Dry reforming of methane over Ni/SBA-15 catalysts prepared by homogeneous precipitation method

Qiulin Zhang,Jing Wang,Ping Ning,Tengfei Zhang,Mingzhi Wang,Kaixian Long,Jianhong Huang 한국화학공학회 2017 Korean Journal of Chemical Engineering Vol.34 No.11

Ni/SBA-15 catalyst was prepared by homogeneous precipitation method (Ni-HP) and used for dry reforming of methane (DRM). The related characterization results indicated that the Ni particles were highly dispersed with a size range of 2-5 nm. Compared with Ni/SBA-15 catalyst prepared by impregnation (Ni-IM), the reduction temperature of Ni-HP obtained from H2-TPR was greatly improved, suggesting the stronger metal-support interaction. After reacting at 700 oC for 100 h, the CH4 conversion of DRM over Ni-HP catalyst slightly decreased from 74.5% to 73.8%. While, for the Ni-IM catalyst, the CH4 conversion dropped from 61.7% to 37.3%. Furthermore, the average particle size of Ni-HP was 3.7 nm and 4.7 nm before and after the long-time stability test, respectively, ascribed to the good antisintering property. Although a certain amount of coke was produced, mainly with disorder filamentous carbon of basegrowth, the Ni/SBA-15 prepared by homogeneous precipitation exhibited excellent catalytic activity and stability.

Carbon dioxide reforming of methane over MgO promoted Ni/CNT catalyst

Dehua Zhang,Guangcheng Wei,Yiru Wang,Jing Wang,Ping Ning,Qiulin Zhang,Mingzhi Wang,Tengfei Zhang,Kaixian Long 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.10

Carbon dioxide reforming of methane to syngas was investigated over a series of MgO promoted Ni/CNT catalysts. MgO played a critical role in improving the catalytic performance of Ni/CNT. The results showed that the addition of MgO strengthened the interaction of Ni and interior surface of CNT. Highly dispersed nickel particles with small size (less than 4.5nm) were also observed in MgO modified CNT. Otherwise, the NiO nanoparticles were facilely reduced over the catalyst prepared with a narrow size of CNT, as shown in H2-TPR. The reaction tests demonstrated that the Ni-based catalyst with an addition of MgO and narrow size of CNT exhibited better catalytic activity. Furthermore, the lifetime of Ni-based catalyst was prolonged effectively after adding MgO, attributed to the stabilization and dispersion of Ni particles and the effective restraint on the gasification of CNT.

Determination of the number of ²³⁵U target nuclei in the irregular target using a fission time projection chamber

Jiajun Zhang,Jun Xiao,Junjie Sun,Mingzhi Zhang,Taiping Peng,Pu Zheng Korean Nuclear Society 2024 Nuclear Engineering and Technology Vol.56 No.2

Based on multiple measurements of ionization loss, the Time Projection Chamber (TPC) combines strong tracking ability with particle identification ability in a large momentum range, which is an important advantage of TPC detection technology over traditional ionization measurement technology. According to these two characteristics of TPC, applying it to the measurement of fission cross-section can greatly improve the measurement accuracy. During the measurement of the fission cross-section, the number of target nuclei is required to be accurately measured. So this paper introduces a method for measuring the number of ²³⁵U target nuclei using a fission TPC system. The measurement result agrees with the reference value, and relative error is around 1 %.

Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on 18F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma

Xiaoyan Feng,Xin Wen,Ling Li,Zhenchang Sun,Xin Li,Lei Zhang,Jingjing Wu,Xiaorui Fu,Xinhua Wang,Hui Yu,Xinran Ma,Xudong Zhang,Xinli Xie,Xingmin Han,Mingzhi Zhang 대한암학회 2021 Cancer Research and Treatment Vol.53 No.3

Purpose There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on 18F-fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) in T-LBL.Materials and Methods Thirty-seven treatment naïve T-LBL patients with PET-CT scans were enrolled. TMTV was obtained using the 41% maximum standardized uptake value (SUVmax) threshold method, and TLG was measured as metabolic tumor volume multiplied by the mean SUV. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier curves and compared by the log-rank test.Results The optimal cutoff values for SUVmax, TMTV, and TLG were 12.7, 302 cm3, and 890, respectively. A high SUVmax, TMTV, and TLG indicated a shorten PFS and OS. On multivariable analysis, TMTV ≥ 302 cm3, and central nervous system (CNS) involvement predicted inferior PFS, while high SUVmax, TLG and CNS involvement were associated with worse OS. Subsequently, we generated a risk model comprising high SUVmax, TMTV or TLG and CNS involvement, which stratified the population into three risk groups, which had significantly different median PFS of not reached, 14 months, and 7 months for low-risk group, mediate-risk group, and high-risk group, respectively (p < 0.001). Median OS were not reached, 27 months, and 13 months, respectively (p < 0.001).Conclusion Baseline SUVmax, TMTV, and TLG measured on PET-CT are strong predictors of worse outcome in T-LBL. A risk model integrating these three parameters with CNS involvement identifies patients at high risk of disease progression.

