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Role of Biomass Gasification in Achieving Circular Economy 生物质气化在实现循环经济中的作用
Pub Date : 2024-05-20 DOI: 10.2174/0124055204319671240515060552
Anil Kumar Vinayak, Hridya Ashokan, Sanyukta Sinha, Yogita Halkara, Anand V P Gurumoorthy
Growing awareness of environmental concerns and the prioritisation of environmentalstewardship necessitates the incorporation of sustainability practices that areboth economical and profitable. This involves transforming existing industrial practicesfrom the ‘take-make-waste’ approach to one that aligns with the principles of a circulareconomy. This includes the use and restoration of bioreserves or the cycling of products ina manner that minimizes waste generation by employing the concepts of reuse and recycling.The adoption of circular economy principles is especially critical in energy-intensiveindustries, and there is increased attention to implementing these principles through biomassgasification. Various methodologies exist for utilizing the potential of biomass byemploying biomass gasification to achieve the desired levels of energy output. Techniquesincorporating circular economy principles for biomass gasification have become increasinglysought after and achieved widespread implementation in the past few decades. In thispaper, we examine the principle of a circular economy and how biomass gasification canbe leveraged in processes requiring high-energy input to achieve the same.
由于人们对环境问题的日益关注以及对环境管理的重视,有必要采用既经济又有利可图的可持续发展做法。这就需要将现有的工业做法从 "索取-制造-浪费 "的方式转变为符合循环经济原则的方式。这包括利用和恢复生物储量,或采用再利用和再循环的概念,以尽量减少废物产生的方式进行产品循环。在能源密集型产业中,采用循环经济原则尤为重要,人们越来越关注通过生物质气化来实施这些原则。通过生物质气化来利用生物质的潜力,以达到所需的能源产出水平,有各种方法。在过去几十年中,将循环经济原则纳入生物质气化的技术越来越受到追捧,并得到广泛实施。在本文中,我们将探讨循环经济的原理,以及在需要高能量输入的工艺中如何利用生物质气化来实现循环经济。
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引用次数: 0
Regulation of the Properties of Polymers based on Thiirane using Mixtures of Amine Hardeners 使用胺类硬化剂混合物调节基于巯基乙烷的聚合物的性能
Pub Date : 2024-05-17 DOI: 10.2174/0124055204303723240510115938
Yuriy Kochergin, Qing He, T. Hryhorenko, Xiangli Meng
Introduction: The possibility of regulating the curing rate and the complexof adhesive, deformation-strength and dynamic mechanical properties of polymersbased on bisphenol A dithioester (thiirane) using a mixture of amine hardeners of variouschemical nature is investigated. Method: Diethylenetriamine, diethylenetriaminomethylphenoland aminopolyamide were investigated as hardeners. The ratio ofthe components of the mixed hardener is selected, which provides the best combinationof strength properties. Results: It was found that the rate of adhesion and cohesivestrength at the initial stage (during the first hour) of curing compositions containing amixture hardener significantly exceeds compositions cured by individual componentsof the mixture. Conclusion: The results of measuring the dynamic mechanical characteristicsof the studied polymers indicate that the dynamic modulus of elasticity,measured at temperatures below and above the transition from a glassy state to a highelastic one, for a sample containing a mixed hardener has an intermediate value betweenthe values characteristic of samples containing individual components of amixed hardener.The ratio of the components of the mixed hardener is selected, which provides the best combination of strength properties.
