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煤间接液化灰渣制备免烧砖研究

中国矿业大学学报 2015年第2期44卷 354-358页

作者：章丽萍温晓东史云天陈傲蕾曲宏斌 dhawal chheda 中国矿业大学(北京)化学与环境工程学院 University of Cincinnati CincinnatiOhio-45220.USA

基于煤炭液化合成油过程中产生的灰渣急需进行合理利用与处置的紧迫性,实验以某企业煤间接液化过程中产生的气化渣、锅炉渣、除尘灰为研究对象,采用了氧化物成分分析、工业分析、元素分析、电子扫描显微镜(SEM)以及能谱仪(EDS)对3种灰... 详细信息

基于煤炭液化合成油过程中产生的灰渣急需进行合理利用与处置的紧迫性,实验以某企业煤间接液化过程中产生的气化渣、锅炉渣、除尘灰为研究对象,采用了氧化物成分分析、工业分析、元素分析、电子扫描显微镜(SEM)以及能谱仪(EDS)对3种灰渣的组分、元素组成、表面结构进行测试分析,探讨了以气化渣和锅炉渣为制备免烧砖的主材料,以生石灰、水泥、除尘灰为辅料,以石膏为激发剂,采用正交实验,通过预搅拌、陈化、二次搅拌、成型、蒸汽养护、脱模出室分检工序制备免烧砖.结果表明:气化渣、锅炉渣、除尘灰、石灰、石膏、水泥的质量分数分别为35.6%,32.4%,14%,8%,4%,6%,在100℃蒸养18h可制备出符合《非烧结砖垃圾尾矿砖》(JC/T422—2007)标准和《蒸压灰砂砖》(GB 11945—1999)标准要求的免烧砖.

关键词：煤间接液化灰渣免烧砖蒸汽养护抗压强度

Flue gas analysis for biomass and coal co‑fring in fuidized bed:process simulation and validation

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International Journal of Coal Science & Technology 2022年第4期9卷 71-81页

作者： Daulet Zhakupov Lyazzat Kulmukanova Yerbol Sarbassov dhawal Shah Department of Chemical and Materials Engineering School of Engineering and Digital SciencesNazarbayev University010001 Nur-SultanKazakhstan

Coal-conversion technologies,although used ubiquitously,are often discredited due to high pollutant emissions,thereby emphasizing a dire need to optimize the combustion *** co-fring of coal/biomass in a fuidized bed reactor has been an efcient way to optimize the pollutants ***,a new model has been designed in Aspen Plus®to simultaneously include detailed reaction kinetics,volatile compositions,tar combustion,and hydrodynamics of the *** of the process model was done with variations in the fuel including high-sulfur Spanish lignite,high-ash Ekibastuz coal,wood pellets,and locally collected municipal solid waste(MSW)and the temperature ranging from 1073 to 1223 *** composition of the exhaust gases,namely,CO/CO_(2)/NO/SO_(2)were determined from the model to be within 2%of the experimental ***-combustion of local MSW with Ekibastuz coal had fue gas composition ranging from 1000 to 5000 ppm of CO,16.2%–17.2%of CO_(2),200–550 ppm of NO,and 130–210 ppm of SO_(2).A sensitivity analysis on co-fring of local biomass and Ekibastuz coal demonstrated the optimal operating temperature for fuidized bed reactor at 1148 K with the recommended biomass-to-coal ratio is 1/4,leading to minimum emissions of CO,NO,and SO_(2).

关键词： Biomass cofring Fluidized-bed combustion Advanced process simulation Flue-gas emissions Fuel utilization Aspen plus

Effect of ambient polycyclic aromatic hydrocarbons and nicotine on the structure of Aβ_(42) protein

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Frontiers of Environmental Science & Engineering 2023年第2期17卷 9-18页

作者： Samal Kaumbekova Mehdi Amouei Torkmahalleh Naoya Sakaguchi Masakazu Umezawa dhawal Shah Department of Chemical and Materials Engineering School of Engineering and Digital SciencesNazarbayev UniversityKabanbay Batyr 53Nur-Sultan010000Kazakhstan Department of Materials Science and Technology Faculty of Advanced EngineeringTokyo University of Science6-3-1 NiijukuKatsushikaTokyo 125-8585Japan

Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons(PAHs)with the progression of neurodegenerative disorders,either by using statistical data from various cities,or via tracking biomarkers during in-vivo *** different neurodegenerative disorders,PAHs are known to cause increased risk for Alzheimer’s disease,related to the development of amyloid beta(Aβ)peptide ***,the complex molecular interactions between peptide monomers and organic pollutants remains *** this work,we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ_(42) peptide monomer in the presence of benzo[a]pyrene,nicotine,and *** the results revealed strong hydrophobic,and hydrogen-bond based interactions between Aβpeptides and these environmental pollutants that resulted in the formation of stable intermolecular *** strong interactions affected the secondary structure of the Aβ_(42) peptide in the presence of the organic pollutants,with almost 50%decrease in theα-helix and 2%–10%increase in theβ-sheets of the ***,the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβpeptide oligomers,and consequent progression of Alzheimer’s disease.

关键词： Polycyclic aromatic hydrocarbons Nicotine toxicology Aβ_(42)peptide Alzheimer’s disease Molecular dynamics simulations Environmental pollution

Stability study on an anti-cancer drug 4-(3,5-bis(2-chlorobenzylidene)-4-oxo-piperidine-1-yl)-4-oxo-2-butenoic acid (CLEFMA) using a stabilityindicating HPLC method

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Journal of Pharmaceutical Analysis 2017年第1期7卷 1-9页

作者： dhawal Raghuvanshi Gregory Nkepang Alamdar Hussain Hooman Yari Vibhudutta Awasthi Department of Pharmaceutical Sciences University of Oklahoma Health Science Center 1110 N. Stonewall Avenue Oklahoma City OK 73117 USA

CLEFMA, 4-(3,5-bis(2-chlorobenzylidene)-4-oxo-piperidine-1-yl)-4-oxo-2-butenoic acid, is a new chemical entity with anti-cancer and anti-inflammatory activities. Here, we report its stability in solution against stress conditions of exposure to acid/base, light, oxidant, high temperature, and plasma. The identity of the degradation products was ascertained by mass and proton nuclear magnetic resonance spectroscopy. To facilitate this study, we developed and validated a reverse phase high performance liquid chromatography method for detection of CLEFMA and its degradation. The method was linear over a range of 1–100 μg/m L; the accuracy and precision were within acceptable limits; it was stability-indicating as it successfully separated cis-/trans-isomers of CLEFMA as well as its degradation product. The major degradation product was produced from amide hydrolysis at maleic acid functionality caused by an acidic buffer, oxidant(3% hydrogen peroxide),or temperature stress(40–60 °C). The log k-p H profile showed that CLEFMA was most stable at neutral p H. In accelerated stability study we found that the shelf-life(T_(90%)) of CLEFMA at 25 °C and 4 °C was 45 days and220 days, respectively. Upon exposure to UV-light(365 nm), the normally prevalent trans-CLEFMA attained cis-configuration. This isomerization also involved the maleic acid moiety. CLEFMA was stable in plasma from which it could be efficiently extracted by an acetonitrile precipitation method. These results indicate that CLEFMA is sensitive to hydrolytic cleavage at its maleic acid moiety, and it is recommended that its samples should be stored under refrigerated and light-free conditions, and under inert environment.

关键词： CLEFMA HPLC Stability Shelf-life Isomerization

A Design Flow for Robust License Plate Localization and Recognition in Complex Scenes

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Journal of Transportation Technologies 2012年第1期2卷 13-21页

作者： dhawal Wazalwar Erdal Oruklu Jafar Saniie 不详

In this paper, we present a new design flow for robust license plate localization and recognition. The algorithm consists of three stages: 1) license plate localization;2) character segmentation;and 3) feature extraction and character recognition. The algorithm uses Mexican hat operator for edge detection and Euler number of a binary image for identifying the license plate region. A pre-processing step using median filter and contrast enhancement is employed to improve the character segmentation performance in case of low resolution and blur images. A unique feature vector comprised of region properties, projection data and reflection symmetry coefficient has been proposed. Back propagation artificial neural network classifier has been used to train and test the neural network based on the extracted feature. A thorough testing of algorithm is performed on a database with varying test cases in terms of illumination and different plate conditions. Practical considerations like existence of another text block in an image, presence of dirt or shadow on or near license plate region, license plate with rows of characters and sensitivity to license plate dimensions have been addressed. The results are encouraging with success rate of 98.10% for license plate localization and 97.05% for character recognition.

关键词： License Plate Localization Character Recognition Reflection Symmetry Coefficient Artificial Neural Network