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Analysis and optimization of energy flow in the full chain of carbon dioxide capture and oil recovery

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碳中和(英文)

碳中和(英文) 2022年第1期1卷 171-183页

作者： fu-zhen zhang Rui-Na Xu Ying-fu He Xin Fang Pei-Xue Jiang Key Laboratory for Thermal Science and Power Engineering of Ministry of Education BeijingChina Key Laboratory of CO_(2) Utilization and Reduction Technology BeijingChina Department of Energy and Power Engineering Tsinghua UniversityBeijing 100084China SINOPEC Exploration&Production Research Institute BeijingChina

CO_(2) capture is a process with a high energy consumption,and its large-scale implementation should be based on comprehensive analysis of its impact on the energy,economy,and environment.The process of injecting CO_(2) into existing oil fields is a well-known enhanced oil recovery(CO_(2)-EOR)technique.Using CO_(2) as a working fluid to recover oil can compensate for the energy consumption of the capture and transport processes,increasing the feasibility of CO_(2) capture while achieving carbon sequestration.In this study,a full-chain CO_(2) capture,utilization,and storage(CCUS)system based on the post-combustion capture method is deconstructed and coupled.A full-chain energy consumption calculation software is developed,and optimization analysis of the energy consumption system is conducted.The energy budget of the oil displacement utilization is deconstructed,and the advantages of the water alternating gas(WAG)method are clarified from an energy budget point of view.The analysis reveals that the benefits of CO_(2)-EOR are far greater than the energy consumption of other CCUS processes,and CCUS-EOR is a CO_(2) utilization method with positive energy benefits.Based on the simulation of the effects of N_(2) and CH_(4) on the recovery factor,a multi-well combined injection-production method is proposed,and the reasons for increasing profit are analyzed.

关键词： Energy budget full-chain Carbon dioxide capture utilization and storage(CCUS) CO_(2)enhanced oil recovery(CO_(2)-EOR)

Accurate atomic scanning transmission electron microscopy analysis enabled by deep learning

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Nano Research 2024年第4期17卷 2971-2980页

作者： Tianshu Chu Lei Zhou Bowei zhang fu-zhen Xuan Shanghai Key Laboratory of Intelligent Sensing and Detection Technology East China University of Science and TechnologyShanghai 200237China School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Key Laboratory of Pressure Systems and Safety of Ministry of Education East China University of Science and TechnologyShanghai 200237China

Currently,the machine learning(ML)-based scanning transmission electron microscopy(STEM)analysis is limited in the simulative stage,its application in experimental STEM is needed but challenging.Herein,we built up a universal model to analyze the vacancy defects and single atoms accurately and rapidly in experimental STEM images using a full convolution network.In our model,the unavoidable interference factors of noise,aberration,and carbon contamination were fully considered during the training,which were difficult to be considered in the past.Even toward the simultaneous identification of various vacancy types and low-contrast single atoms in the low-quality STEM images,our model showed rapid process speed(45 images per second)and high accuracy(>95%).This work represents an improvement in experimental STEM image analysis by ML.

关键词： deep learning low-dimensional materials atomic defects single atoms

Data-driven rational design of single-atom materials for hydrogen evolution and sensing

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Nano Research 2024年第4期17卷 3352-3358页

作者： Lei Zhou Pengfei Tian Bowei zhang fu-zhen Xuan Shanghai Key Laboratory of Intelligent Sensing and Detection Technology East China University of Science and TechnologyShanghai 200237China School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Key Laboratory of Pressure Systems and Safety of Ministry of Education East China University of Science and TechnologyShanghai 200237China

Herein we proposed a data-driven high-throughput principle to screen high-performance single-atom materials for hydrogen evolution reaction(HER)and hydrogen sensing by combing the theoretical computations and a topology-based multi-scale convolution kernel machine learning algorithm.After the rational training by 25 groups of data and prediction of all 168 groups of single-atom materials for HER and sensing,respectively,a high prediction accuracy(>0.931 R^(2) score)was achieved by our model.Results show that the promising HER catalysts include Pt atoms in C_(4) and Sc atoms in C_(1)N_(3) coordination environment.Moreover,Y atoms in C_(4) coordination environment and Cd atoms in C_(2)N_(2)-ortho coordination environment were predicted with great potential as hydrogen sensing materials.This method provides a way to accelerate the discovery of innovative materials by avoiding the time-consuming empirical principles in experiments.