简介研究了使用不同化学性质的胺类固化剂混合物调节双酚 A 二硫酯(硫烷)聚合物的固化速率以及粘合力、变形强度和动态机械性能的可能性。方法:研究了作为固化剂的二乙烯三胺、二乙烯三胺甲基苯酚和氨基多酰胺。选择混合固化剂中各组分的比例,以获得最佳的强度性能组合。研究结果结果发现,含有混合固化剂的固化组合物在初始阶段(第一小时)的粘附率和内聚强度明显高于由混合物的单个成分固化的组合物。结论对所研究聚合物的动态机械特性进行测量的结果表明,在低于和高于从玻璃态向高弹性态过渡的温度下测量的含有混合固化剂的样品的动态弹性模量,其数值介于含有混合固化剂单个成分的样品的数值之间。
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引用次数: 0
Predicting the Residual Strength of Oil and Gas Pipelines Using the GA-BP Neural Network 利用 GA-BP 神经网络预测油气管道的残余强度
Pub Date : 2024-05-03 DOI: 10.2174/0124055204315589240502052118
Zhanhui Wang, Mengzhao Long, Wenlong Duan, Aimin Wang, Xiaojun Li
Most NN (neural network) research only conducted qualitative analysis,analyzing its accuracy, with certain limitations, without studying its NN model, error convergenceprocess, and pressure ratio. There is relatively limited research on the application ofNN optimized by GA (genetic algorithm) to oil and gas pipelines; Moreover, the residualstrength evaluation of GA-BP NN (genetic algorithm backpropagation neural network) has theadvantages of high global search ability, efficiency not limited by constant differences, and theuse of probability search instead of path search, which has a wide application prospect.Using MATLAB software, establish GA-BP NN models under five residual strengthevaluation criteria and introduce the relative error of the parameters and the pressure ratio tocomprehensively analyze the accuracy and applicability of GA-BP NN.Using MATLAB software to estimate the residual strength of oil and gas pipelines with the GA, artificial NN BP, and GA-BP NN.Firstly, using MATLAB software, a GA-BP NN model was established based on fiveresidual strength evaluation criteria: ASME B31G Modified, BS7910, PCORRC, DNV RPF101, and SHELL92, by changing five factors that affect the residual strength of oil and gaspipelines: diameter, wall thickness, yield strength, corrosion length, and corrosion depth; Second,the trained GA-BP NN model is used to predict the residual strength of the same set of evaluationcriteria test data and compared with the calculation results of five residual strength evaluationcriteria. The relative error of the parameters and pressure ratio are introduced to comprehensivelyanalyze the accuracy and applicability of the GA-BP NN.The error convergence time of the BP NN is longer, and the optimized GA-BP NN hasa shorter convergence time. By comparing the convergence training times of different models, itcan be obtained that for the five sets of residual strength evaluation criteria of ASME B31GModified, BS7910, PCORRC, DNV RP F101, and SHELL92, the optimized GA-BP NN modelsignificantly reduces convergence training times, significantly improves convergence speed, andfurther evolves the system performance. From the relative error and local magnification, it canbe seen that for the ASME B31G Modified evaluation criteria, the maximum relative error ofthe BP NN model is 1.4008%, and the maximum relative error of the GA-BP NN model is0.7304%. For the evaluation criterion BS7910, the maximum relative error of the BP NN modelis 0.7239%, and the maximum relative error of the GA-BP NN model is 0.5242%; for the evaluationcriteria of DNV RP F101, the maximum relative error of the BP NN model is 1.1260%,and the maximum relative error of the GA-BP NN model is 0.4810%; for the PCORRC evaluationcriteria, the maximum relative, error and the maximum relative error of the GA-BP NNmodel is 0.8004%; for the SHELL92 evaluation criterion, the maximum relative error of the BPNN model is 1.2292%, and the
大多数 NN(神经网络)研究只是进行定性分析,分析其精度,具有一定的局限性,没有对其 NN 模型、误差收敛过程和压力比进行研究。此外,GA-BP 神经网络(遗传算法反向传播神经网络)的剩余强度评价具有全局搜索能力强、效率不受常量差异限制、用概率搜索代替路径搜索等优点,具有广泛的应用前景。利用 MATLAB 软件,在五种残余强度评价准则下建立 GA-BP NN 模型,并引入参数相对误差和压力比,全面分析 GA-BP NN 的准确性和适用性。首先,利用 MATLAB 软件,基于五种残余强度评价准则建立了 GA-BP NN 模型:首先,利用 MATLAB 软件,基于 ASME B31G Modified、BS7910、PCORRC、DNV RPF101 和 SHELL92 五种残余强度评价标准,通过改变直径、壁厚、屈服强度、腐蚀长度和腐蚀深度五个影响因素,建立了 GA-BP NN 模型;其次,利用训练好的 GA-BP NN 模型预测同一组评价标准试验数据的残余强度,并与五种残余强度评价标准的计算结果进行比较。引入参数相对误差和压力比来综合分析 GA-BP NN 的准确性和适用性。通过比较不同模型的收敛训练时间,可以得出对于 ASME B31GModified、BS7910、PCORRC、DNV RP F101 和 SHELL92 五套残余强度评价标准,优化后的 GA-BP NN 模型显著减少了收敛训练时间,明显提高了收敛速度,系统性能得到进一步提高。从相对误差和局部放大率可以看出,对于 ASME B31G Modified 评价标准,BP NN 模型的最大相对误差为 1.4008%,而 GA-BP NN 模型的最大相对误差为 0.7304%。在 BS7910 评估标准中,BP NN 模型的最大相对误差为 0.7239%,GA-BP NN 模型的最大相对误差为 0.5242%;在 DNV RP F101 评估标准中,BP NN 模型的最大相对误差为 1.1260%,GA-BP NN 模型的最大相对误差为 0.4810%;在 PCORRC 评估标准中,GA-BP NN 模型的最大相对误差和最大相对误差均为 0.8004%;在 SHELL 评估标准中,BP NN 模型的最大相对误差为 0.7239%,GA-BP NN 模型的最大相对误差为 0.5242%。GA-BP NN的预测结果与五种剩余强度评价标准的计算结果较为接近,预测效果较好,可以较为准确地预测油气管道的剩余强度。根据压力比,BP NN 模型在五种残余强度标准下的平均压力比 A 为 1.0004,GA-BP NN 模型的平均压力比 A 为 0.9998。这些发现对腐蚀性油气管道残余强度的预测具有重要意义。
