Satya S. Bulusu

Methanol clusters (CH3OH)n: putative global minimum-energy structures from model potentials and dispersion-corrected density functional theory.

Putative global minima are reported for methanol clusters (CH3OH)n with n ≤ 15. The predictions are based on global optimization of three intermolecular potential energy models followed by local optimization and single-point energy calculations using two variants of dispersion-corrected density functional theory. Recurring structural motifs include folded and/or twisted rings, folded rings with a short branch, and stacked rings. Many of the larger structures are stabilized by weak C-H···O bonds.

Neural network potentials for dynamics and thermodynamics of gold nanoparticles

For understanding the dynamical and thermodynamical properties of metal nanoparticles, one has to go beyond static and structural predictions of a nanoparticle. Accurate description of dynamical properties may be computationally intensive depending on the size of nanoparticle. Herein, we demonstrate the use of atomistic neural network potentials, obtained by fitting quantum mechanical data, for extensive molecular dynamics simulations of gold nanoparticles. The fitted potential was tested by performing global optimizations of size selected gold nanoparticles (Aun, 17 ≤ n ≤ 58). We performed molecular dynamics simulations in canonical (NVT) and microcanonical (NVE) ensembles on Au17, Au34, Au58 for a total simulation time of around 3 ns for each nanoparticle. Our study based on both NVT and NVE ensembles indicate that there is a dynamical coexistence of solid-like and liquid-like phases near melting transition. We estimate the probability at finite temperatures for set of isomers lying below 0.5 eV from the global minimum structure. In the case of Au17 and Au58, the properties can be estimated using global minimum structure at room temperature, while for Au34, global minimum structure is not a dominant structure even at low temperatures.

Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147 nanocluster

We propose a highly efficient method for fitting the potential energy surface of a nanocluster using a spherical harmonics based descriptor integrated with an artificial neural network. Our method achieves the accuracy of quantum mechanics and speed of empirical potentials. For large sized gold clusters (Au147), the computational time for accurate calculation of energy and forces is about 1.7 s, which is faster by several orders of magnitude compared to density functional theory (DFT). This method is used to perform the global minimum optimizations and molecular dynamics simulations for Au147, and it is found that its global minimum is not an icosahedron. The isomer that can be regarded as the global minimum is found to be 4 eV lower in energy than the icosahedron and is confirmed from DFT. The geometry of the obtained global minimum contains 105 atoms on the surface and 42 atoms in the core. A brief study on the fluxionality in Au147 is performed, and it is concluded that Au147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

Density functional theory guided Monte Carlo simulations: Application to melting of Na13

We present a density functional theory (DFT) based Monte Carlo simulation method in which a simple energy function gets fitted on-the-fly to DFT energies and gradients. The fitness of the energy function gets tested periodically using the classical importance function technique [R. Iftimie, D. Salahub, D. Wei, and J. Schofield, J. Chem. Phys. 113, 4852 (2000)]. The function is updated to fit the DFT energies and gradients of the most recent structures visited whenever it fails to achieve a preset accuracy. In this way, we effectively break down the problem of fitting the entire potential energy surface (PES) into many easier problems, which are to fit small local regions of the PES. We used the scaled Morse potential empirical function to guide a DFT Monte Carlo simulation of Na(13) at various temperatures. The use of empirical function guide produced a computational speed-up of about 7 in our test system without affecting the quality of the results.

Structural Evolution of Gold Clusters Aun - (n = 21-25) Revisited

We performed a combined theoretical and experimental photoelectron spectroscopy study of the structural evolution of gold anion clusters Aun- in the size range n = 21-25, a special size range for gold anion clusters where extensive structural changes from the pyramidal structure at Au20- toward the core-shell structure at Au26- were expected to occur. Density functional theory calculations with inclusion of spin-orbit effects were employed to produce the simulated spectra for the selected low-energy isomers obtained from basin-hopping global minimum search. The comparison of these simulated spectra with reasonably well-resolved experimental photoelectron spectra resulted in the identification of the low-lying structures of the gold clusters. The fused-planar and hollow-tubular structures are found dominant in this special size range. The highly stable tetrahedral Au20 unit (viewed as the fragment of face-centered cubic (FCC) bulk gold) was found intact only in the minor isomer at n = 21, whereas hollow-tubular structures were found prevalent in the n = 22-25 range. At n = 25, the dominant structure is a hollow-tubular one with two of gold pyramids fused together, but not a core-shell one as previously believed.

c-T phase diagram and Landau free energies of (AgAu)55 nanoalloy via neural-network molecular dynamic simulations

For understanding the structure, dynamics, and thermal stability of (AgAu)55 nanoalloys, knowledge of the composition-temperature (c-T) phase diagram is essential due to the explicit dependence of properties on composition and temperature. Experimentally, generating the phase diagrams is very challenging, and therefore theoretical insight is necessary. We use an artificial neural network potential for (AgAu)55 nanoalloys. Predicted global minimum structures for pure gold and gold rich compositions are lower in energy compared to previous reports by density functional theory. The present work based on c-T phase diagram, surface area, surface charge, probability of isomers, and Landau free energies supports the enhancement of catalytic property of Ag-Au nanoalloys by incorporation of Ag up to 24% by composition in Au nanoparticles as found experimentally. The phase diagram shows that there is a coexistence temperature range of 70 K for Ag28Au27 compared to all other compositions. We propose the power spectrum coefficients derived from spherical harmonics as an order parameter to calculate Landau free energies.

Closed-Shell Metal Clusters

Metal clusters are studied for many reasons, including modeling heterogeneous catalysts, understanding how physical properties and chemical reactivity evolve in the intermediate size regime between molecular species and solids, and trying to create building blocks for new materials [1]. The latter requires clusters, and cluster assemblies, that are stable under normal conditions. This is challenging. Taking the viewpoint of the solid state, metal clusters represent the ultra finely divided form of a solid, with an extremely high surface area and very large surface energy. They are inherently unstable [2]. So, one may ask, why go through the trouble of trying to make materials out of clusters, and how?

Correlation of structure with UV-visible spectra by varying SH composition in Au-SH nanoclusters

In the present work, we model artificial neural network (ANN) potentials for Au n (SH) m nanoclusters in the range of n = 10 to n = 38. The accuracy of ANN potentials is tested by comparing the global minimum (GM) structures of Au n (SH) m nanoclusters, at saturated amount of SH, with the earlier reported structures. The GM structures are reported for the first time for nanoclusters with compositions lower than the saturated SH composition. We calculate the probability of low energy isomers to explain the fluxional behaviour of Au n (SH) m nanoclusters at lower SH compositions. Furthermore, we try to correlate the structures of Au n (SH) m nanoclusters with UV-visible spectra based on Time-dependent density functional theory (TDDFT) calculations. The UV-visible spectral analysis reveals that significant spectroscopic variations are observed at different SH compositions. This study provides a fundamental understanding of structural changes with decreasing SH compositions and with increasing the size of the nanocluster.