Abstract: A ZSM-23 zeolite and a preparation process thereof are provided. The pore volume of mesopores having a pore size of 3-8 nm of the zeolite is 45-90% of the total pore volume of the zeolite. The zeolite has a relative crystallinity of 95-120% and a relative crystallinity retention of 95-100% after a hydrothermal treatment with steam for 2 hours at 600° C. The process for preparing the zeolite includes the following steps: (1) preparing or selecting a silicon source for preparing the ZSM-23 zeolite, such as amorphous silica; (2) performing an alkali treatment on the silicon source for preparing the ZSM-23 zeolite such as amorphous silica mentioned in step (1); and (3) preparing the ZSM-23 zeolite by using the alkali-treated amorphous silica as the silicon source. The ZSM-23 zeolite has a rich mesoporous structure and a good hydrothermal stability.

Abstract: A ZSM-23 zeolite and a process for preparing the same and use thereof are provided. The total acid amount of the ZSM-23 zeolite is 0.05-0.25 mmol/g, preferably 0.06-0.22 mmol/g, more preferably 0.06-0.20 mmol/g. The strong acid content of the ZSM-23 zeolite is 5-33%, preferably 7-33%, more preferably 9-33%, or further preferably 7-31%, further more preferably 10-28% of the total acid amount. The strong acid refers to an acid having a desorption temperature of 350° C. or higher in an NH3 temperature programmed desorption (NH3-TPD). The ZSM-23 zeolite has a low strong acid content.

Abstract: An method and an apparatus for generating an image, and an electronic device are provided. The method comprises: performing a plurality of types of image enhancement processing on an image to be processed respectively to obtain a plurality of pre-enhanced images; performing image quality classification on a first image block in the image to be processed to obtain a first quality classification result for the first image block; determining a target pre-enhanced image from the plurality of pre-enhanced images based on the first quality classification result for the first image block; determining a second image block in the target pre-enhanced image; and generating a target image based on the second image block.

Abstract: Disclosed is a hydrocracking catalyst, a preparation method and an application thereof. The catalyst comprises a carrier, silicon dioxide and active ingredients loaded on the carrier, wherein the carrier comprises Y molecular sieves and SAPO-34 molecular sieves. The preparation method of the hydrocracking catalyst comprises the following steps: (1) mixing materials comprising Y molecular sieves and SAPO-34 molecular sieves, and then subjecting the mixture to molding, drying and calcinating to obtain a carrier; (2) introducing silane and the active ingredients into the carrier prepared in the step (1), subsequently performing the drying and calcinating to prepare the hydrocracking catalyst. The catalyst prepared with the method can be used for hydrocracking reaction, thereby significantly increase yield of jet fuel.

Abstract: A DLM-1 molecular sieve, a process for preparing the molecular sieve, and use thereof in treating an organic substance are provided. The DLM-1 molecular sieve is an Al-SBA-15 molecular sieve, and has a schematic chemical composition as represented by the formula “first oxide*second oxide”. The first oxide is silica, the second oxide is alumina, and the content by mass percent of alumina in the schematic chemical composition is 2% to 85%. The DLM-1 molecular sieve is suitable for the hydrodenitrogenation reaction of heavy distillate oil, and is favorable for improving the hydrodenitrogenation activity.

Abstract: The embodiments of the present application provide method, apparatus, electronic device, and medium for image super-resolution and model training. The method includes: inputting the image to be processed into a first super-resolution network model and a second super-resolution network model trained in advance, respectively; the first super-resolution network model is a trained convolutional neural network; the second super-resolution network model is a generative network included in a trained generative adversarial network; obtaining a first image output from the first super-resolution network model and a second image output from the second super-resolution network model; fusing the first image and the second image to obtain a target image, wherein the resolution of the target image is greater than the resolution of the image to be processed.

Abstract: Disclosed is a hydrocracking catalyst, a preparation method and an application thereof. The catalyst comprises a carrier, silicon dioxide and active ingredients loaded on the carrier, wherein the carrier comprises Y molecular sieves and SAPO-34 molecular sieves. The preparation method of the hydrocracking catalyst comprises the following steps: (1) mixing materials comprising Y molecular sieves and SAPO-34 molecular sieves, and then subjecting the mixture to molding, drying and calcinating to obtain a carrier; (2) introducing silane and the active ingredients into the carrier prepared in the step (1), subsequently performing the drying and calcinating to prepare the hydrocracking catalyst. The catalyst prepared with the method can be used for hydrocracking reaction, thereby significantly increase yield of jet fuel.

Abstract: An method and an apparatus for generating an image, and an electronic device are provided. The method comprises: performing a plurality of types of image enhancement processing on an image to be processed respectively to obtain a plurality of pre-enhanced images; performing image quality classification on a first image block in the image to be processed to obtain a first quality classification result for the first image block; determining a target pre-enhanced image from the plurality of pre-enhanced images based on the first quality classification result for the first image block; determining a second image block in the target pre-enhanced image; and generating a target image based on the second image block.

Abstract: A method for preparing hexadecahydropyrene includes the step of carrying out the hydrogenation reaction to hydrocarbon oil containing pyrene compounds in the presence of a hydrogenation catalyst. The pyrene compounds are selected from at least one of pyrene and unsaturated hydrogenation products thereof. The hydrogenation catalyst contains a carrier and an active metal component loaded on the carrier. The active metal component is Pt and/or Pd and the carrier contains a small crystal size Y zeolite, alumina and amorphous silica-alumina. The small crystal size Y zeolite has an average grain diameter of 200-700 nm, a molar ratio of SiO2 to Al2O3 of 40-120, a relative crystallinity of ?95%, and a specific surface area of 900-1,200 m2/g. The pore volume of secondary pores in 1.7-10 nm diameter is more than 50% of the total pore volume.

Abstract: A method for preparing hexadecahydropyrene includes the step of carrying out the hydrogenation reaction to hydrocarbon oil containing pyrene compounds in the presence of a hydrogenation catalyst. The pyrene compounds are selected from at least one of pyrene and unsaturated hydrogenation products thereof. The hydrogenation catalyst contains a carrier and an active metal component loaded on the carrier. The active metal component is Pt and/or Pd and the carrier contains a small crystal size Y zeolite, alumina and amorphous silica-alumina. The small crystal size Y zeolite has an average grain diameter of 200-700 nm, a molar ratio of SiO2 to Al2O3 of 40-120, a relative crystallinity of ?95%, and a specific surface area of 900-1,200 m2/g. The pore volume of secondary pores in 1.7-10 nm diameter is more than 50% of the total pore volume.