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引用次数: 0
Thermo-Acoustic Behaviour of K2CrO4 and K4 [Fe(CN)6] in AqueousDimethylformamide at Different Temperatures K2CrO4 和 K4 [Fe(CN)6] 在二甲基甲酰胺水溶液中不同温度下的热声行为
Pub Date : 2024-04-16 DOI: 10.2174/0124055204296907240330083154
Rajalaxmi Panda, Subhraraj Panda, Susanta Kumar Biswal
Acoustic parameters can help us understand how temperature andconcentration affect the behaviour of potassium ferrocyanide and potassium chromate electrolytesin the aqueous solvent Dimethylformamide.The solution's density (ρ), viscosity (η), and ultrasonic speed (u) were measuredat various concentrations and temperatures (ranging from 293 K to 313 K) using a pycnometer,an Ostwald viscometer, and an ultrasonic interferometer at frequencies of 1MHz,respectively. Based on these measurements, other acoustic parameters were calculated,such as free length (Lr), internal pressure (πi), adiabatic compressibility (β), acoustic impedance(Z), relaxation time (τ), and Gibbs free energy (ΔG).These acoustic and thermodynamic parameters were used to explore various interactions,molecular motion, and interaction modes, as well as their effects, which were influencedby the size of the pure component and the mixtures. The analysis showed thatchanges in temperature and concentration led to specific parameter differences, which affectedthe interactions between the solute and solvent.This study demonstrated that increasing the concentration of the mixture increasedthe density, viscosity, and ultrasonic velocity due to the interaction between thesolute and solvent, indicating molecular interaction in the mixture.
声学参数有助于我们了解温度和浓度如何影响亚铁氰化钾和铬酸钾电解质在水性溶剂二甲基甲酰胺中的行为。在不同浓度和温度(从 293 K 到 313 K)下,使用温度计、奥斯特瓦尔德粘度计和频率为 1MHz 的超声干涉仪分别测量了溶液的密度 (ρ)、粘度 (η) 和超声波速度 (u)。这些声学和热力学参数被用来探索各种相互作用、分子运动和相互作用模式,以及它们受纯组分和混合物大小影响的效应。分析表明,温度和浓度的变化会导致特定参数的差异,从而影响溶质和溶剂之间的相互作用。这项研究表明,由于溶质和溶剂之间的相互作用,混合物浓度的增加会提高密度、粘度和超声波速度,这表明混合物中存在分子相互作用。
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引用次数: 0
Predictive Modeling and Optimization of Plywood Drying: An Artificial Neural Network Approach 胶合板干燥的预测建模和优化:人工神经网络方法
Pub Date : 2024-04-08 DOI: 10.2174/0124055204304381240403085107
Darío Guamán-Lozada, María José Tobar Heredia, Mayra Zambrano Vinueza, Roister Alexis Pesantes Ortiz, Marlon Moscoso Martínez, Paul Marcelo Manobanda Pinto
This investigation delves into the optimization of the plywooddrying process through the development of predictive models for output moisture content(MC_Out) and waviness. It focuses on bridging the gap in current methodologies by employingartificial neural networks (ANNs), optimized with genetic algorithms, to enhanceprediction accuracy and process efficiency.A comprehensive experimental design was employed, analyzingthe effects of three wood types (Doncel, Tamburo, and Zapote), two thickness levels, andthree drying speeds on MC_Out and waviness. Data collected were subjected to both traditionalstatistical analysis and ANNs. The ANNs were fine-tuned through genetic algorithms,exploring different network architectures to achieve optimal predictive performance.Statistical models revealed the significant influence of wood type, thickness, anddrying speed on MC_Out and waviness, explaining 95.9% and 84.3% of the variations,respectively. The optimized ANN models, however, demonstrated superior accuracy, withthe MC_Out model achieving fitted R-squared values of 0.940 and 0.757 for training andvalidation sets, respectively, thus outperforming traditional models in predicting dryingoutcomes.The study underscores the effectiveness of ANNs in capturing complex nonlinearrelationships within the plywood drying data, which traditional statistical modelsmight not fully elucidate. The successful optimization of ANN architecture via genetic algorithmsfurther highlights the potential of machine learning approaches in industrial applications,offering a more precise and reliable method for predicting drying process outcomes.The integration of artificial neural networks, optimized through genetic algorithms,represents a significant advancement in the predictive modeling of plywood dryingprocesses. This approach not only offers enhanced prediction accuracy for key variablessuch as MC_Out and waviness but also paves the way for more efficient and controlleddrying operations, ultimately contributing to the production of higher-quality plywood.
