The size and shape of a metal nanoparticle determine its optical properties. When placed in an array the single particle response is further modified by the scattered fields, which for a random array are unique to each scatterer. However, at the array level scattering and absorption retain single-particle-like spectra. Using T-Matrix calculations and an analytical model of intra-array coupling in amorphous arrays we show how the branching ratio of the localized plasmon decay depends on disorder and particle density. We calculate the effective polarizability and demonstrate its effects on scattering and absorption. The scattering-to-absorption ratio is a function of particle separation in the disordered array and can significantly deviate from the inherent single particle ratio. We trace the period of this oscillatory dependence of the ratio to the single particle plasmon resonance wavelength. This effect has implications for applications in which one of the decay channels has to be dominant, for example, absorption for hot electron−hole pair generation in the metal particles or scattering into a nearby semiconductor.

The effect of external static charging on borophenes -2D boron crystals -is investigated by using first principles calculations. The influence of the excess negative charge on the stability of the 2D structures is examined using a very simple analysis of decomposition of the binding energy of a given boron layer into contributions coming from boron atoms that have different coordination numbers. This analysis is important to understand how the local neighbourhood of an atom influences the overall stability of the monolayer structure. The decomposition is done for the α-sheet and its related family of structures. From this analysis, we have found a preference for 2D boron crystals with very small or very high charges per atom. The structures with intermediate charges are energetically not favourable. We have also found a clear preference in terms of binding energy for the experimentally seen γ-sheet and δ-sheet structures that is almost independent on the considered excess of negative charge of the structures. On the other hand, we have shown that a model based solely on nearest-neighbour interactions, although instructive, is too simple to predict binding energies accurately.

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This work discusses a general-purpose genetic algorithms (Holland, 1975) scientific header-only library named Quilë. The software is written in C++20 and has been released under the terms of the MIT license. It is available at https://github.com/ttarkowski/quile/. The name of the library come from the fictional language Neo-Quenya and means "color" (cf. origin of the word chromosome).Genetic algorithms, or more broadly, evolutionary computations, is a field of computer science devoted to population-based, trial-and-error methods of problem solving. Evolutionary computation was invented by Alan Turing by noting that the principles of biological evolution and genetics can be applied to optimization problems (Turing, 1948(Turing, , 1950. One of the first evolutionary computations performed on a computer was done by Nils A. Barricelli (Barricelli, 1962;Galloway, 2011). Evolutionary computations have found wide applications in many disciplines (