相关论文: Emerging disciplines based on superatoms: a perspe…

Engineered nanoparticles made from noble metals, rare-earth oxides or semiconductors are emerging as the central constituents of future nanotech developments. In this review, a survey of the complexing strategies between nanoparticles and…

Using a sample of 903 APM clusters we investigate whether their dynamical status, as evidenced by the presence of significant substructures, is related to the large-scale structure of the Universe. We find that the cluster dynamical…

Extensions of nuclear supersymmetry are discussed, together with a proposal for new, more stringent and precise tests that probe the susy classification and specific two-particle correlations among supersymmetric partners. The combination…

Unsupervised machine learning, and in particular data clustering, is a powerful approach for the analysis of datasets and identification of characteristic features occurring throughout a dataset. It is gaining popularity across scientific…

Superfunctional materials are defined as materials with specific properties being superior to the functions of engineering materials. Numerous studies introduced severe plastic deformation (SPD) as an effective process to improve the…

Driven by the recent rapid increase in the number of materials databases published (open and commercial), I discuss here some perspectives on the growing need for standardized, interoperable, open databases. The field of computational…

I take a quick overview at the recent development of combinatorics and its current directions, as a discipline in its own right, as part of mathematics, and as part of science and wider society.

Recent advances in atomic and nano-scale growth and characterization techniques have led to the production of modern magnetic materials and magneto-devices which reveal a range of new fascinating phenomena. The modeling of these is a tough…

In this paper we study research trends in condensed matter physics. Trends are analyzed by means of the the number of publications in the different sub-fields as function of the years. We found that many research topics have a similar…

Advances in machine learning have impacted myriad areas of materials science, ranging from the discovery of novel materials to the improvement of molecular simulations, with likely many more important developments to come. Given the rapid…

In this paper we discuss various philosophical aspects of the hyperstructure concept extending networks and higher categories. By this discussion we hope to pave the way for applications and further developments of the mathematical theory…

At the forefront of nanochemistry, there exists a research endeavor centered around intermetallic nanocrystals, which are unique in terms of long-range atomic ordering, well-defined stoichiometry, and controlled crystal structure. In…

The properties and applications of metallic nanoparticles are inseparably connected not only to their detailed morphology and composition, but also to their structural configuration and mutual interactions. As a result, the assemblies often…

Machine learning has now become an integral part of research and innovation. The field of machine learning density functional theory has continuously expanded over the years while making several noticeable advances. We briefly discuss the…

Density functional calculations were performed to systematically study a series of finite and infinite cluster-assembled silicon nanotubes (SiNTs). One-dimensional SiNTs can be prepared by proper assembly of hydrogenated cage-like silicon…

Here we will give a perspective on new possible interplays between Machine Learning and Quantum Physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum…

The application of high end computing to astrophysical problems, mainly in the galactic environment, is under development since many years at the Dep. of Physics of Sapienza Univ. of Roma. The main scientific topic is the physics of self…

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongly coupled plasma physics, high pressure physics and high…

The theoretical expectations for the supersymmetric particle spectrum is reviewed and a brief overview on present constraints on supersymmetric models from collider experiments is presented. Finally, we discuss the discovery potential of…

We summarize what has been learned about the neutrino mass spectrum and neutrino mixing, identify interesting open questions that can be answered by accelerator neutrino facilities of the future, and discuss the importance and physics of…