本研究通过开发输出含水率(MC_Out)和波浪度的预测模型,对胶合板干燥过程进行了优化。研究采用了综合实验设计,分析了三种木材类型(Doncel、Tamburo 和 Zapote)、两种厚度水平和三种干燥速度对 MC_Out 和波度的影响。对收集到的数据进行了传统的统计分析和 ANNs 分析。统计模型显示,木材类型、厚度和干燥速度对 MC_Out 和波度有显著影响,分别解释了 95.9% 和 84.3% 的变化。然而,优化后的人工神经网络模型表现出更高的准确性,MC_Out 模型在训练集和验证集上的拟合 R 平方值分别为 0.940 和 0.757,因此在预测干燥结果方面优于传统模型。通过遗传算法对人工神经网络结构的成功优化,进一步凸显了机器学习方法在工业应用中的潜力,为预测干燥过程结果提供了更精确、更可靠的方法。这种方法不仅提高了对 MC_Out 和波浪度等关键变量的预测精度,还为更高效、更可控的干燥操作铺平了道路,最终有助于生产出更高质量的胶合板。
{"title":"Predictive Modeling and Optimization of Plywood Drying: An Artificial Neural Network Approach","authors":"Darío Guamán-Lozada, María José Tobar Heredia, Mayra Zambrano Vinueza, Roister Alexis Pesantes Ortiz, Marlon Moscoso Martínez, Paul Marcelo Manobanda Pinto","doi":"10.2174/0124055204304381240403085107","DOIUrl":"https://doi.org/10.2174/0124055204304381240403085107","url":null,"abstract":"\u0000\u0000This investigation delves into the optimization of the plywood\u0000drying process through the development of predictive models for output moisture content\u0000(MC_Out) and waviness. It focuses on bridging the gap in current methodologies by employing\u0000artificial neural networks (ANNs), optimized with genetic algorithms, to enhance\u0000prediction accuracy and process efficiency.\u0000\u0000\u0000\u0000A comprehensive experimental design was employed, analyzing\u0000the effects of three wood types (Doncel, Tamburo, and Zapote), two thickness levels, and\u0000three drying speeds on MC_Out and waviness. Data collected were subjected to both traditional\u0000statistical analysis and ANNs. The ANNs were fine-tuned through genetic algorithms,\u0000exploring different network architectures to achieve optimal predictive performance.\u0000\u0000\u0000\u0000Statistical models revealed the significant influence of wood type, thickness, and\u0000drying speed on MC_Out and waviness, explaining 95.9% and 84.3% of the variations,\u0000respectively. The optimized ANN models, however, demonstrated superior accuracy, with\u0000the MC_Out model achieving fitted R-squared values of 0.940 and 0.757 for training and\u0000validation sets, respectively, thus outperforming traditional models in predicting drying\u0000outcomes.\u0000\u0000\u0000\u0000The study underscores the effectiveness of ANNs in capturing complex nonlinear\u0000relationships within the plywood drying data, which traditional statistical models\u0000might not fully elucidate. The successful optimization of ANN architecture via genetic algorithms\u0000further highlights the potential of machine learning approaches in industrial applications,\u0000offering a more precise and reliable method for predicting drying process outcomes.\u0000\u0000\u0000\u0000The integration of artificial neural networks, optimized through genetic algorithms,\u0000represents a significant advancement in the predictive modeling of plywood drying\u0000processes. This approach not only offers enhanced prediction accuracy for key variables\u0000such as MC_Out and waviness but also paves the way for more efficient and controlled\u0000drying operations, ultimately contributing to the production of higher-quality plywood.\u0000","PeriodicalId":20833,"journal":{"name":"Recent Innovations in Chemical Engineering (Formerly Recent Patents on Chemical Engineering)","volume":"266 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140730326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modeling the Effect of Sulfur Composition in Dispersed SystemsInvolving Organosulfur Compounds 涉及有机硫化合物的分散体系中硫成分的影响建模
Pub Date : 2024-03-13 DOI: 10.2174/0124055204288808240301080254
J. F. Pérez-Sánchez, Ana Maria Mendoza-Martínez, Edgardo J. Suárez Domínguez, A. Palacio-Pérez, Jose Rafael Rodríguez-Rodríguez, Y. Pérez-Badell, Elena F. Izquierdo Kulich
Organosulfur compounds within petroleum have far-reaching consequencesfor the refining industry, combustion of petroleum products, and environmentalquality. They induce corrosion in refining equipment, hamper the efficient burning of petroleumproducts, and contribute to environmental degradation. In high-density asphalt crudes,these compounds are predominantly concentrated within asphaltenes. However, crude oilswith extremely high sulfur content, may be distributed across the four constituent familiesdefined by the SARA analysis of crude oil composition. These compounds, characterizedby differing polarities, can trigger the formation of a dispersed phase, whose