Rich Ground State Chemical Ordering in Nanoparticles: Exact Solution of a Model for Ag-Au Clusters

We show that nanoparticles can have very rich ground state chemical order. This is illustrated by determining the chemical ordering of Ag-Au 309-atom Mackay icosahedral nanoparticles. The energy of the nanoparticles is described using a cluster expansion model, and a Mixed Integer Programming (MIP) approach is used to find the exact ground state configurations for all stoichiometries. The chemical ordering varies widely between the different stoichiometries, and display a rich zoo of structures with non-trivial ordering.Comment: Revised version. New figure added, discussion expanded, some material moved into supplementary fil

Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials

Neural message passing on molecular graphs is one of the most promising methods for predicting formation energy and other properties of molecules and materials. In this work we extend the neural message passing model with an edge update network which allows the information exchanged between atoms to depend on the hidden state of the receiving atom. We benchmark the proposed model on three publicly available datasets (QM9, The Materials Project and OQMD) and show that the proposed model yields superior prediction of formation energies and other properties on all three datasets in comparison with the best published results. Furthermore we investigate different methods for constructing the graph used to represent crystalline structures and we find that using a graph based on K-nearest neighbors achieves better prediction accuracy than using maximum distance cutoff or the Voronoi tessellation graph

Atomic structure optimization with machine-learning enabled interpolation between chemical elements

We introduce a computational method for global optimization of structure and ordering in atomic systems. The method relies on interpolation between chemical elements, which is incorporated in a machine learning structural fingerprint. The method is based on Bayesian optimization with Gaussian processes and is applied to the global optimization of Au-Cu bulk systems, Cu-Ni surfaces with CO adsorption, and Cu-Ni clusters. The method consistently identifies low-energy structures, which are likely to be the global minima of the energy. For the investigated systems with 23-66 atoms, the number of required energy and force calculations is in the range 3-75

Benchmark density functional theory calculations for nano-scale conductance

We present a set of benchmark calculations for the Kohn-Sham elastic transmission function of five representative single-molecule junctions. The transmission functions are calculated using two different density functional theory (DFT) methods, namely an ultrasoft pseudopotential plane wave code in combination with maximally localized Wannier functions, and the norm-conserving pseudopotential code Siesta which applies an atomic orbital basis set. For all systems we find that the Siesta transmission functions converge toward the plane-wave result as the Siesta basis is enlarged. Overall, we find that an atomic basis with double-zeta and polarization is sufficient (and in some cases even necessary) to ensure quantitative agreement with the plane-wave calculation. We observe a systematic down shift of the Siesta transmission functions relative to the plane-wave results. The effect diminishes as the atomic orbital basis is enlarged, however, the convergence can be rather slow.Comment: 10 pages, 7 figure

Band Gap Tuning and Defect Tolerance of Atomically Thin Two- Dimensional Organic-Inorganic Halide Perovskites

Organic–inorganic halide perovskites have proven highly successful for photovoltaics but suffer from low stability, which deteriorates their performance over time. Recent experiments have demonstrated that low dimensional phases of the hybrid perovskites may exhibit improved stability. Here we report first-principles calculations for isolated monolayers of the organometallic halide perovskites (C₄H₉NH₃)₂MX₂Y₂, where M = Pb, Ge, Sn and X,Y = Cl, Br, I. The band gaps computed using the GLLB-SC functional are found to be in excellent agreement with experimental photoluminescence data for the already synthesized perovskites. Finally, we study the effect of different defects on the band structure. We find that the most common defects only introduce shallow or no states in the band gap, indicating that these atomically thin 2D perovskites are likely to be defect tolerant