Modeling of a paper-making wastewater treatment process using a fuzzy neural network

Mingzhi Huang,유창규,Jinquan Wan,Yan Wang,Yongwen Ma,Huiping Zhang,류홍빈,Zhanzhan Hu 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.5

An intelligent system that includes a predictive model and a control was developed to predict and control the performance of a wastewater treatment plant. The predictive model was based on fuzzy C-means clustering, fuzzy inference and neural networks. Fuzzy C-means clustering was used to identify model’s architecture, extract and optimize fuzzy rule. When predicting, MAPE was 4.7582% and R was 0.8535. The simulative results indicate that the learning ability and generalization of the model was good, and it can achieve a good predication of effluent COD. The control model was based on a fuzzy neural network model, taking into account the difference between the predicted value of COD and the setpoint. When simulating, R was 0.9164, MAPE was 5.273%, and RMSE was 0.0808, which showed that the FNN control model can effectively change the additive dosages. The control of a paper-making wastewater treatment process in the laboratory using the developed predictive control model and MCGS (monitor and control generated system) software shows the dosage was computed accurately to make the effluent COD remained at the setpoint,when the influent COD value or inflow flowrate was changed. The results indicate that reasonable forecasting and control performances were achieved through the developed system; the maximum error was only 3.67%, and the average relative error was 2%.

A GA-Based Neural Fuzzy System for Modeling a Paper Mill Wastewater Treatment Process

Huang, Mingzhi,Wan, Jinquan,Ma, Yongwen,Zhang, Huiping,Wang, Yan,Wei, Chaohai,Liu, Hongbin,Yoo, ChangKyoo American Chemical Society 2011 INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH - Vol.50 No.23

<P>A genetic algorithm-based neural fuzzy system (GA-NFS) was presented for studying the coagulation process of wastewater treatment in a paper mill. In order to adapt the system to a variety of operating conditions and acquire a more flexible learning ability, the GA-NFS was employed to model the nonlinear relationships between the effluent concentration of pollutants and the chemical dosages, and a hybrid learning algorithm divided into two stages was proposed for parameters learning. During the first learning stage, a genetic algorithm was used to optimize the structure of GA-NFS and the membership function of each fuzzy term due to its capability of parallel and global search. On the basis of an optimized training stage, the back-propagation algorithm (BP algorithm) was chosen to update the parameters of GA-NFS to improve the system precision. The GA-NFS proves to be very effective in modeling coagulation perform and performs better than adaptive-network-based fuzzy inference system (ANFIS). RMSE, MAPE, and <I>R</I> between the predicted and observed values for GA-NFS were only 0.01099, 2.3337, and 0.9375, respectively.</P>

FBXL20-mediated Vps34 ubiquitination as a p53 controlled checkpoint in regulating autophagy and receptor degradation

Xiao, Juan,Zhang, Tao,Xu, Daichao,Wang, Huibing,Cai, Yu,Jin, Taijie,Liu, Min,Jin, Mingzhi,Wu, Kejia,Yuan, Junying Cold Spring Harbor Laboratory Press 2015 Genes & development Vol.29 No.2

<P>Vps34, the catalytic subunit in the class III phosphatidylinositol 3 kinase complexes, mediates the production of PtdIns3P, a key intracellular lipid involved in regulating autophagy and receptor degradation. Xiao et al. show that DNA damage-activated mitotic arrest and CDK activation lead to the phosphorylation of Vps34. This provides a signal to promote Vps34 ubiquitination and proteasomal degradation mediated by FBXL20, leading to inhibition of autophagy and receptor endocytosis. Importantly, they also find that expression of FBXL20 is regulated by p53-dependent transcription.</P><P>Vacuolar protein-sorting 34 (Vps34), the catalytic subunit in the class III PtdIns3 (phosphatidylinositol 3) kinase complexes, mediates the production of PtdIns3P, a key intracellular lipid involved in regulating autophagy and receptor degradation. However, the signal transduction pathways by which extracellular signals regulate Vps34 complexes and the downstream cellular mechanisms are not well understood. Here we show that DNA damage-activated mitotic arrest and CDK activation lead to the phosphorylation of Vps34, which provides a signal to promote its ubiquitination and proteasomal degradation mediated by FBXL20 (an F-box protein) and the associated Skp1 (S-phase kinase-associated protein-1)–Cullin1 complex, leading to inhibition of autophagy and receptor endocytosis. Furthermore, we show that the expression of FBXL20 is regulated by p53-dependent transcription. Our study provides a molecular pathway by which DNA damage regulates Vps34 complexes and its downstream mechanisms, including autophagy and receptor endocytosis, through SCF (Skp1–Cul1–F-box)-mediated ubiquitination and degradation. Since the expression of FBXL20 is regulated by p53-dependent transcription, the control of Vps34 ubiquitination and proteasomal degradation by FBXL20 and the associated SCF complex expression provides a novel checkpoint for p53 to regulate autophagy and receptor degradation in DNA damage response.</P>