关键词： machine learning single-atom materials sensing hydrogen evolution

Carrimycin in the treatment of acute promyelocytic leukemia combined with pulmonary tuberculosis: A case report

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World Journal of Clinical Cases 2024年第3期12卷 623-629页

作者： fu-Yu Yang Lei Shao Jie Su zhen-Meng zhang Department of Infectious Diseases The Affiliated Central Hospital of Shandong First Medical UniversityJinan 250013Shandong ProvinceChina

BACKGROUND Pulmonary tuberculosis(PTB)is prevalent in immunocompromised populations,including patients with hematologic malignancies,human immunodeficiency virus infections,and chronic diseases.Effective treatment for acute promyelocytic leukemia(APL)combined with PTB is lacking.These patients show an extremely poor prognosis.Therefore,studies should establish efficient treatment options to improve patient survival and prognosis.CASE SUMMARY A 60-year-old male with pain in the right side of his chest and a fever for 4 d visited the outpatient department of our hospital.Peripheral blood smear revealed 54%blasts.Following bone marrow examinations,variant APL with TNRC18-RARA fusion gene was diagnosed.Chest computed tomography scan showed bilateral pneumonitis with bilateral pleural effusions,partial atelectasis in the lower lobes of both lungs,and the bronchoalveolar lavage fluid gene X-Pert test was positive,indicative of PTB.Carrimycin,ethambutol(EMB),and isoniazid(INH)were administered since he could not receive chemotherapy as the WBC count decreased continuously.After one week of treatment with carrimycin,the patient recovered from fever and received chemotherapy.Chemotherapy was very effective and his white blood cells counts got back to normal.After being given five months with rifampin,EMB and INH and chemotherapy,the patient showed complete remission from pneumonia and APL.CONCLUSION We report a case of PTB treated successfully with carrimycin with APL that requires chemotherapy.

关键词： Carrimycin Hematologic disease Acute myeloid leukemia Acute promyelocytic leukemia Pulmonary tuberculosis Case report

Effect of Surface Charge on Flashover for Oil-Pressboard Insulation under AC-DC Combined Electric Field

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Journal of Energy and Power Engineering 2013年第9期7卷 1803-1808页

作者： Yi-long Chen BO Qi Chao-chao Xi Yi-fan Liao fu-zhen zhang Ye Zhu Beijing Key Laboratory of High Voltage and Electro Magnetic Compatibility North China Electric Power University Beo'ing102206 China State key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric PowerUniversity Beij'ing 102206 China Electric Power Research Institute China Southern Power Grid Guangzhou 510080 China

For converter transformer, AC-DC combined electric field can trigger space charge accumulation on oil-impregnated pressboard interface. The accumulation of space charge on oil-pressboard interface can result in electric field distortion, trend to trigger surface discharge of barriers. This paper studied the influence of surface charge on flashover voltage of oil-impregnated pressboard under AC-DC combined electric field. The study finds that the flashover voltage of oil-pressboard interface under negative polarity DC superimposed AC electric field is higher than that of positive DC superimposed AC voltage to form composite electric field. It was found that homopolar surface charge has been accumulated on the interface of oil-pressboard with positive or negative DC voltage through measuring surface potential by the electrostatic capacitive probe. The surface charge produced electric field in the opposite direction, which weakening the synthetic electric field strength. What"s more, under the same conditions, the negative surface charge density oil-pressboard is much larger than the positive.

