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Geochemical and petrological studies of high sulfur coal and overburden from Makum coalfield (northeast India) towards understanding and mitigation of acid mine drainage

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International Journal of Coal science & technology 2024年第1期11卷 133-147页

作者： Angana Mahanta Debashis Sarmah Nilotpol Bhuyan Monikankana Saikia Sarat Phukan K.S.V.Subramanyam Ajit Singh Prasenjit Saikia Binoy K.Saikia Coal and Energy Division CSIR-North East Institute of Science and TechnologyJorhatAssam785006India Academy of Scientific&Innovative Research(Acsir) Ghaziabad201002India Department of Geological sciences Gauhati UniversityGuwahatiAssam781014India Geochemistry Division CSIR-National Geophysical Research InstituteUppal RoadHyderabad500007India

Opencast coal mining produces trash of soil and rock containing various minerals,that are usually dumped nearby the abandoned sites which causes severe environmental concern including the production of acid mine drainage(AMD)through oxidation pyrite *** current study entailed assessing the potential production of AMD from an opencast coal mining region in northeast part of *** order to have a comprehensive overview of the AMD problem in Makum coalfield,the physico-chemical,geochemical,and petrological characteristics of the coal and overburden(OB)samples collected from the Makum coalfield(northeast India)were thoroughly *** maceral compositions reveal that coal features all three groups of macerals(liptinite,vitrinite,and inertinite),with a high concentration of liptinite indicating the coal of perhydrous,thereby rendering it more ***(FeS_(2))oxidation kinetics were studied by conducting the aqueous leaching experiments of coal and(OB)samples to interpret the chemical weathering under controlled laboratory conditions of various temperature and time periods,and to replicate the actual mine site *** coupled plasma-optical emission spectroscopy(ICP-OES)was operated to detect the disposal of some precarious elements from coal and OB samples to the leachates during our controlled leaching *** Rare earth element(REE)enrichment in the samples shows the anthropogenic incorporation of the REE in the coal and *** experiments reveal the change in conductivity,acid producing tendency,total dissolved solid(TDS),total Iron(Fe)and dissolved Sulfate(SO_(4)^(2−))ions on progress of the leaching ***,the discharge of FeS_(2) via atmospheric oxidation in laboratory condition undergoes a significant growth with the rise of temperature of the reaction systems in the environment and follows pseudo first order kinetics.A bio-remediative strategies is also reported in this paper to mitigate AMD water by

关键词： Opencast mining Pyrite oxidation Coal geochemistry Coal petrology Rare earth elements AMD remediation

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： Training Visualization Inverse problems Green products Noise reduction Pipelines Signal processing

All laser direct writing process for temperature sensor based on graphene and silver

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Frontiers of Optoelectronics 2024年第1期17卷 45-55页

作者： Qi Li Ruijie Bai Lianbo Guo Yang Gao Shanghai Key Laboratory of Intelligent Sensing and Detection technology School of Mechanical and Power EngineeringEast China University of Science and TechnologyShanghai 200237China north Automatic Control technology institute Taiyuan 030006China Wuhan National Laboratory for Optoelectronics Huazhong University of Science&TechnologyWuhan 430074China

A highly sensitive temperature sensing array is prepared by all laser direct writing(LDW)method,using laser induced silver(LIS)as electrodes and laser induced graphene(LIG)as temperature sensing layer.A finite element analysis(FEA)photothermal model incorporating a phase transition mechanism is developed to investigate the relationship between laser parameters and LIG properties,providing guidance for laser processing parameters selection with laser power of 1–5 W and laser scanning speed(greater than 50 mm/s).The deviation of simulation and experimental data for widths and thickness of LIG are less than 5%and 9%,*** electrical properties and temperature responsiveness of LIG are also *** changing the laser process parameters,the thickness of the LIG ablation grooves can be in the range of 30–120μm and the resistivity of LIG can be regulated within the range of 0.031–67.2Ω・*** percentage temperature coefficient of resistance(TCR)is calculated as−0.58%/°***,the FEA photothermal model is studied through experiments and simulations data regarding LIS,and the average deviation between experiment and simulation is less than 5%.The LIS sensing samples have a thickness of about 14μm,an electrical resistivity of 0.0001–100Ω・m is insensitive to temperature and pressure ***,for a LIS-LIG based temperature sensing array,a correction factor is introduced to compensate for the LIG temperature sensing being disturbed by pressure stimuli,the temperature measurement difference is decreased from 11.2 to 2.6°C,indicating good accuracy for temperature measurement.

