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    BIOAUGMENTATION TREATMENT PROCESS FOR LITHIUM BATTERY PRODUCING WASTEWATER
    63.
    发明申请
    BIOAUGMENTATION TREATMENT PROCESS FOR LITHIUM BATTERY PRODUCING WASTEWATER 有权

    公开(公告)号：US20220402791A1

    公开(公告)日：2022-12-22

    申请号：US17883032

    申请日：2022-08-08

    Applicant: NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY ,  ZHENRUN ENVIRONMENTAL SCIENCE AND TECHNOLOGY CO., LTD.

    Inventor： Jinyou SHEN ,  Hebing ZHANG ,  Jing WANG ,  Junfeng HE ,  Xinbai JIANG ,  Hong WANG ,  Cheng HOU ,  Xiaodong LIU

    IPC: C02F3/30 ,  C02F3/34

    Abstract: The present invention relates to the technical field of wastewater treatment, and discloses a bioaugmentation treatment process for lithium battery producing wastewater. The method comprises the following steps: 1) introducing wastewater into a hydrolytic acidification tank, and adding Enterobacter sp. NJUST50 and activated sludge to the hydrolytic acidification tank for hydrolytic acidification treatment; 2) introducing the effluent into an anoxic tank, and adding Enterobacter sp. NJUST50 and anaerobic activated sludge for anoxic treatment; 3) introducing the effluent into an aerobic tank, and adding Enterobacter sp. NJUST50 and aerobic activated sludge for aerobic treatment; 4) introducing the effluent into an anoxic filter tank, and adding Enterobacter sp. NJUST50 and anaerobic activated sludge to the filter tank for treatment; and 5) introducing the effluent into a biological aerated filter tank, and adding a sludge mixture of Enterobacter sp. NJUST50 with aerobic activated sludge to the filter tank for treatment.

    A SINGLE-SHOT DIFFERENTIAL PHASE CONTRAST QUANTITATIVE PHASE IMAGING METHOD BASED ON COLOR MULTIPLEXED ILLUMINATION
    64.
    发明申请
    A SINGLE-SHOT DIFFERENTIAL PHASE CONTRAST QUANTITATIVE PHASE IMAGING METHOD BASED ON COLOR MULTIPLEXED ILLUMINATION 有权

    公开(公告)号：US20220366552A1

    公开(公告)日：2022-11-17

    申请号：US17766088

    申请日：2020-08-18

    Applicant: NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY

    Inventor： Qian CHEN ,  Yao FAN ,  Chao ZUO ,  Jiasong SUN ,  Xiangpeng PAN ,  Shijie FENG ,  Yuzhen ZHANG ,  Guohua GU ,  Jiaji LI ,  Jialin ZHANG

    IPC: G06T5/50 ,  G02B21/36

    Abstract: A single-shot differential phase contrast quantitative phase imaging method based on color multiplexing illumination. A color multiplexing illumination solution is used to realize single-shot differential phase contrast quantitative phase imaging. In the single-shot color multiplexing illumination solution, three illumination wavelengths of red, green, and blue are used to simultaneously illuminate a sample, and the information of the sample in multiple directions is converted into intensity information on different channels of a color image. By performing channel separation on this color image, the information about the sample at different spatial frequencies can be obtained. Such a color multiplexing illumination solution requires only one acquired image, thus enhancing the transfer response of the phase transfer function of single-shot differential phase contrast imaging in the entire frequency range, and achieving real-time dynamic quantitative phase imaging with a high contrast, a high resolution, and a high stability. In addition, an alternate illumination strategy is provided, so that a completely isotropic imaging resolution at the limit acquisition speed of the camera can be achieved.

    Quantitative phase imaging method based on differential phase contrast with optimal lighting pattern design
    65.
    发明授权
    Quantitative phase imaging method based on differential phase contrast with optimal lighting pattern design 有权

    公开(公告)号：US11487096B2

    公开(公告)日：2022-11-01

    申请号：US17294322

    申请日：2019-07-05

    Applicant: Nanjing University of Science and Technology

    Inventor： Qian Chen ,  Chao Zuo ,  Yao Fan ,  Jiasong Sun ,  Jiaji Li ,  Shijie Feng ,  Yuzhen Zhang

