反应工程方法在锂电池真空干燥模拟上的应用

锂离子电池注液之前的真空干燥,对于电芯的循环性能、安全性、稳定性有极其重要的影响。电芯结构设计、材料体系、烘箱尺寸等的不同会导致真空干燥过程存在差异。反应工程方法(REA)在常压、高初始水含量的对流干燥模拟预测上已有广泛应用,本研究将REA干燥理论应用于真空、低初始水含量的干燥过程仿真,发现与实验结果匹配良好。同时考虑了电芯气袋与烘箱环境湿度变化对干燥过程的影响,水含量预测偏差小于10%,利用单因子仿真实验所总结的规律能用于指导锂电池真空干燥工艺的改善。介绍了该模型在生产中的应用情况,也表明REA将在锂电池真空干燥预测上有很好的工业应用前景。     

水残磷酸二铵水分的快速测定

由美国进口的磷酸二铵 ,被广泛用于我国的农业生产 ,由于装卸、运输环节较多 ,在实际到货中 ,磷酸二铵被水残损是经常发生的事件。残损的磷酸二铵其水分项目的检测方法目前国内外尚未见报道。因为水分含量是准确评估残损化肥价值的重要指标之一、是贬值的主要依据 ,因此 ,研究制定其测定方法是相当必要的。目前 ,对水分项目的检验方法主要有干燥剂真空干燥法、真空烘箱法、烘箱法等。由于水残磷酸二铵含有大量的外在水分 ,样品无法进行粉碎、均样等处理加工。大量的实验表明 ,干燥剂真空干燥法根本无法对之实施检测 ;真空烘箱法的检测时间一…     

普通烘箱法快速测定粒状重钙游离水含量

化工行业标准 HG2 2 2 2 91规定粒状重钙游离水分含量是采用真空烘箱在一定真空度和温度下 ,以失重来测定。此法对设备有特殊要求 ,耗时在 2 .5 h以上 ,不能满足生产控制的要求。采用普通烘箱在不同温度、不同烘干时间下对粒状重钙的游离水含量进行了测定 ,并将测定结果与真空烘箱法所测结果进行对比 ,摸索出合适的测定条件。实验结果表明 ,采用普通烘箱快速测定重钙中游离水含量的方法是可行的 ,具有测定条件简单、耗时较短的特点 ,其准确度可满足生产中控分析的要求。1　实验部分1·1　主要仪器ZK 82 A型真空干燥箱 ;2 X 2型旋片式真空…     

复混肥料中游离水测定的不确定度评定（偏导数法）

1测定方法 依据GB／T8576-2002真空烘箱法测定，称取一定量试样，在规定的温度、真空度条件下，干燥一定时间，冷却，称重失去的质量，计算游离水含量。     

真空烘箱法测试肥料中游离水分的偏离分析及解决方法

采用真空烘箱法测定肥料中游离水分时,受箱体内水汽平衡的制约,测试结果易低于真实值。采用重设真空法能打破箱体内水汽平衡,降低真空烘箱箱体内空气相对湿度,当DZF6090真空烘箱样品水分总含量低于2.3 g时,重设真空3次,可保证结果的准确性。箱体内空气相对湿度23.5%可作为样品游离水分完全干燥的指示值。     

复合肥及原料中水分含量的快速测定

我公司于2006年8月建成年产200 kt尿基复合肥装置.复合肥以及原料磷铵中水分含量的测定,国标中规定了2种方法,即真空烘箱法和卡尔·费休试剂滴定法.真空烘箱法需要在一定真空条件下干燥2 h,测定时间较长.卡尔·费休试剂滴定法是先用二氧六环或甲醇等有毒溶剂对样品中水分进行萃取,然后再用离心机离心得到萃取液,最后将萃取液注入滴定反应瓶滴定,测定时间需40～50 min.     

青豆在狭缝型分布板流化床中的干燥特性

针对Geldart D类颗粒,以青豆为实验物料,研究了在狭缝型分布板流化床干燥装置(300 mm×200 mm)中的干燥特性。通过与烘箱以及传统多孔型分布板流化床的比较,表明狭缝型分布板特殊的瓦楞结构更有利于提高物料的干燥速率。应用红-黄-蓝(RYB)颜色模型,研究了干燥过程中青豆的色泽变化和体积收缩情况。结果表明,随着干燥温度由60℃升高到80℃和100℃时,物料色泽值由27.9升高到29.8和34.9,收缩率由70.5%降低到55.1%和45.6%,为后续建立青豆的干燥简化(REA)模型提供依据。     

普通烘箱低温快速测定磷酸二铵的水分

我公司在试生产期间对磷铵的水分中间控制分析要求快速,但按国家标准中的真空烘箱法测定1个结果需3h,不能满足生产需要。质检部提出用普通烘箱在常压下测定磷酸二铵的水分,并找出这种方法与真空烘箱法测定结果的误差在允许范围内所对应的温度和干燥时间。     

