We present a universal method for the largescale prediction of the atomic structure of clusters. Our algorithm performs the joint evolutionary search for all clusters in a given area of the compositional space and takes advantage of structural similarities frequently observed in clusters of close compositions. The resulting speedup is up to 50 times compared to current methods. This enables the first-principles studies of multi-component clusters with full coverage of a wide range of compositions. As an example, we report an unprecedented firstprinciples global optimization of 315 Si n O m clusters with n ≤ 15 and m ≤ 20. The obtained map of Si-O cluster stability shows the existence of both expected (SiO 2 ) n and unexpected (e.g. Si 4 O 18 ) stable (magic) clusters, which can be important for miscellaneous applications.Graphical TOC Entry 1 arXiv:1812.06568v1 [cond-mat.mtrl-sci] 17 Dec 2018The unique properties of nanoparticles are extensively used in optoelectronics, photovoltaics, photocatalysis, biomedicine, etc. These properties are closely linked to the atomic structure of particles, what is more explicit in the small particles and nanoclusters. 1,2 Despite the importance of knowing the structure, its experimental determination remains very difficult. 3 For this reason the main body of structural information on clusters is obtained via first-principles calculations 4 which were mostly done either for monoatomic clusters or for binary clusters of stoichiometric composition corresponding to the bulk compounds, while clusters of general composition were studied only in few publications. 5,6 Such an accent in ab initio research ignores the fact that the chemistry of clusters is much richer than that of solids because of a large share of surface atoms. Multi-component clusters often have stable compositions, which are far from chemical compounds presented in the bulk x-T phase diagram. This is of interest not only for basic chemistry of clusters. It significantly increases the scope of candidate nanomaterials for practical applications such as: the development of efficient and affordable catalysts 7,8 and magnets, 9 the investigation of complex processes of nucleation and particle growth, 10-12 etc.The bottle-neck of first-principles activity in cluster studies is the computational cost of atomic structure determination, which is a global optimization of the total energy among all possible atomic configurations. There are several methods of structure prediction (basin and minima hopping, 13,14 simulated annealing, 15 evolutionary algorithm, 16 etc.), however they all involve thousands of local optimizations (relaxations) even for finding a structure of one cluster. In the applications mentioned above, the computation of atomic structure and the screening of stability and properties are required in wide regions including hundreds of cluster compositions, therefore such firstprinciples investigations turn out extremely exhausting. To reduce the computational cost, the global optimization is frequently performed ...

Understanding the high-pressure behavior of C-H system is of great importance due to its key role in organic, bio-, petroleum and planetary chemistry. We have performed a systematic investigation of the pressure-composition phase diagram of the C-H system at pressures up to 400 GPa using evolutionary structure prediction coupled with ab initio calculations and discovered that only saturated hydrocarbons are thermodynamically stable. Several stable methane-hydrogen co-crystals are predicted: 2CH4 * H2, earlier obtained experimentally, is predicted to have I4/m space group and 2-90 GPa stability range at 0 K, and two new thermodynamically stable compounds 2CH4 * 7H2 (P-3m1 space group) and CH4 * 9H2 (Cm space group), as potential energy storage materials. P21/c phase of methane is predicted to be stable at pressures < 8 GPa; bulk graphane (CH) was shown to be thermodynamically stable at 7-18 and 18-50 GPa and 0 K in the P-3m and Cmca phases, respectively; polyethylene is shown to have a narrow field of stability. We report the p-T-x phase diagram of the C-H system and p-T phase diagram of CH4.

Crystalline silica (SiO2) is a major material used in many technologies, yet the exact surface structures of silica polymorphs are still mostly unknown. Here we perform a comprehensive study of surface reconstructions of α-cristobalite (001), α-quartz (001) and stishovite (110) and (100) using evolutionary algorithm USPEX in conjunction with ab initio calculations. We found the well-known “dense surface” to be among low-energy reconstructions of α-quartz (001), as well as its previously proposed distorted version, which we call “shifted surface”. For cristobalite and stishovite we show the formation of reconstructions without dangling bonds which share common features with well-known “dense surface” of α-quartz (001). We call them “dense cristobalite” and “dense stishovite” – all of these have honeycomb arrangements of corner-sharing SiO4-tetrahedra in the surface layers. These tetrahedral honeycombs have very low surface energies, and such tetrahedral surface pattern is observed even in stishovite (the bulk structure of which has SiO6-octahedra, rather than SiO4-tetrahedra).

No abstract

We address the question why among the multitude of imaginable C n H m compositions some are easily synthesizable and abundant in nature, while others are not. To shed light on this problem we borrow approaches from nanocluster study, where stability with respect to neighboring compositions is used as a criterion of “magic” (particularly stable) clusters. By merging this criterion with predictions of lowest-energy structures of all C n H m molecules in a wide range of compositions (n ≤ 20, m ≤ 42) we provide guidelines for predicting the presence or absence of certain hydrocarbon molecules in various environments, their relative abundance and reactivity/inertness. The resulting maps of stability show the increased stability of C2n H2 compounds, polyaromatic hydrocarbons, and diamondoids, which is supported by experimental studies of the interstellar medium, flames, and petroleum fractions. This approach can be applied to any other molecular system, rationalizing the diversity of known compounds and predicting new potentially synthesizable molecules.

Oxidation of silicon nanoclusters depending on the temperature and oxygen pressure is explored from first principles using the evolutionary algorithm, and structural and thermodynamic analysis. From our calculations of 90 SiO clusters we found that under normal conditions oxidation does not stop at the stoichiometric SiO composition, as it does in bulk silicon, but goes further placing extra oxygen atoms on the cluster surface. These extra atoms are responsible for light emission, relevant to reactive oxygen species and many of them are magnetic. We argue that the super-oxidation effect is size-independent and discuss its relevance to nanotechnology and miscellaneous applications, including biomedical ones.

Silicon nanocrystals (NC) have great potential for applications in optoelectronics, photovoltaics and biomedicine. The photo-physical characteristics of these particles strongly depend on whether they are crystalline or amorphous. This structural...

PACS 73.22.-f-Electronic structure of nanoscale materials and related systems PACS 61.46.Bc-Structure of clusters (e.g., metcars; not fragments of crystals; free or loosely aggregated or loosely attached to a substrate) PACS 64.75.Jk-Phase separation and segregation in nanoscale systems Abstract-The total energy and geometry of nanoclusters Si10H2m (m = 0-12) are calculated using evolutionary structure searching and density functional theory. The calculation shows that the arrangement of Si atoms is close to the diamond crystal structure only in the cluster Si10H16, while in others it is unique for each composition. We found that the ensemble of Si10 clusters remains uniform after passivation only if hydrogen concentration corresponds to one of the stable compositions-Si10, Si10H14, Si10H16 Si10H20, or Si10H22. Passivation by an arbitrary amount of hydrogen converts the ensemble into a mixture of the stable clusters having the nearest compositions. In addition there are numerous metastable cluster configurations with energies within ∼ 0.1 eV above the ground state. These metastable configurations come into existence in synthesis at T ≥ 500 K, making experimentally realizable cluster compositions even more diverse.