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12. Preparation and adsorption kinetics and thermodynamics of sodium humate‐modified diatomite.

Author

Chen, Hongye, Gao, Ruqin, and Ma, Qiuhui

Subjects
*ADSORPTION kinetics, *DIATOMACEOUS earth, *THERMODYNAMICS, *FIELD emission electron microscopy, *TRANSMISSION electron microscopes
Abstract

Diatomaceous earth has been used as a nonorganic carrier to prepare a sodium humate modified diatomaceous space using the sol‐gel method. X‐ray diffraction, field emission scanning electron microscopy, transmission electron microscope, the Brunauer–Emmett–Teller (BET) method, and other methods were used to characterize its physio‐chemical properties. The effects of sodium humate/diatomite on the pH of tetracycline in water, the dosage of adsorbent, and pollutant temperature on the adsorption effect were studied. The results show that after alkali modification, the porous structure of diatomite remains undamaged, and the specific surface area of the modified sample is increased to 12.712 m2/g, and the average pore diameter is reduced to 146.19 nm. Adding 20‐mg sodium humate/diatomite into 100‐mL tetracycline wastewater with an initial concentration of 20 mg/L, and pH of 5 at a temperature of 55°C, the adsorption capacity reaches 75.1 mg/L, and the removal rate reaches 78.3%. The quasi‐second‐order kinetic model was fitted by regression and found to have R2 > 0.99, indicating that the adsorption process was one of surface adsorption. It is a process that involves initially rapid adsorption and then slowly reaching equilibrium. As an adsorption thermodynamics model, the Temkin, Redlich‐Peterson and Koble‐Corrigan models can explain humic acid sodium/diatomite behavior in the adsorption of tetracycline in water (each with R2 ≥ 0.99), and the effects of surface behavior in multilayer adsorption and electrostatic attraction on uneven heterogeneous adsorption. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Stimulates Short-Chain Dehydrogenase/Reductase Proteins to Alleviate Heart Failure Independent of Mitochondrial Protein Deacetylation

Author

Walker, Matthew A., primary, Chen, Hongye, additional, Yadav, Aprajita, additional, Ritterhoff, Julia, additional, Villet, Outi, additional, McMillen, Tim, additional, Wang, Yuliang, additional, Purcell, Hayley, additional, Djukovic, Danijel, additional, Raftery, Daniel, additional, Isoherranen, Nina, additional, and Tian, Rong, additional

Published
2023
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17. Highly Nonlinear Memory Selectors with Ultrathin MoS2/WSe2/MoS2 Heterojunction.

Author

Chen, Hongye, Wan, Tianqing, Zhou, Yue, Yan, Jianmin, Chen, Changsheng, Xu, Zhihang, Zhang, Songge, Zhu, Ye, Yu, Hongyu, and Chai, Yang

Subjects
*NONVOLATILE random-access memory, *SCHOTTKY barrier, *HETEROJUNCTIONS, *BORON nitride, *DATA warehousing, *STRAY currents
Abstract

Resistive random access memory (RRAM) crossbar arrays require the highly nonlinear selector with high current density to address a specific memory cell and suppress leakage current through the unselected cell. 3D monolithic integration of RRAM array requires selector devices with a small footprint and low‐temperature processing for ultrahigh‐density data storage. Here, an ultrathin two‐terminal n‐p‐n selector with 2D transition metal dichalcogenides (TMDs) is designed by a low‐temperature transfer method. The van der Waals contact between transferred Au electrodes and TMDs reduces the Fermi level pinning and retains the intrinsic transport behavior of TMDs. The selector with a single type of TMD exhibits a trade‐off between current density and nonlinearity depending on the barrier height. By tuning the Schottky barrier height and controlling the thickness of p‐type WSe2 in MoS2/WSe2/MoS2 n‐p‐n selector for a punch‐through transport, the selector shows high nonlinearity (≈ 230) and high current density (2 × 103 A cm−2) simultaneously. The n‐p‐n selectors are further integrated with a bipolar hexagonal boron nitride memory and calculate the maximum crossbar size of the 2D material‐based one‐selector one‐resistor according to a 10% read margin, which offers the possible realization of future 3D monolithic integration. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Interpretable Spatial-Temporal Attention Graph Convolution Network for Service Part Hierarchical Demand Forecast