    IPC: G02B21/14 ,  G02B21/36 ,  H04N5/232 ,  H04N5/235 ,  G06T7/00

    Abstract: The patent discloses a differential phase contrast (DPC) quantitative phase microscopy method based on the optimal illumination pattern design. Firstly, the optimal illumination pattern corresponding to the isotropic phase transfer function of DPC quantitative phase imaging is derived, which is determined as a semi-annular illumination pattern with the illumination numerical aperture NAill equal to the numerical aperture NAobj of the objective lens. The illumination intensity distribution varies with the cosine of the illumination angle, and it can be expressed as S(θ)=cos(θ). This patent effectively compensates for the frequency loss of phase transfer, not only the high-frequency responses of PTF are enhanced, but also the transfer responses of low-frequency phase information is significantly improved. As a result, the optimal illumination scheme ensures the correctness and achieves high resolution phase reconstruction, while the number of illuminations is reduced to a minimum of two, which greatly increases the imaging speed, allowing for real-time dynamic, high-correctness, high-resolution phase imaging results.

    A DEEP LEARNING-BASED TEMPORAL PHASE UNWRAPPING METHOD FOR FRINGE PROJECTION PROFILOMETRY
    67.
    发明申请
    A DEEP LEARNING-BASED TEMPORAL PHASE UNWRAPPING METHOD FOR FRINGE PROJECTION PROFILOMETRY 有权

    公开(公告)号：US20210356258A1

    公开(公告)日：2021-11-18

    申请号：US17280464

    申请日：2019-07-05

    Applicant: Nanjing University of Science and Technology

    Inventor： Qian CHEN ,  Chao ZUO ,  Shijie FENG ,  Yuzhen ZHANG ,  Guohua GU

    IPC: G01B11/25 ,  G06N3/04 ,  G06N3/08

    Abstract: The invention discloses a deep learning-based temporal phase unwrapping method for fringe projection profilometry. First, four sets of three-step phase-shifting fringe patterns with different frequencies (including 1, 8, 32, and 64) are projected to the tested objects. The three-step phase-shifting fringe images acquired by the camera are processed to obtain the wrapped phase map using a three-step phase-shifting algorithm. Then, a multi-frequency temporal phase unwrapping (MF-TPU) algorithm is used to unwrap the wrapped phase map to obtain a fringe order map of the high-frequency phase with 64 periods. A residual convolutional neural network is built, and its input data are set to be the wrapped phase maps with frequencies of 1 and 64, and the output data are set to be the fringe order map of the high-frequency phase with 64 periods. Finally, the training dataset and the validation dataset are built to train and validate the network. The network makes predictions on the test dataset to output the fringe order map of the high-frequency phase with 64 periods. The invention exploits a deep learning method to unwrap a wrapped phase map with a frequency of 64 using a wrapped phase map with a frequency of 1 and obtain an absolute phase map with fewer phase errors and higher accuracy.

    METHODS FOR LIGNOCELLULOSIC BIOMASS PRE-TREATMENT: DENSIFICATION OF BIOMASS WITH ALKALINE OR ACIDIC CHEMICAL(S) THEREOF AND FOR BIOTRANSFORMATION THEREOF
    68.
    发明申请
    METHODS FOR LIGNOCELLULOSIC BIOMASS PRE-TREATMENT: DENSIFICATION OF BIOMASS WITH ALKALINE OR ACIDIC CHEMICAL(S) THEREOF AND FOR BIOTRANSFORMATION THEREOF 有权

    公开(公告)号：US20210269837A1

    公开(公告)日：2021-09-02

    申请号：US17252168

    申请日：2019-07-17

    Applicant: NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY

    Inventor： Mingjie JIN ,  Xiangxue CHEN ,  Xinchuan YUAN

    IPC: C12P19/14

    Abstract: A biomass pretreatment method is provided to improve the bio-digestibility of lignocellulosic biomass. This pretreatment method densifies biomass with alkaline or acidic chemical(s) to obtain densified biomass containing chemicals. Pretreatment effects are realized during densification. The chemicals in densified biomass further react with biomass during biomass storage and transportation to improve the pretreatment effects. Further treatment (e.g. stream) can also be applied to the densified biomass to achieve better effects. As chemicals are mixed well with biomass during densification and the biomass density is greatly increased, further treatment is of high efficiency and high solid loading. This pretreatment method is simple and the densified biomass with chemicals is resistant to microbial contamination/degradation and thus facilitates storage and transportation.

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