destabilizationresults in tube clogging issues.The research problem focuses on understanding how sulfur composition affectsthe formation of a dispersed phase in low-polarity organic dispersion media for sulfurcontaininghydrocarbons. It is investigated because the presence of sulfur in crude oil significantlyaffects the behavior of dispersed phases, which can result in operational and environmentalquality issues to comprehensively assess the impact of sulfur composition on thedynamics and stability of this dispersed phase, we introduce a mesoscopic model based onthe master equation. This model considers the molecular structure of system componentsand their molecular properties, established through computational quantum chemistry andstatistical thermodynamics toolsWhile our research focuses on a two-phase system, our theoretical insights suggestthat increased sulfur content escalates the likelihood of destabilizing the dispersed phase.This adverse effect can be mitigated by incorporating additives capable of reducing thepolarizability of the dispersion medium. The novelty lies in the development of a stochasticmodel to predict the dynamics of dispersed phase formation in sulfur-containing hydrocarbons.This model considers molecular interactions and stochastic processes, offering insightsinto the influence of sulfur composition on phase behavior.A stochastic model, based on molecular structure, predicts accelerated formationwith increased sulfur concentration, reaching non-equilibrium steady states. Limitationsinclude ad hoc transition probabilities and the exclusion of factors like density andviscosity. Real crudes, with complex compositions, may exhibit different behavior. Thepresence of sulfur in the dispersion medium enhances the stability of the dispersed system.Our work sheds light on the intricate interplay between sulfur content and the performanceof petroleum systems, offering potential solutions to mitigate these issues. Quantitativeresults include accelerated dispersed phase formation with increased sulfur concentration.Qualitatively, molecular interactions and stochastic processes were explored, highlightingsulfur's impact on phase dynamics.
石油中的有机硫化合物对炼油工业、石油产品燃烧和环境质量有着深远的影响。它们会腐蚀炼油设备,妨碍石油产品的有效燃烧,并导致环境恶化。在高密度沥青原油中,这些化合物主要集中在沥青质中。不过,硫含量极高的原油可能分布在 SARA 原油成分分析所定义的四个成分家族中。这些化合物具有不同的极性,可引发分散相的形成,而分散相的不稳定性会导致管道堵塞问题。研究问题的重点是了解硫成分如何影响含硫烃类在低极性有机分散介质中形成分散相。为了全面评估硫成分对分散相动力学和稳定性的影响,我们引入了一个基于主方程的介观模型。虽然我们的研究侧重于两相体系,但我们的理论见解表明,硫含量的增加会增加分散相失稳的可能性。该模型考虑了分子相互作用和随机过程,有助于深入了解硫成分对相行为的影响。基于分子结构的随机模型预测,随着硫浓度的增加,分散相的形成会加速,并达到非平衡稳态。局限性包括临时过渡概率以及排除密度和粘度等因素。成分复杂的实际原油可能会表现出不同的行为。我们的工作揭示了硫含量与石油系统性能之间错综复杂的相互作用,为缓解这些问题提供了潜在的解决方案。定量结果包括随着硫浓度的增加而加速分散相的形成;定性结果则探讨了分子相互作用和随机过程,突出了硫对相动力学的影响。
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引用次数: 0
Selective Extraction of Lithium from Spent NMC Battery CathodesUsing Sodium Hydroxide as a Leaching Agent at ElevatedTemperatures 利用氢氧化钠作为浸出剂在高温下从废旧 NMC 电池阴极中选择性提取锂
Pub Date : 2024-03-08 DOI: 10.2174/0124055204298649240229073645
Rohiman Ahmad Zulkipli, Indra Perdana, D. Aprilianto, Tri Rahmawati, Rochmadi
The demand for lithium-ion batteries (LIBs) is rapidly increasing due tothe growth of the electronics and electric vehicle industries. Even though the batteries are rechargeable, their storage capacity decreases, and they eventually end up being wasted. Recycling the spent LIBs is necessary to reduce the environmental impact and utilize the preciousmetals contained in the wasteThe present work focuses on the selective recovery oflithium from the cathodes of spent NMC batteries through the hydrometallurgical process usinga sodium hydroxide solution. The leaching process was carried out in 2 M and 4 M NaOH concentrations for 120 minutes at high pressure and at temperatures of 398.15 K, 423.15 K, 448.15K, and 473.15 K. Experimental results showed that 56.53% of lithium could be recovered withnearly 100% selectivity under the optimum leaching conditions of 473.15 K and 4 M NaOH.The release of lithium ions was due to a combination of sodium adsorption, ion exchange, andimpregnation mechanisms.Calculation results showed that the activation energy of thelithium leaching process was 2.1990×104 J/mol, the reaction was endothermic with enthalpyand entropy at standard conditions (298.15 K) of 4.8936×105 J/mol and 1.4421×103 J/mol/K,respectively.The present work also suggested that total lithium recovery can beincreased through leaching processes.
