Drude–Lorentz Model for Optical Properties of Photoexcited Transition Metals under Electron–Phonon Nonequilibrium

Evaluating the optical properties of matter under the action of ultrafast light is crucial in modeling laser–surface interaction and interpreting laser processing experiments. We report optimized coefficients for the Drude–Lorentz model describing the permittivity of several transition metals (Cr, W, Ti, Fe, Au, and Ni) under electron–phonon nonequilibrium, with electrons heated up to 30,000 K and the lattice staying cold at 300 K. A Basin-hopping algorithm is used to fit the Drude–Lorentz model to the nonequilibrium permittivity calculated using ab initio methods. The fitting coefficients are provided and can be easily inserted into any calculation requiring the optical response of the metals during ultrafast irradiation. Moreover, our results shed light on the electronic structure modifications and the relative contributions of intraband and interband optical transitions at high electron temperatures corresponding to the laser excitation fluence used for surface nanostructuring.

Search for Global Minimum Structures of P2n+1+ (n = 1–15) Using xTB-Based Basin-Hopping Algorithm

A new program for searching global minimum structures of atomic clusters using basin-hopping algorithm based on the xTB method was developed here. The program can be performed with a much higher speed than its replacement directly based on DFT methods. Considering the structural varieties and complexities in finding their global minimum structures, phosphorus cluster cations were studied by the program. The global minimum structures of cationic P2n+1+ (n = 1–15) clusters are determined through the unbiased structure searching method. In the last step, further DFT optimization was performed for the selected isomers. For P2n+1+ (n = 1–4, 7), the found global minimum structures are in consistent with the ones previously reported; while for P2n+1+ (n = 5, 6, 8–12), newly found isomers are more energy-favorable than those previously reported. And those for P2n+1+ (n = 13–15) are reported here for the first time. Among them, the most stable isomers of P2n+1+ (n = 4–6, 9) are characterized by their C3v, Cs, C2v and Cs symmetry, in turn. But those of P2n+1+ (n = 7, 8, 10–12), no symmetry has been identified. The most stable isomers of P29+ and P31+ are characterized by single P-P bonds bridging units inside the clusters. Further analysis shows that the pnicogen bonds play an important role in the stabilization of these clusters. These results show that the new developed program is effective and robust in searching global minimum structures for atom clusters, and it also provides new insights into the role of pnicogen bonds in phosphorus clusters.

Investigation of structural and energetic behavior of 55-atom Pt–Ag–Au ternary nanoalloys

A systematic theoretical investigation of structural and energetic behaviors of 55-atom Pt–Ag–Au ternary nanoalloys has been performed in two different composition systems. We have performed Gupta and Density Functional Theory (DFT) approaches on chosen systems. The Basin-Hopping algorithm is used for structural optimizations of PtnAg[Formula: see text]Au[Formula: see text] ([Formula: see text]–13) and PtnAu[Formula: see text]Ag[Formula: see text] ([Formula: see text]–13) ternary nanoalloys with Gupta many-body potential to model interatomic interactions. Local optimization results show that while the tendency of Au atoms to be located varies according to the composition system, the tendency of Pt and Ag atoms to be located does not change in both. For all compositions of Pt–Ag–Au nanoalloys, the structures with the best chemical ordering were then reoptimized by DFT relaxations and the mixing energies of the Gupta and DFT levels were compared. Our mixing energy analysis showed that PtnAg[Formula: see text]Au[Formula: see text] ([Formula: see text]–13) nanoalloys are not energetically suitable for mixing at both Gupta and DFT level. Also, mixing energy variations of PtnAu[Formula: see text]Ag[Formula: see text] ([Formula: see text]–13) nanoalloys obtained at Gupta level does not agree with the one obtained at DFT level. In addition, it has been found that the minimization energy changes when an atom in the central site is exchanging by an atom in the second shell and surface.

