Tailored cobalt-salen complexes enable electrocatalytic intramolecular allylic C-H functionalizations.

Oxidative allylic C-H functionalization is a powerful tool to streamline organic synthesis as it minimizes the need for functional group activation and generates alkenyl-substituted products amenable to further chemical modifications. The intramolecular variants can be used to construct functionalized ring structures but remain limited in scope and by their frequent requirement for noble metal catalysts and stoichiometric chemical oxidants. Here we report an oxidant-free, electrocatalytic approach to achieve intramolecular oxidative allylic C-H amination and alkylation by employing tailored cobalt-salen complexes as catalysts.

Antigenicity of tissues and organs from GGTA1/CMAH/β4GalNT2 triple gene knockout pigs.

Clinical xenotransplantations have been hampered by human preformed antibody-mediated damage of the xenografts. To overcome biological incompatibility between pigs and humans, one strategy is to remove the major antigens [Gal, Neu5Gc, and Sd(a)] present on pig cells and tissues. Triple gene (GGTA1, CMAH, and β 4GalNT2) knockout (TKO) pigs were produced in our laboratory by CRISPR-Cas9 targeting.

Detecting fast signals beyond bandwidth of detectors based on computational temporal ghost imaging.

Measurement of fast signal is getting more and more important in many fields. In this paper, we propose to detect a temporal signal based on the idea of computational ghost imaging (GI), which can greatly reduce requirements on bandwidth of detectors. In experiments, we implement retrieving of a temporal signal with time scale of 50ns using a detector of 1kHz bandwidth, which is much lower than the requirement on bandwidth of detector according to information theory.

Multi-scale Adaptive Computational Ghost Imaging.

In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme.

Experimental quantum state tomography via compressed sampling.

A fundamental difficulty in demonstrating quantum state tomography is that the required resources grow exponentially with the system size. For pure states and nearly pure states, the task of tomography can be more efficient. We proposed two methods for state reconstruction, by (1) minimizing entropy and (2) maximizing likelihood.