关键词：表面电荷密度复合电场绝缘纸板闪络电压交直流空间电荷交流电场直流叠加

LATS1 Promotes B-ALL Tumorigenesis by Regulating YAP1 Phosphorylation and Subcellular Localization

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Current Medical Science 2024年第1期44卷 81-92页

作者： Feng zhang Mohammed Awal Issah Hai-ying fu Hua-rong ZHOU Ting-bo LIU Jian-zhen SHEN fujian Provincial Key Laboratory on Hematology Fujian Medical Center of HematologyFujian Institute of HematologyClinical Research Center for Hematological Malignancies of Fujian ProvinceFujian Medical University Union HospitalFuzhou 350001China Tamale Technical University Faculty of Allied Health and Pharmaceutical SciencesDepartment of Medical Laboratory TechnologyTamale NS-011-2000Ghana Department of Hematology The Third Affiliated People's Hospital of Fujian University of Traditional Chinese MedicineThe Third People's Hospital of Fujian ProvinceFuzhou 350122China

Objective YAP1 plays a dual role as an oncogene and tumor suppressor gene in several tumors;differentiating between these roles may depend on the YAP1 phosphorylation pattern.The specific function of YAP1 in B cell acute lymphoblastic leukemia(B-ALL),however,is currently unclear.Thus,in the present study,the role of YAP1 in B-ALL was investigated using relevant cell lines and patient datasets.Methods The effects of shRNA-mediated knockdown on YAP1 and LATS1 levels in the NALM6 and MOLT-4 cell lines were examined using Western blotting,quantitative real-time polymerase chain reaction,flow cytometry,immunostaining,and nude mouse subcutaneous tumorigenesis experiments.Gene expression levels of Hippo pathway-related molecules before and after verteporfin(VP)treatment were compared using RNA-Seq to identify significant Hippo pathway-related genes in NALM6 cells.Results Patients with ALL showing high YAP1 expression and low YAP1-Ser127 phosphorylation levels had worse prognoses than those with low YAP1 protein expression and high YAP1-Ser127 phosphorylation levels.YAP1-Ser127 phosphorylation levels were lower in NALM6 cells than in MOLT-4 and control cells;YAP1 was distributed in the nuclei in NALM6 cells.Knockdown of YAP1 inhibited MOLT-4 and NALM6 cell proliferation and arrested the NALM6 cell cycle in the G0/G1 phase.Before and after VP treatment,the expression of the upstream gene LATS1 was upregulated;its overexpression promoted YAP1-Ser127 phosphorylation.further,YAP1 was distributed in the plasma.Conclusion LATS1 may downregulate YAP1-Ser127 phosphorylation and maintain B-ALL cell function;thus,VP,which targets this axis,may serve as a new therapeutic method for improving the outcomes for B-ALL patients.

关键词： acute lymphoblastic leukemia large tumor suppressor kinase 1 phosphorylation RNA-Seq Yesl-associated protein

Enhancing Green Ammonia Electrosynthesis Through Tuning Sn Vacancies in Sn‑Based MXene/ MAX Hybrids

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Nano-Micro Letters 2024年第5期16卷 154-168页

作者： Xinyu Dai zhen‑Yi Du Ying Sun Ping Chen Xiaoguang Duan Junjun zhang Hui Li Yang fu Baohua Jia Lei zhang Wenhui Fang Jieshan Qiu Tianyi Ma Key Laboratory for Green Synthesis and Preparative Chemistry of Advanced Materials of Liaoning Province College of ChemistryInstitute of Clean Energy ChemistryLiaoning UniversityShenyang 110036People’s Republic of China State Key Laboratory of Clean and Efficient Coal Utilization Taiyuan University of TechnologyTaiyuan 030024People’s Republic of China School of Chemistry and Chemical Engineering Anhui UniversityHefei 230601People’s Republic of China School of Chemical Engineering The University of AdelaideAdelaideSA 5005Australia State Key Laboratory of High‑Efficiency Utilization of Coal and Green Chemical Engineering College of Chemistry and Chemical EngineeringNingxia UniversityYinchuan 750021NingxiaPeople’s Republic of China School of Science RMIT UniversityMelbourneVIC 3000Australia Guangdong Provincial Key Laboratory of Advanced Energy Storage Materials School of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510640People’s Republic of China College of Chemical Engineering State Key Laboratory of Chemical Resource EngineeringBeijing University of Chemical TechnologyBeijing 100029People’s Republic of China

