Abstract: Disclosed is a method for preparing fast ionic conductors based on in-situ polymerization, which uses the spatial resistance volume effect to widen ion migration channels by copolymerizing high spatial resistance monomers with highly reactive crosslinkers, resulting in shorter ion transport paths and substantially higher ionic conductivity of in-situ solid-state polymer electrolytes; also, the high spatial resistance monomers and highly reactive crosslinkers synergistically construct a three-dimensional network structure with both high mechanical strength and stable electrode electrolyte interface properties.

Abstract: According to the application, a double interphase layer strategy with self-healing function is constructed at an interphase between an in-situ solid-state electrolyte and a lithium metal by the synergistic effect of double Lewis acids, a first protective layer inhibits a side reaction of the lithium metal and the in-situ solid-state electrolyte, and a second protective layer self-heals defects of the double interphase layer. The application solves the problem of unstable interface between electrode and electrolyte of in-situ solid-state lithium metal battery, and obtains lithium metal battery with high energy density, high coulombic efficiency and ultra-long cycling life.

Abstract: The present disclosure relates to a method and apparatus for classifying pixels in an input image and image processing system. The apparatus includes a first confidence determination unit configured for determining a first confidence of each of the pixels in the input image belonging to each of a plurality of predetermined classes; a detection unit configured for acquiring, by using a detector for detecting a particular class among the plurality of predetermined classes, detection results used to indicate pixels which belong to the particular class; an updating unit configured for updating the first confidences according to the detection results; and a class determination unit configured for determining the class to which each of the pixels in the input image belongs among the plurality of predetermined classes, according to the updated first confidences.

Abstract: The present disclosure relates to a method and apparatus for classifying pixels in an input image and image processing system. The apparatus includes a first confidence determination unit configured for determining a first confidence of each of the pixels in the input image belonging to each of a plurality of predetermined classes; a detection unit configured for acquiring, by using a detector for detecting a particular class among the plurality of predetermined classes, detection results used to indicate pixels which belong to the particular class; an updating unit configured for updating the first confidences according to the detection results; and a class determination unit configured for determining the class to which each of the pixels in the input image belongs among the plurality of predetermined classes, according to the updated first confidences.