Author

Ouyang, Wenli, Zhang, Yahong, Zhu, Mingda, Zhang, Xiuling, Chen, Hongye, Ren, Yinghao, Fan, Wei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tang, Jie, editor, Kan, Min-Yen, editor, Zhao, Dongyan, editor, Li, Sujian, editor, and Zan, Hongying, editor

Published
2019
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22. Contributors

Author

Chen, Haotian, primary, Chen, Hongye, additional, Chou, Ho-Hsiu, additional, Ding, Yichun, additional, Gao, Naiwei, additional, He, Yonglin, additional, Huang, Wei, additional, Lee, Wen-Ya, additional, Li, Wenjin, additional, Li, Yue, additional, Li, Zhangpeng, additional, Lv, Yuhuan, additional, Maheshwari, Vivek, additional, Min, Lizhen, additional, Onyilagha, Obiora, additional, Pan, Kai, additional, Peng, Dengfeng, additional, Qu, Sicen, additional, Saraf, Rohit, additional, Su, Bin, additional, Wang, Jinqing, additional, Wang, Mingti, additional, Wang, Xuewen, additional, Wang, Yapei, additional, Wu, Xianzhang, additional, Yang, Shengrong, additional, Zhang, Haixia, additional, Zhang, Xuan, additional, Zheng, Lu, additional, Zhou, Ye, additional, and Zhu, Zhengtao, additional

Published
2021
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27. Tunable J-type aggregation of silicon phthalocyanines in a surface-anchored metal–organic framework thin film.

Author

Chen, Hongye, Martín-Gomis, Luis, Xu, Zhiyun, Fischer, Jan C, Howard, Ian A, Herrero, David, Sobrino-Bastán, Víctor, Sastre-Santos, Ángela, Haldar, Ritesh, and Wöll, Christof

Abstract

Organic chromophores and semiconductors, like anthracene, pentacene, perylene, and porphyrin, are prone to aggregation, and their packing in the solid state is often hard to predict and difficult to control. As the condensed phase structures of these chromophores and semiconductors are of crucial importance for their optoelectronic functionality, strategies to control their assembly and provide new structural motifs are important. One such approach uses metal–organic frameworks (MOFs); the organic chromophore is converted into a linker and connected by metal ions or nodes. The spatial arrangement of the organic linkers can be well-defined in a MOF, and hence optoelectronic functions can be adjusted accordingly. We have used such a strategy to assemble a phthalocyanine chromophore and illustrated that the electronic inter-phthalocyanine coupling can be rationally tuned by introducing bulky side grounds to increase steric hindrance. We have designed new phthalocyanine linkers and using a layer-by-layer liquid-phase epitaxy strategy thin films of phthalocyanine-based MOFs have been fabricated and their photophysical properties explored. It was found that increasing the steric hindrance around the phthalocyanine reduced the effect of J-aggregation in the thin film structures. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Alterations in Oral Microbiota of Differentiated Thyroid Carcinoma Patients With Xerostomia After Radioiodine Therapy

Author

Lin, Baiqiang, primary, Zhao, Fuya, additional, Liu, Yang, additional, Sun, Jiayu, additional, Feng, Jing, additional, Zhao, Lei, additional, Wang, Haoran, additional, Chen, Hongye, additional, Yan, Wei, additional, Guo, Xiao, additional, Shi, Shang, additional, Li, Zhiyong, additional, Wang, Shuang, additional, Lu, Yu, additional, Zheng, Jianjun, additional, and Wei, Yunwei, additional

Published
2022
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36. Randomized Clinical Trial: Probiotics Alleviated Oral-Gut Microbiota Dysbiosis and Thyroid Hormone Withdrawal-Related Complications in Thyroid Cancer Patients Before Radioiodine Therapy Following Thyroidectomy

