Structural Complexity and Phonon Physics in 2D Arsenenes

In the quest for stable 2D arsenic phases, four different structures have been recently claimed to be stable. We show that, due to phonon contributions, the relative stability of those structures differs from previous reports and depends crucially on temperature. We also show that one of those four phases is in fact mechanically unstable. Furthermore, our results challenge the common assumption of an inverse correlation between structural complexity and thermal conductivity. Instead, a richer picture emerges from our results, showing how harmonic interactions, anharmonicity and symmetries all play a role in modulating thermal conduction in arsenenes. More generally, our conclusions highlight how vibrational properties are an essential element to be carefully taken into account in theoretical searches for new 2D materials

Complex networks analysis in socioeconomic models

This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including results for opinion and citation networks. Finally, some avenues for future research are introduced before summarizing the main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared for Complexity and Geographical Economics - Topics and Tools, P. Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published

Finding unprecedentedly low-thermal-conductivity half-Heusler semiconductors via high-throughput materials modeling

The lattice thermal conductivity ({\kappa}{\omega}) is a key property for many potential applications of compounds. Discovery of materials with very low or high {\kappa}{\omega} remains an experimental challenge due to high costs and time-consuming synthesis procedures. High-throughput computational pre-screening is a valuable approach for significantly reducing the set of candidate compounds. In this article, we introduce efficient methods for reliably estimating the bulk {\kappa}{\omega} for a large number of compounds. The algorithms are based on a combination of machine-learning algorithms, physical insights, and automatic ab-initio calculations. We scanned approximately 79,000 half-Heusler entries in the AFLOWLIB.org database. Among the 450 mechanically stable ordered semiconductors identified, we find that {\kappa}{\omega} spans more than two orders of magnitude- a much larger range than that previously thought. {\kappa}{\omega} is lowest for compounds whose elements in equivalent positions have large atomic radii. We then perform a thorough screening of thermodynamical stability that allows to reduce the list to 77 systems. We can then provide a quantitative estimate of {\kappa}{\omega} for this selected range of systems. Three semiconductors having {\kappa}{\omega} < 5 W /(m K) are proposed for further experimental study.Comment: 9 pages, 4 figure