasma makes an accurate many-body study of atomic properties inevitable. This work presents transition line parameters in the absence or presence of plasma atmosphere for astrophysically important candidates, Ar$^{7+}$, Kr$^{7+}$, Xe$^{7+}$, and Rn$^{7+}$. We employ relativistic coupled-cluster (RCC) theory, a well-known correlation exhaustive method. In the case of a plasma environment, we use Debye Model. Our calculations agree with experiments available in the literature for ionization potentials, transition strengths of allowed and forbidden selections, and lifetimes of several low-lying states. The unit ratios of length and velocity forms of transition matrix elements are the critical estimation of the accuracy of the transition data presented here, especially for a few presented first time in the literature. We do compare our findings with the available recent theoretical results. Our reported data can be helpful to the astronomer in estimating the density of the plasma environment around the astronomical objects or in the discovery of observational spectra corrected by that environment. The present results should be advantageous in the modeling and diagnostics laboratory plasma, whereas the calculated ionisation potential depression parameters reveal important characteristics of atomic structure

Electrochemical Reduction of CO₂ on Ir<i>_x</i>Ru_{(1–<i>x</i>)}O₂(110) Surfaces

High overpotentials and low faradic efficiencies plague metal catalysts for direct conversion of CO₂ to methanol and other liquid fuels. RuO₂-based electrocatalysts have been observed to evolve methanol at low overpotentials, which has been attributed to an alternative reaction mechanism with oxygen-coordinated intermediates that can circumvent the limitations imposed by the scaling relations on metal catalysts. Here, we introduce an innovative concept of ligand effects in oxide catalysts. Both IrO₂ and RuO₂ binds OH* and other intermediates from the electrochemical reduction of CO₂ (CO2RR) strongly, but the stable and miscible system Ir_<i>x</i>Ru_(1‑x)O₂ exhibits anomalous weaker binding energy in the presence of CO* spectators, because of Ru–Ir ligand effects. The weakened adsorbate binding leads to a very low CO2RR onset potential (methanol evolution at −0.2 V RHE). An Ir atom at the bridge site with Ru neighbors binds intermediates such as OH* and OCHO* much weaker, because of synergistic ligand effects and adsorbate–adsorbate interactions. Consequently, a RuO₂ surface doped with Ir move close to the top of the predicted CO2RR volcano for oxides, which offers a significant improvement over state-of-the-art electrocatalysts for conversion of CO₂ into methanol. Analysis of electronic structure parameters with adsorbate binding energies indicates the ligand effect depletes electrons from the Ir atom and shifts the t_2g orbitals. The lack of electron donation from CO* spectators to Ir at the active site cause favorable adsorbate binding