Author

Lin, Baiqiang, primary, Zhao, Fuya, additional, Liu, Yang, additional, Wu, Xin, additional, Feng, Jing, additional, Jin, Xiangren, additional, Yan, Wei, additional, Guo, Xiao, additional, Shi, Shang, additional, Li, Zhiyong, additional, Liu, Lujia, additional, Chen, Hongye, additional, Wang, Haoran, additional, Wang, Shuang, additional, Lu, Yu, additional, and Wei, Yunwei, additional

Published
2022
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45. Interplay of structural dynamics and electronic effects in an engineered assembly of pentacene in a metal–organic framework

Author

Haldar, Ritesh, primary, Kozlowska, Mariana, additional, Ganschow, Michael, additional, Ghosh, Samrat, additional, Jakoby, Marius, additional, Chen, Hongye, additional, Ghalami, Farhad, additional, Xie, Weiwei, additional, Heidrich, Shahriar, additional, Tsutsui, Yusuke, additional, Freudenberg, Jan, additional, Seki, Shu, additional, Howard, Ian A., additional, Richards, Bryce S., additional, Bunz, Uwe H. F., additional, Elstner, Marcus, additional, Wenzel, Wolfgang, additional, and Wöll, Christof, additional

Published
2021
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47. Tuning Optical Properties by Controlled Aggregation: Electroluminescence Assisted by Thermally‐Activated Delayed Fluorescence from Thin Films of Crystalline Chromophores

Author

Haldar, Ritesh, primary, Jakoby, Marius, additional, Kozlowska, Mariana, additional, Rahman Khan, Motiur, additional, Chen, Hongye, additional, Pramudya, Yohanes, additional, Richards, Bryce S., additional, Heinke, Lars, additional, Wenzel, Wolfgang, additional, Odobel, Fabrice, additional, Diring, Stéphane, additional, Howard, Ian A., additional, Lemmer, Uli, additional, and Wöll, Christof, additional

Published
2020
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50. Interpretable Spatial-Temporal Attention Graph Convolution Network for Service Part Hierarchical Demand Forecast

Author

Zhu Mingda, Zhang Yahong, Zhang Xiuling, Fan Wei, Ouyang Wenli, Chen Hongye, and Ren Yinghao

Subjects
Supply chain management, Computer science, business.industry, Deep learning, 020206 networking & telecommunications, 02 engineering and technology, Demand forecasting, computer.software_genre, 01 natural sciences, Convolutional neural network, 010104 statistics & probability, Recurrent neural network, 0202 electrical engineering, electronic engineering, information engineering, Graph (abstract data type), Supply chain network, Data mining, Artificial intelligence, 0101 mathematics, business, computer, Natural language processing, Interpretability
Abstract

Accurate service part demand forecast plays a key role in service supply chain management. It enables better decision making in the planning of service part procurement and distribution. To achieve high responsiveness, the service supply chain network exhibits a hierarchical structure: forward stocking locations (FSL) close to the end customer, distribution centers (DC) in the middle and center hub (CH) at the top. Hierarchical forecasts require not only good prediction accuracy at each level of the service supply chain network, but also the consistency between different levels. The accuracy and consistency of hierarchical forecasts are important to be interpretable to the decision-makers (DM). Moreover, service part demand data is the spatial-temporal time series that the observations made at neighboring regions and adjacent timestamps are not independent but dynamically correlated with each other. Recent advances in deep learning enable promising results in modeling the complex spatial-temporal relationship. Researchers use convolutional neural networks (CNN) to model spatial correlations and recurrent neural networks (RNN) to model temporal correlations. However, these deep learning models are non-transparent to the DMs who broadly require justifications in the decision-making processes. Here an interpretable solution is in the urgent demand. In this paper, we present an interpretable general framework STAH (Spatial-Temporal Attention Graph Convolution network for Hierarchical demand forecast). We evaluate our approach on Lenovo Group Ltd.’s service part demand data in India. Experimental results demonstrate the efficacy of our approach, showing superior accuracy while increasing model interpretability.

Published
2019

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