由于电子和电动汽车行业的发展,对锂离子电池(LIB)的需求正在迅速增长。尽管锂离子电池可以充电,但其存储容量会逐渐减小,最终会被浪费掉。为了减少对环境的影响并利用废弃物中的贵重金属,有必要对废旧 LIB 进行回收。实验结果表明,在 473.15 K 和 4 M NaOH 的最佳浸出条件下,可回收 56.53% 的锂,选择性接近 100%。计算结果表明,锂浸出过程的活化能为 2.1990×104 J/mol,反应为内热反应,标准条件(298.15 K)下的焓和熵分别为 4.8936×105 J/mol 和 1.4421×103 J/mol/K。
{"title":"Selective Extraction of Lithium from Spent NMC Battery Cathodes\u0000Using Sodium Hydroxide as a Leaching Agent at Elevated\u0000Temperatures","authors":"Rohiman Ahmad Zulkipli, Indra Perdana, D. Aprilianto, Tri Rahmawati, Rochmadi","doi":"10.2174/0124055204298649240229073645","DOIUrl":"https://doi.org/10.2174/0124055204298649240229073645","url":null,"abstract":"\u0000\u0000The demand for lithium-ion batteries (LIBs) is rapidly increasing due to\u0000the growth of the electronics and electric vehicle industries. Even though the batteries are rechargeable, their storage capacity decreases, and they eventually end up being wasted. Recycling the spent LIBs is necessary to reduce the environmental impact and utilize the precious\u0000metals contained in the waste\u0000\u0000\u0000\u0000The present work focuses on the selective recovery of\u0000lithium from the cathodes of spent NMC batteries through the hydrometallurgical process using\u0000a sodium hydroxide solution. The leaching process was carried out in 2 M and 4 M NaOH concentrations for 120 minutes at high pressure and at temperatures of 398.15 K, 423.15 K, 448.15\u0000K, and 473.15 K. Experimental results showed that 56.53% of lithium could be recovered with\u0000nearly 100% selectivity under the optimum leaching conditions of 473.15 K and 4 M NaOH.\u0000The release of lithium ions was due to a combination of sodium adsorption, ion exchange, and\u0000impregnation mechanisms.\u0000\u0000\u0000\u0000Calculation results showed that the activation energy of the\u0000lithium leaching process was 2.1990×104 J/mol, the reaction was endothermic with enthalpy\u0000and entropy at standard conditions (298.15 K) of 4.8936×105 J/mol and 1.4421×103 J/mol/K,\u0000respectively.\u0000\u0000\u0000\u0000The present work also suggested that total lithium recovery can be\u0000increased through leaching processes.\u0000","PeriodicalId":20833,"journal":{"name":"Recent Innovations in Chemical Engineering (Formerly Recent Patents on Chemical Engineering)","volume":"74 S34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140257228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Failure Pressure of API 5L X100 Pipeline with Single Defect API 5L X100 管道单缺陷失效压力研究
Pub Date : 2024-03-07 DOI: 10.2174/0124055204294716240306065810
Zhanhui Wang, Wenlong Duan, Mengzhao Long, Aimin Wang, Xiaojun Li
With the continuous application of API 5L X100 high-strengthgrade steel pipeline and the development trend of increasing pipeline diameter and designpressure in China's long natural gas and petroleum pipeline, API 5L X100 high-strengthgrade steel pipeline steel is bound to become the aorta in long-distance pipeline constructionin the future. Studying the failure pressure of API 5L X100 high-strength grade steelpipeline has high economic and social benefitsExploring the corrosion mechanism of the two single corroded pipeline modelswith outer defect and inner defect.Using ANSYS Workbench 15.0 software to explore the two single corroded piping models with outer defect and inner defect.Using ANSYS Workbench 15.0 software to explore the two single corrodedpipeline models with outer defect and inner defect and the influence of geometric parameterssuch as defect depth, defect length, defect width, etc., on the maximum equivalentstress and failure pressure investigated. Based on the finite element analysis database, thefailure pressures of two single corroded pipeline models were fitted using Matlab softwareand the fitting formulas.In the corrosion defect area of the pipeline, stress concentration occurs; Far awayfrom the corrosion defect area, the stress distribution is uniform. For the pipeline modelwith outer defect and inner defect, as the defect depth and length increases, failure pressureshows a decreasing trend and is almost unaffected by defect width; As the ratio of diameterto thickness increases, failure pressure shows a decreasing trend; By fitting failure pressureformula of the pipeline models with outer defect and inner defect, a multivariate fittingfunction formula of failure pressure is obtained, with high fitting exactitude.The conclusion obtained have certain guiding values for the normal and stableoperation of natural gas and petroleum transportation pipelines.