Renewable energy driven N_(2) electroreduction with air as nitrogen source holds great promise for realizing scalable green ammonia production.However,relevant out-lab research is still in its infancy.Herein,a novel Sn-based MXene/MAX hybrid with abundant Sn vacancies,Sn@Ti_(2)CTX/Ti_(2)SnC–V,was synthesized by controlled etching Sn@Ti_(2)SnC MAX phase and demonstrated as an efficient electrocatalyst for electrocatalytic N2 reduction.Due to the synergistic effect of MXene/MAX heterostructure,the existence of Sn vacancies and the highly dispersed Sn active sites,the obtained Sn@Ti2CTX/Ti_(2)SnC–V exhibits an optimal NH_(3) yield of 28.4μg h^(−1) mg_(cat)^(−1) with an excellent FE of 15.57% at−0.4 V versus reversible hydrogen electrode in 0.1 M Na_(2)SO_(4),as well as an ultra-long durability.Noticeably,this catalyst represents a satisfactory NH3 yield rate of 10.53μg h^(−1) mg^(−1) in the home-made simulation device,where commercial electrochemical photovoltaic cell was employed as power source,air and ultrapure water as feed stock.The as-proposed strategy represents great potential toward ammonia production in terms of financial cost according to the systematic technical economic analysis.This work is of significance for large-scale green ammonia production.

关键词： Green ammonia synthesis N2 electroreduction Renewable energy Sn MXene/MAX hybrid

维普期刊数据库

Nuclear charge radius predictions by kernel ridge regression with odd-even effects

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Nuclear Science and Techniques 2024年第2期35卷 94-102页

作者： Lu Tang zhen-Hua zhang Mathematics and Physics Department North China Electric Power UniversityBeijing 102206China Hebei Key Laboratory of Physics and Energy Technology North China Electric Power UniversityBaoding 071000China

The extended kernel ridge regression(EKRR)method with odd-even effects was adopted to improve the description of the nuclear charge radius using five commonly used nuclear models.These are:(i)the isospin-dependent A^(1∕3) formula,(ii)relativistic continuum Hartree-Bogoliubov(RCHB)theory,(iii)Hartree-Fock-Bogoliubov(HFB)model HFB25,(iv)the Weizsacker-Skyrme(WS)model WS*,and(v)HFB25*model.In the last two models,the charge radii were calculated using a five-parameter formula with the nuclear shell corrections and deformations obtained from the WS and HFB25 models,respectively.For each model,the resultant root-mean-square deviation for the 1014 nuclei with proton number Z≥8 can be significantly reduced to 0.009-0.013 fm after considering the modification with the EKRR method.The best among them was the RCHB model,with a root-mean-square deviation of 0.0092 fm.The extrapolation abilities of the KRR and EKRR methods for the neutron-rich region were examined,and it was found that after considering the odd-even effects,the extrapolation power was improved compared with that of the original KRR method.The strong odd-even staggering of nuclear charge radii of Ca and Cu isotopes and the abrupt kinks across the neutron N=126 and 82 shell closures were also calculated and could be reproduced quite well by calculations using the EKRR method.

关键词： Nuclear charge radius Machine learning Kernel ridge regression method

维普期刊数据库

Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of Electronics 2024年第1期33卷 303-312页

作者： Tao zhang Ying fu Jun zhang School of Computer Science and Technology Beijing Institute of Technology Advanced Reasearch Institute of Multidisciplinary Science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. Existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Image denoising Image demosaicing Joint processing Guided attention Paired real dataset