Enantioselective Organocatalytic Singly Occupied Molecular Orbital Activation: The Enantioselective α-Enolation of Aldehydes

The first enantioselective organocatalytic α-enolation of aldehydes has been accomplished using singly occupied molecular orbital (SOMO) catalysis. Chiral secondary amines react with aldehydes to form transient enamines that undergo selective one-electron oxidation to generate electrophilic radical cations. These SOMO-activated radical cations are susceptible to attack by ketone-derived enol silanes, rendering α-substituted-γ-ketoaldehyde products with uniformly high levels of asymmetric induction. Wide latitude in both the aldehyde and enolsilane component is readily accommodated, allowing generic access to a diverse assortment of enantioenriched 1,4-dicarbonyl compounds. This report highlights the potential of SOMO catalysis to enable the development of entirely new classes of asymmetric reactions that have no traditional catalytic equivalents

Controlling the Magnetic Anisotropy of the van der Waals Ferromagnet Fe3GeTe2 through Hole Doping.

Identifying material parameters affecting properties of ferromagnets is key to optimized materials that are better suited for spintronics. Magnetic anisotropy is of particular importance in van der Waals magnets, since it not only influences magnetic and spin transport properties, but also is essential to stabilizing magnetic order in the two-dimensional limit. Here, we report that hole doping effectively modulates the magnetic anisotropy of a van der Waals ferromagnet and explore the physical origin of this effect. Fe3-xGeTe2 nanoflakes show a significant suppression of the magnetic anisotropy with hole doping. Electronic structure measurements and calculations reveal that the chemical potential shift associated with hole doping is responsible for the reduced magnetic anisotropy by decreasing the energy gain from the spin-orbit induced band splitting. Our findings provide an understanding of the intricate connection between electronic structures and magnetic properties in two-dimensional magnets and propose a method to engineer magnetic properties through doping

Switching Magnetism and Superconductivity with Spin-Polarized Current in Iron-Based Superconductor

We have explored a new mechanism for switching magnetism and superconductivity in a magnetically frustrated iron-based superconductor using spin-polarized scanning tunneling microscopy (SPSTM). Our SPSTM study on single crystal Sr$_2$VO$_3$FeAs shows that a spin-polarized tunneling current can switch the Fe-layer magnetism into a non-trivial $C_4$ (2$\times$2) order, not achievable by thermal excitation with unpolarized current. Our tunneling spectroscopy study shows that the induced $C_4$ (2$\times$2) order has characteristics of plaquette antiferromagnetic order in Fe layer and strongly suppressed superconductivity. Also, thermal agitation beyond the bulk Fe spin ordering temperature erases the $C_4$ state. These results suggest a new possibility of switching local superconductivity by changing the symmetry of magnetic order with spin-polarized and unpolarized tunneling currents in iron-based superconductors.Comment: 33 pages, 16 figure

Study of a Vocal Feature Selection Method and Vocal Properties for Discriminating Four Constitution Types

The voice has been used to classify the four constitution types, and to recognize a subject's health condition by extracting meaningful physical quantities, in traditional Korean medicine. In this paper, we propose a method of selecting the reliable variables from various voice features, such as frequency derivative features, frequency band ratios, and intensity, from vowels and a sentence. Further, we suggest a process to extract independent variables by eliminating explanatory variables and reducing their correlation and remove outlying data to enable reliable discriminant analysis. Moreover, the suitable division of data for analysis, according to the gender and age of subjects, is discussed. Finally, the vocal features are applied to a discriminant analysis to classify each constitution type. This method of voice classification can be widely used in the u-Healthcare system of personalized medicine and for improving diagnostic accuracy