随着API 5L X100高强度等级钢制管线的不断应用,以及我国天然气和石油长输管线管径和设计压力不断增大的发展趋势,API 5L X100高强度等级钢制管线钢必将成为未来长输管线建设的主动脉。利用ANSYS Workbench 15.0软件探讨外缺陷和内缺陷两种单一腐蚀管道模型的腐蚀机理,以及缺陷深度、缺陷长度、缺陷宽度等几何参数对最大等效应力和失效压力的影响、研究了几何参数如缺陷深度、缺陷长度、缺陷宽度等对最大等效应力和破坏压力的影响。基于有限元分析数据库,利用 Matlab 软件和拟合公式对两个单一腐蚀管道模型的失效压力进行了拟合。对于有外侧缺陷和内侧缺陷的管道模型,随着缺陷深度和长度的增加,失效压力呈下降趋势,且几乎不受缺陷宽度的影响;随着直径与厚度比值的增加,失效压力呈下降趋势;通过对有外侧缺陷和内侧缺陷的管道模型的失效压力公式进行拟合,得到了失效压力的多元拟合函数公式,拟合精度较高,所得结论对天然气和石油运输管道的正常稳定运行具有一定的指导意义。
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引用次数: 0
Photoesterification of Waste Cooking Oil using ZnO Doped EmptyFruit Bunches Ash Heterogeneous Catalyst 使用掺杂氧化锌的空果枝灰异构催化剂对废食用油进行光酯化反应
Pub Date : 2024-03-04 DOI: 10.2174/0124055204293369240221044511
Norshahidatul Akmar Mohd Shohaimi, Norshahiera Khairul Adnan, Siti Fadhilah Ibrahim
Waste from the palm oil industry, such as empty fruitbunch ash (EFBA) and palm oil mill effluents (POME), is a type of biomass createdduring the production of palm oil and produced in vast quantities. Due to the massiveamounts of empty fruit bunch ash produced because of the exponential rise inworldwide palm oil production, major plantations are having trouble disposing ofthem.The purpose of this research is to study the effectiveness of the ZnO-EFBA catalystunder visible light irradiation for the photoesterification reaction and its physicochemicalproperties of the photocatalyst that will be determined using TGA, SEMEDX,XRD and BET.The biodiesel will be produced by using two steps which are photoesterificationto reduce the FFA value in WCO and followed by transesterification to produceFAMEs. The photoesterification reactions were conducted using WCO under visiblelight irradiation. Various parameters were examined, including different reaction timesof 1 to 4 hours, different methanol to oil molar ratios of 12:1, 14:1, 16:1, and 18:1, anddifferent ZnO-EFBA catalyst loadings ranging from 0 wt.% to 8 wt.%. The obtainedresults demonstrated that each WCO sample has a different optimum condition in thephotoesterification reaction. Moreover, it was observed that lower FFA values correlatedwith higher biodiesel conversion rates in the transesterification reaction with79.06%, 77.72% and 73.33% for samples 1, 2 and 3, respectively.By using EFBA as a heterogeneous catalyst doped with ZnO in the manufacturingof biodiesel, it helps to reduce the waste that the palm oil industry creates, limitingthe adverse effects on human health and environmental harm. Furthermore, biodieselis a renewable, clean-burning alternative to petroleum fuel, which is domesticallymanufacturedThe use of biodiesel as a vehicle fuel boosts energy security, enhancesthe environment and air quality, and offers safety advantages
棕榈油行业产生的废物,如空果束灰(EFBA)和棕榈油厂废水(POME),是棕榈油生产过程中产生的一种生物质,产量巨大。由于全球棕榈油产量呈指数级增长,产生了大量的空果束灰,主要种植园在处理它们时遇到了困难。本研究的目的是研究 ZnO-EFBA 催化剂在可见光照射下进行光酯化反应的有效性,并使用 TGA、SEMDX、XRD 和 BET 测定光催化剂的理化性质。光酯化反应是在可见光照射下使用 WCO 进行的。研究了各种参数,包括不同的反应时间(1 至 4 小时),不同的甲醇与油的摩尔比(12:1、14:1、16:1 和 18:1),以及不同的 ZnO-EFBA 催化剂负载量(0 wt.% 至 8 wt.%)。结果表明,每种 WCO 样品在光酯化反应中都有不同的最佳条件。此外,还观察到在酯交换反应中,较低的 FFA 值与较高的生物柴油转化率相关,样品 1、2 和 3 的转化率分别为 79.06%、77.72% 和 73.33%。通过使用 EFBA 作为掺杂氧化锌的异相催化剂来生产生物柴油,有助于减少棕榈油工业产生的废物,限制对人类健康和环境的不利影响。此外,生物柴油是一种可再生、清洁燃烧的石油燃料替代品,可在国内生产。
