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| 1 | Lactobacillus casei protects intestinal mucosa from damage in chicks caused by Salmonella pullorum via regulating immunity and the Wnt signaling pathway显示文摘This study is to explore the mechanisms underlying the protective effects of Lactobacillus casei(L.casei)on the intestinal mucosal barrier of chicks infected with Salmonella pullorum(S.pullorum)through histological,immunological,and molecular biology methods.The results showed that L.casei significantly reduced the diarrhea rate,increased the daily weight gain,and maintained normal levels of IgA,IgM,and IgG in the serum of chicks infected with S.pullorum.Furthermore,we found that L.casei markedly improved the immunity of gut mucosa by regulating cytokine and chemokine receptor balance,elevating the number of intraepithelial lymphocytes. | Deng Ziteng Han Deping Wang Yuying Wang Qiuzhen Ma Yunfei | 2021 | 解剖学杂志2021，44，S01： | 0 |
| 2 | Toward batch synthesis of high-quality graphene by cold-wall chemical vapor deposition approach显示文摘Chemical vapor deposition(CVD)has emerged as a promising approach for the controlled growth of graphene films with appealing scalability,controllability,and uniformity.However,the synthesis of high-quality graphene films still suffers from low production capacity and high energy consumption in the conventional hot-wall CVD system.In contrast,owing to the different heating mode,cold-wall CVD(CW-CVD)system exhibits promising potential for the industrial-scale production,but the quality of as-received graphene remains inferior with limited domain size and high defect density.Herein,we demonstrated an efficient method for the batch synthesis of high-quality graphene films with millimeter-sized domains based on CW-CVD system.With reduced defect density and improved properties,the as-received graphene was proven to be promising candidate material for electronics and anti-corrosion application.This study provides a new insight into the quality improvement of graphene derived from CW-CVD system,and paves a new avenue for the industrial production of high-quality graphene films for potential commercial applications. | Kaicheng Jia Ziteng Ma Wendong Wang Yongliang Wen Huanxin Li Yeshu Zhu Jiawei Yang Yuqing Song Jiaxin Shao Xiaoting Liu Qi Lu Yixuan Zhao Jianbo Yin Luzhao Sun Hailin Peng Jincan Zhang Li Lin Zhongfan Liu | 2022 | Nano Research2022，15，11： | 0 |
| 3 | Porous-structure engineered spacer for high-throughput and rapidgrowth of high-quality graphene films显示文摘Chemical vapor deposition(CVD)in conjunction with batch-to-batch manufacturing process is considered as the most promising technical route for mass-production of high-quality graphene films.To improve the space utilization of the CVD chamber and increase the throughput per batch,stacking of the Cu foil substrates is efficient,but suffers from the problems of adjacent fusion and the poor mass-transfer.Here,we demonstrate an efficient strategy for high-throughput and rapid growth of high-quality graphene by alternate stacking of Cu foils and porous carbon fiber paper(CFP).Relying on the unhindered mass-transfer through the pores of CFPs,full-covered high-quality graphene films on compact-stacked Cu foils were achieved within 2 min.Computational fluid dynamics(CFD)simulation and isotope labeling technique were performed to explore the gas diffusion and graphene growth process in the confined space of the Cu-CFP stacks.This work provides a feasible method for industrial production of graphene films,which may also be used for batch production of other two-dimensional materials. | Ziteng Ma Heng Chen Xiaofeng Song Buhang Chen Qin Li Yanglizhi Li Haiyang Liu Kaicheng Jia Shenghong Huang Luzhao Sun Zhongfan Liu | 2022 | Nano Research2022，15，11： | 0 |
| 4 | Fast scanning growth of high-quality graphene films on Cu foils fueled by dimeric carbon precursor显示文摘Carbon source precursor is a critical factor governing chemical vapor deposition growth of graphene films.Methane(CH4),has been the most commonly used precursor in the last decade,but it presents challenges in terms of decomposition efficiency and growth rate.Here we thoroughly evaluated acetylene(C2H_(2)),a precursor that is probably for providing carbon dimer(C2)species,for fast growth of large-scale graphene films.We find that the graphene growth behaviors fueled by C2H_(2) exhibit unconventional localized growth behavior with significant advantages in terms of high growth rate,which mainly ascribe to the as-decomposed C2 species.Therefore,a C2-fueled scanning growth strategy is proposed,and the fast scanning growth rate of 40 cm/min was experimentally demonstrated.This growth strategy is compatible with the approach of unidirectional growth of single-crystal graphene films,and the as-grown graphene films are of high-quality.This work demonstrates a reliable and promising strategy for the rapid synthesis of high-quality graphene film and may pave the avenue to cost-effective mass production of graphene materials in the roll-to-roll system. | Heng Chen Xiucai Sun Xiaofeng Song Buhang Chen Ziteng Ma Wanjian Yin Luzhao Sun Zhongfan Liu | 2023 | Nano Research2023，16，10： | 0 |
| 5 | Machine learning on properties of multiscale multisource hydroxyapatite nanoparticles datasets with different morphologies and sizes显示文摘Machine learning models for exploring structure-property relation for hydroxyapatite nanoparticles(HANPs)are still lacking.A multiscale multisource dataset is presented,including both experimental data(TEM/SEM,XRD/crystallinity,ROS,anti-tumor effects,and zeta potential)and computation results(containing 41,976 data samples with up to 9768 atoms)of nanoparticles with different sizes and morphologies at density functional theory(DFT),semi-empirical DFTB,and force field,respectively.Three geometric descriptors are set for the explainable machine learning methods to predict surface energies and surface stress of HANPs with satisfactory performance.To avoid the pre-determination of features,we also developed a predictive deep learning model within the framework of graph convolution neural network with good generalizability.Energies with DFT accuracy are achievable for largesized nanoparticles from the learned correlations and scale functions for mapping different theoretical levels and particle sizes.The simulated XRD spectra and crystallinity values are in good agreement with experiments. | Ziteng Liu Yinghuan Shi Hongwei Chen Tiexin Qin Xuejie Zhou Jun Huo Hao Dong Xiao Yang Xiangdong Zhu Xuening Chen Li Zhang Mingli Yang Yang Gao Jing Ma | 2021 | npj Computational Materials2021，，1： | 0 |
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