微波干燥法快速测定无机磷化工产品水不溶物

简述了无机磷化工产品生产过程中水不溶物对生产过程控制的重要性,提出了无机磷化工产品中的水不溶物的快速测定方法——微波干燥法。传统检测方法中无机磷化工产品水不溶物的检测国标方法为烘箱干燥法,本文通过对微波时间的选择、含量的检测、与国标法结果的比较、准确度和精密度的测定,可以得出微波干燥法快速简便、结果准确、精密度高等优点。     

餐厨垃圾烘箱干燥和流化干燥过程动力学

在60—100℃条件下,选择烘箱和流化床分别对餐厨垃圾干燥过程的水分变化动力学特性进行研究,并运用4个模型进行数学拟合处理。结果表明:温度对餐厨垃圾干燥过程的影响显著,随着温度的增加,餐厨垃圾样品的含水率(质量分数)和水分比均快速下降,相同温度下,流化干燥达到平衡含水率所需时间远小于烘箱干燥;餐厨垃圾干燥过程的动力学特性可以用Page模型很好地进行模拟和预测;研究中所用的餐厨垃圾样品,其有效湿分扩散系数在烘箱干燥和流化干燥中分别为3.35×10-10—2.43×10-9,1.00×10-7—2.20×10-7m2/s;活化能分别为46.52,21.93 kJ/mol;餐厨垃圾流化干燥的效率比烘箱干燥要高得多。     

Modeling of Drying of Food Materials with Thickness of Several Centimeters by the Reaction Engineering Approach (REA)

Food materials are highly perishable. Drying is necessary to restrict biological and chemical activity to extend shelf life. A good drying model is useful for design of a better dryer, evaluation of dryer performance, prediction of product quality, and optimization. The reaction engineering approach (REA) is a simple-lumped parameter model revealed to be accurate and robust to model drying of various thin layers or small objects. Modeling drying behavior of different sizes is essential for a good drying model, yet it is still very challenging, even for a traditional diffusion-based model, which requires several sets of experiments to generate the diffusivity function. The REA is implemented in this study, for the first time, to model drying of rather thick samples of food materials. An approximate spatial distribution of sample temperature is introduced and combined with the REA to model drying kinetics. Results have indicated that the REA can model both moisture content and temperature profiles. The accuracy and effectiveness of the REA to model drying of thick samples of food materials are revealed in this study. This has extended the application of REA substantially. The application of the REA is currently not restricted for thin layesr or small objects but also for thick samples.     

Spatial reaction engineering approach as an alternative for nonequilibrium multiphase mass‐transfer model for drying of food and biological materials

Drying is a complex process which involves simultaneous heat and mass transfer. Complicated structure and heterogeneity of food and biological materials add to the complexity of drying. Drying models are important for improving dryer design and for evaluating dryer performance. The lumped reaction engineering approach (L‐REA) has been shown to be an accurate and robust alternative for cost‐effective simulations of challenging drying systems. However, more insightful physics has to be shown spatially. In this study, the REA is coupled with the standard mechanistic drying models to yield the spatial‐REA (S‐REA) as nonequilibrium multiphase mass‐transfer model. The S‐REA consists of a system of equations of conservation with the REA representing the local evaporation and wetting rate. Results of the modeling using the S‐REA match well with the experimental data reported previously. This is the first comprehensive REA approach to model the profiles of water vapor concentration during drying of food and biological materials. This study indicates that the S‐REA can be an accurate nonequilibrium multiphase mass‐transfer model with appropriate account of the local evaporation rate. The overall REA concept is expected to contribute substantially for better and cost‐effective representation of transport phenomena of drying process. © 2012 American Institute of Chemical Engineers AIChE J, 59: 55–67, 2013     

Machine learning of materials design and state prediction for lithium ion batteries

With the widespread use of lithium ion batteries in portable electronics and electric vehicles,further improvements in the performance of lithium ion battery materials and accurate prediction of battery state are of increasing interest to battery researchers.Machine learning,one of the core technologies of artificial intelligence,is rapidly changing many fields with its ability to learn from historical data and solve complex tasks,and it has emerged as a new technique for solving current research problems in the field of lithium ion batteries.This review begins with the introduction of the conceptual framework of machine learning and the general process of its application,then reviews some of the progress made by machine learning in both improving battery materials design and accurate prediction of battery state,and finally points out the current application problems of machine learning and future research directions.It is believed that the use of machine learning will further promote the large-scale application and improve-ment of lithium-ion batteries.     