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引用次数: 0
Photoelectrode FTO/ Anodized TiO2 Production and Characterizationfor Methylene Blue Affected Photoelectrochemical Decomposition 用于受亚甲蓝影响的光电化学分解的光电极 FTO/ 阳极氧化 TiO2 的生产和特性分析
Pub Date : 2024-02-14 DOI: 10.2174/0124055204284488240120053918
Berrak Çalışkan, Enes Şayan, Hakan Kızıltaş
The production of thin film TiO2 nanostructured systems for electrocatalytic, photocatalytic, and photoelectrocatalytic applications has been an essentialtopic in recent years. Due to the light-sensitive effect of TiO2, it can be produced by various methods and used as a photoelectrode to remove dye. Using magnetron sputtering, Tithin films can be deposited on different substrates and converted into transparent TiO2structures by electrochemical anodization.In this study, the thin Ti film was produced using a magnetic spraying techniqueon the FTO substrate, and then an anodic TiO2 structure was obtained by the anodizationtechnique. TiO2 films produced by the anodizing technique were used as a photoelectrodefor the degradation of MB. The reactor contained 400 mL of 20 mg/L MB solution at20 °C. The produced photoelectrode was characterized by the SEM/EDS, FTIR, XRD, andUV-Vis Spectrophotometer analyses.The EDS analysis confirmed the presence of titanium and oxygen in the FTO/Anodized TiO2 photoelectrode. The XRD results showed that all the peaks of the producedFTO/ Anodic TiO2 were associated with the anatase phase of TiO2. According to the FTIRspectroscopy, the functional groups of the anodized TiO2 were obtained for the FTO/ Anodized TiO2. The electrocatalytic, photocatalytic, and photoelectrocatalytic degradation experiments were performed with the degradation of the dye solution of MB on the FTO/Anodic TiO2 photoelectrode, and the rates of dye degradation were determined as 17.12%,64.67%, and 82.12%, respectivelyThis study showed that the methylene blue dye of FTO/ Anodic TiO2 is asuitable photoelectrode for electrocatalytic, photocatalytic, and photoelectrocatalytic degradation.
生产用于电催化、光催化和光电催化应用的薄膜 TiO2 纳米结构系统是近年来的一个重要课题。由于 TiO2 具有光敏效应,因此可以通过各种方法制备并用作光电电极来去除染料。本研究采用磁控溅射技术在 FTO 衬底上制备 Ti 薄膜,然后通过阳极氧化技术获得阳极 TiO2 结构。阳极氧化技术制备的 TiO2 薄膜被用作降解甲基溴的光电电极。反应器中含有 400 毫升 20 毫克/升的甲基溴溶液,温度为 20 °C。通过扫描电镜/电子显微镜、傅立叶变换红外光谱、X 射线衍射和紫外可见分光光度计分析,对制备的光电极进行了表征。XRD 结果表明,制得的 FTO/Anodic TiO2 的所有峰值都与 TiO2 的锐钛矿相有关。傅立叶变换红外光谱(FTIRspectroscopy)显示了阳极氧化 TiO2 的官能团。在 FTO/Anodic TiO2 光电极上对 MB 的染料溶液进行了电催化、光催化和光电催化降解实验,测定的染料降解率分别为 17.该研究表明,FTO/阳极TiO2光电极适用于亚甲基蓝染料的电催化、光催化和光电催化降解。
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引用次数: 0
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Recent Innovations in Chemical Engineering (Formerly Recent Patents on Chemical Engineering)
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