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As an elementary type of collective excitation, plasmon has been found to dominate the optical properties of metals. The collective behavior of electrons in plasmons reflects the important difference between condensed matter and molecule-like ones. It is of great significance to study the evolution of plasmonic response and find out the boundary.
Controversy exists on such interesting questions as the division between the nanoparticle and molecules, and the physics of mesoscopic and microscopic plasmonic evolution. A unified understanding covering the small and large size limit, namely macro / meso / micro scales with sufficiently atomic precision is thus required. Clusters, as the transition from atomic molecules to condensed matter, are the ideal candidate for studying the evolution of plasmons.
Recently, the research team led by academician GUO Guangcan from the USTC of the Chinese Academy of Sciences has made security analysis and improvement of source independent quantum random number generators with imperfect devices.
A breakthrough that has implications for molecular biology, pharmacology and nanotechnologies. The fields of application are many. Identifying the mechanisms behind neurodegenerative processes in some proteins, for example, can help limit their proliferation. Understanding how a protein takes on a certain shape can open the way to use the nanomachines that nature has designed to cut, edit or block damaged or defective genes. Their study was published in the international academic journal Physical Review Letters
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Researchers from the University of Cambridge, the University of Milan and Google Research have used machine learning techniques to predict how proteins, particularly those implicated in neurological diseases, completely change their shapes in a matter of microseconds.
They found that when amyloid beta, a key protein implicated in Alzheimer s disease, adopts a highly disordered shape, it actually becomes less likely to stick together and form the toxic clusters which lead to the death of brain cells.
The results, reported in the journal
Nature Computational Science, could aid in the future development of treatments for diseases involving disordered proteins, such as Alzheimer s disease and Parkinson s disease.
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VIDEO: This is a high-speed Atomic Force Microscope movie of the first steps of viral self-assembly. It shows how a hexamer at the edge of the growing lattice gradually forms from. view more
Credit: Wouter Roos, University of Groningen
The reproductive cycle of viruses requires self-assembly, maturation of virus particles and, after infection, the release of genetic material into a host cell. New physics-based technologies allow scientists to study the dynamics of this cycle and may eventually lead to new treatments. In his role as physical virologist, Wouter Roos, a physicist at the University of Groningen, together with two longtime colleagues, has written a review article on these new technologies, which was published in