关键词： Laser direct writing Temperature sensor Finite element analysis Laser induced graphene Laser induced silver

Nano-silica modified lightweight and high-toughness carbon fiber/phenolic ablator with excellent thermal insulation and ablation performance

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Defence technology（防务技术） 2024年第1期31卷 192-199页

作者： Wenjie Xu Wenda Song Xianfeng Jia Cheng Ma Jitong Wang Wenming Qiao Licheng Ling State Key Laboratory of Chemical Engineering East China University of Science and TechnologyShanghai 200237China School of Chemical Engineering and Materials Changzhou Institute of TechnologyChangzhou 213032China Key Laboratory of Specially Functional Polymeric Materials and Related technology(Ministry of Education) School of Materials Science and EngineeringEast China University of Science and TechnologyShanghai 200237China

Lightweight and high-toughness carbon fiber/phenolic ablator(CFPA)is required as the Thermal Protection System(TPS)material of aerospace vehicles for next-generation space *** improve the ablative properties,silica sol with good particle size distribution prepared using tetramethoxysilane(TMOS)was blended with natural rubber latex and deposited onto carbon fiber felt,which was then integrated with phenolic aerogel matrix,introducing nano-silica into the framework of *** modified CFPA with a low density of 0.28—0.31 g/cm3exhibits strain-in-fracture as high as 31.2%and thermal conductivity as low as 0.054 W/(m·K).Furthermore,a trace amount of nano-silica could effectively protect CFPA from erosion of oxidizing atmosphere in different high-temperature *** oxyacetylene ablation test of 3000°C for 20 s shows a mass ablation rate of 0.0225 g/s,a linear ablation rate of 0.209 mm/s for the modified CFPA,which are 9.64%and 24.82%lower than the unmodified ***,the long-time butane ablation test of 1200°C for 200 s shows an insignificant recession with mass and linear ablation rate of 0.079 g/s and 0.039 mm/s,16.84%and 13.33%lower than the unmodified ***,the fixed thermocouple in the test also demonstrates a good thermal insulation performance with a low peak back-face temperature of 207.7°C,12.25%lower than the unmodified ***,the nano-silica modified CFPA with excellent overall performance presents promising prospects in high-temperature aerospace applications.

关键词： Nano-silica Carbonfiber Phenolic aerogel Insulation Ablation

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 ***,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 *** 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 *** 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 *** 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 *** show that the promising HER catalysts include Pt atoms in C_(4) and Sc atoms in C_(1)N_(3) coordination ***,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 *** 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

Density functional theory study of B- and Si-doped carbons and their adsorption interactions with sulfur compounds

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Carbon Energy 2024年第2期6卷 195-208页

作者： Peng Guo Hong Zhang Shuliang Dong Libao An College of Mechanical Engineering North China University of Science and TechnologyTangshanHebeiChina College of Life sciences North China University of Science and TechnologyTangshanHebeiChina

Understanding the adsorption interactions between carbon materials and sulfur compounds has far-reaching impacts,in addition to their well-known important role in energy storage and conversion,such as lithium-ion *** this paper,properties of intrinsic B or Si single-atom doped,and B-Si codoped graphene(GR)and graphdiyne(GDY)were investigated by using density functional theory-based calculations,in which the optimal doping configurations were explored for potential applications in adsorbing sulfur *** showed that both B or Si single-atom doping and B-Si codoping could substantially enhance the electron transport properties of GR and GDY,improving their surface ***,B and Si atoms displayed synergistic effects for the codoped configurations,where B-Si codoped GR/GDY exhibited much better performance in the adsorption of sulfurcontaining chemicals than single-atom doped *** addition,results demonstrated that,after B-Si codoping,the adsorption energy and charge transfer amounts of GDY with sulfur compounds were much larger than those of GR,indicating that B-Si codoped GDY might be a favorable material for more effectively interacting with sulfur reagents.

关键词： adsorption density functional theory doping graphdiyne graphene sulfur compounds

Deterioration Reason and Improvement Measure of the Retarding Effect of Protein Retarder on Phosphorus Building Gypsum

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Journal of Wuhan University of technology(Materials science) 2024年第4期39卷 962-967页

作者：刘志刚 TANG Zezheng 杨立荣 WANG Chunmei XIE Yuantao LIU Yisen College of Materials science and Engineering North China University of Science and TechnologyTangshan 063210China

The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding ***,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was *** pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on *** liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the *** adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.

关键词： protein retarder phosphorus building gypsum deterioration reason improvement measure

Enhancing SAEAs with unevaluated solutions:a case study of relation model for expensive optimization

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science China(Information sciences) 2024年第2期67卷 41-58页

作者： Hao HAO Xiaoqun ZHANG Aimin ZHOU institute of Natural sciences Shanghai Jiao Tong University Shanghai Frontiers science Center of Molecule Intelligent Syntheses School of Computer science and technology East China Normal University

Surrogate-assisted evolutionary algorithms(SAEAs) hold significant importance in resolving expensive optimization problems. Extensive efforts have been devoted to improving the efficiency of SAEAs through the development of proficient model-assisted solution selection methods, which, however, first requires generating high-quality solutions. The fundamental paradigm of evaluating a limited number of solutions in each generation within SAEAs reduces the variance of adjacent populations, thereby affecting the quality of offspring solutions. This is a frequently encountered issue yet receives little attention. To address the issue, this paper presents a framework using unevaluated solutions to enhance the efficiency of *** surrogate model is employed to identify high-quality solutions for the direct generation of new solutions without evaluation. To ensure dependable selection, we have introduced two tailored relation models to select the optimal solution and the unevaluated population. A comprehensive experimental analysis is performed on two test suites, which showcases the superiority of the relation model over regression and classification models in the solution selection phase. Furthermore, the surrogate-selected unevaluated solutions with high potential have been shown to enhance the efficiency of the algorithm significantly.

关键词： expensive optimization unevaluated solutions relation model surrogate-assisted evolutionary algorithm