Ca+ Ions Solvated in Helium Clusters

We present a combined experimental and theoretical investigation on Ca+ ions in helium droplets, HeNCa+. The clusters have been formed in the laboratory by means of electron-impact ionization of Ca-doped helium nanodroplets. Energies and structures of such complexes have been computed using various approaches such as path integral Monte Carlo, diffusion Monte Carlo and basin-hopping methods. The potential energy functions employed in these calculations consist of analytical expressions following an improved Lennard-Jones formula whose parameters are fine-tuned by exploiting ab initio estimations. Ion yields of HeNCa+ -obtained via high-resolution mass spectrometry- generally decrease with N with a more pronounced drop between N=17 and N=25, the computed quantum HeNCa+ evaporation energies resembling this behavior. The analysis of the energies and structures reveals that covering Ca+ with 17 He atoms leads to a cluster with one of the smallest energies per atom. As new atoms are added, they continue to fill the first shell at the expense of reducing its stability, until N=25, which corresponds to the maximum number of atoms in that shell. Behavior of the evaporation energies and radial densities suggests liquid-like cluster structures.

Exploring the most stable aptamer/target molecule complex by the stochastic tunnelling-basin hopping-discrete molecular dynamics method

The stochastic tunnelling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method was applied to the search for the most stable biomolecular complexes in water by using the MARTINI coarse-grained (CG) model. The epithelial cell adhesion molecule (EpCAM, PDB code: 4MZV) was used as an EpCAM adaptor for an EpA (AptEpA) benchmark target molecule. The effects of two adsorption positions on the EpCAM were analysed, and it is found that the AptEpA adsorption configuration located within the EpCAM pocket-like structure is more stable and the energy barrier is lower due to the interaction with water. By the root mean square deviation (RMSD), the configuration of EpCAM in water is more conservative when the AptEpA binds to EpCAM by attaching to the pocket space of the EpCAM dimer. For AptEpA, the root mean square fluctuation (RMSF) analysis result indicates Nucleobase 1 and Nucleobase 2 display higher flexibility during the CGMD simulation. Finally, from the binding energy contour maps and histogram plots of EpCAM and each AptEpA nucleobase, it is clear that the binding energy adsorbed to the pocket-like structure is more continuous than that energy not adsorbed to the pocket-like structure. This study has proposed a new numerical process for applying the STUN-BH-DMD with the CG model, which can reduce computational details and directly find a more stable AptEpA/EpCAM complex in water.

Application of Optimization Algorithms in Clusters

The structural characterization of clusters or nanoparticles is essential to rationalize their size and composition-dependent properties. As experiments alone could not provide complete picture of cluster structures, so independent theoretical investigations are needed to find out a detail description of the geometric arrangement and corresponding properties of the clusters. The potential energy surfaces (PES) are explored to find several minima with an ultimate goal of locating the global minima (GM) for the clusters. Optimization algorithms, such as genetic algorithm (GA), basin hopping method and its variants, self-consistent basin-to-deformed-basin mapping, heuristic algorithm combined with the surface and interior operators (HA-SIO), fast annealing evolutionary algorithm (FAEA), random tunneling algorithm (RTA), and dynamic lattice searching (DLS) have been developed to solve the geometrical isomers in pure elemental clusters. Various model or empirical potentials (EPs) as Lennard–Jones (LJ), Born–Mayer, Gupta, Sutton–Chen, and Murrell–Mottram potentials are used to describe the bonding in different type of clusters. Due to existence of a large number of homotops in nanoalloys, genetic algorithm, basin-hopping algorithm, modified adaptive immune optimization algorithm (AIOA), evolutionary algorithm (EA), kick method and Knowledge Led Master Code (KLMC) are also used. In this review the optimization algorithms, computational techniques and accuracy of results obtained by using these mechanisms for different types of clusters will be discussed.

Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios

Starting from an original portfolio of life insurance policies, in this article we propose a methodology to select model points portfolios that reproduce the original one, preserving its market risk under a certain measure. In order to achieve this goal, we first define an appropriate risk functional that measures the market risk associated to the interest rates evolution. Although other alternative interest rate models could be considered, we have chosen the LIBOR (London Interbank Offered Rate) market model. Once we have selected the proper risk functional, the problem of finding the model points of the replicating portfolio is formulated as a problem of minimizing the distance between the original and the target model points portfolios, under the measure given by the proposed risk functional. In this way, a high-dimensional global optimization problem arises and a suitable hybrid global optimization algorithm is proposed for the efficient solution of this problem. Some examples illustrate the performance of a parallel multi-CPU implementation for the evaluation of the risk functional, as well as the efficiency of the hybrid Basin Hopping optimization algorithm to obtain the model points portfolio.