中间相炭微球在锂离子电池负极材料的应用进展

中间相炭微球(MCMB)具有良好锂离子扩散性、导电性和机械稳定性等优势,是目前应用广泛、综合性能优异的锂离子电池负极材料,但较低理论比容量是制约其发展的关键因素。为了获得性能优良的MCMB基锂离子电池负极材料,改性修饰和复合材料已然成为目前研发重点。笔者论述了碳结构、表界面和复合材料等微观结构设计对MCMB负极材料电化学性能的影响。从碳堆积结构类型、有序性、层间距以及球体粒径大小等方面,论述了碳结构微观设计对MCMB电化学性能的影响。发现具有乱层结构的MCMB在充放电过程中内部产生应力较小,且碳结构较稳定,具有优异循环稳定性;内部具有大量微孔或碳层间距较大的MCMB,在充放电过程中可提高锂离子在电极中的迁移速率,并提供更多的储锂空间,一般具有优良的充放电比容量和倍率性能;小粒径MCMB具有较短的锂离子迁移路径和随之增加的比表面积,通常具有较好倍率性能,伴随着可逆比容量和充放电效率的衰减。从表界面碳层改性、包覆和掺杂改性等方面,论述了表界面改性对MCMB电化学性能的影响。表面碳层修饰可增加MCMB与电解液的相容性及其比表面积,提高了与电解液的接触面积及贮锂容量,改善了锂离子电池负极材料的电化学性能;另外,MCMB表面包覆一层无定型碳,可避免其表面与电解液直接接触,减少电化学副反应的产生,提升其可逆比容量。从碳活性物质复合材料、非碳活性物质复合材料等方面,论述了复合材料微观结构设计对MCMB电化学性能的影响。碳活性物质可降低MCMB内部碳层结构的有序性,减少锂离子嵌入过程中的内部应力,提升MCMB循环稳定性。非碳活性物质诱导MCMB生成更加有序的碳层结构,提高MCMB的比表面积,从而改善MCMB表面与电解液分子的接触能力及其嵌锂性能,有利于提升MCMB负极材料可逆比容量、循环性能和倍率性能。MCMB具有高碳层间距和多缺陷位点等结构特征,有利于钠离子自由脱嵌,应用于钠离子电池时具有良好的可逆比容量、循环稳定性和倍率性能。MCMB的不规则定向层状结构经活化等处理具有较高比表面积,可应用于超级电容器电极材料。最后提出在高性能锂离子电池电极材料快速发展的需求下,从微观结构角度设计MCMB纳米复合材料将是MCMB负极材料的研究重点。     

新法合成磷酸锌锂及其多重数据挖掘

对合成磷酸锌锂的新方法进行了研究.以磷酸锌铵和碳酸锂为原料经室温固相反应得到前驱体,接着让这一前驱体在高温下保温晶化得结晶形态的磷酸锌锂.基于均匀设计试验方案以及数据挖掘技术的应用,研究了研磨时间、保温时间、保温温度对磷酸锌锂晶体合成的影响.XRD表征的结果表明,用最佳工艺条件合成得到的产物为63 nm的LiZnPO4,且产物产率高达99.5%.实验成功地同时优化控制了磷酸锌锂的组成及产率,从而得到比较纯净的、结晶态的磷酸锌锂晶体.     

锂离子电池正极材料磷酸钒锂制备方法研究进展

单斜结构的磷酸钒锂[Li₃V₂（PO₄）₃]材料与其他锂离子电池正极材料相比具有较高的工作电压（3.0~4.8 V）、良好的离子迁移率和优良的热稳定性,是一种具有竞争优势和发展前景的大功率锂离子电池正极材料,成为了近年来研究的热点。综述了锂离子电池正极材料磷酸钒锂的结构特点及其充放电机理。磷酸钒锂的常用合成方法有碳热还原法、水热法、溶胶-凝胶法及流变相法等,着重阐述了磷酸钒锂的不同合成方法对所制备样品的形貌和电化学性能的影响。分析总结了不同合成方法的改进方法,以改善磷酸钒锂正极材料电子导电性和锂离子扩散系数较低的问题。最后,针对磷酸钒锂正极材料在锂离子电池的应用中所存在的问题展望了该材料未来可能的发展方向和研究热点。指出需要优化材料的制备方法以改善材料的颗粒形貌、提高电子导电率和扩散系数等,进而改善材料的循环性能、倍率性能和充放电性能等;需要改进制备流程、提高实验的安全性、简化反应流程和减少制备成本等,以实现磷酸钒锂正极材料的工业化应用。     

锂离子电池正极材料进展

介绍了锂离子电池的发展阶段、工作原理及特点,叙述了锂电池已商业化正极材料钴酸锂、锰酸锂、磷酸铁锂的特性、合成方法及其优缺点,纳米技术锂离子电池正极材料应用及其合成方法。认为应根据现有正极材料出现的问题,通过掺杂、包覆、加入辅助剂和表面修饰改性等方法减低成本,利用纳米材料的优点和微米材料优良的稳定性和容易制备的优点合成纳微分层结构的材料解决纳米材料的低热力学稳定性、团聚及与电解液发生副反应等问题;可以尝试着探索新的方法合成纳米级颗粒．并将最优的方法应用于新材料和经典电极材料的制备,从而充分发挥纳米级材料的尺寸效应和表面效应．改善电极材料的电化学活性．有助于推进纳米正极材料的工业化进程。     

HTV硅橡胶生胶挥发分的快速测定

为了缩短测试甲基乙烯基硅橡胶生胶挥发分的时间,将常压恒温干燥箱烘烤改为真空干燥烘箱烘烤。考察了称样量、烘箱温度、烘烤时间、真空度对测试结果的影响,并与传统的电热恒温干燥箱法测试数据进行对照;验证了此法的精密度、再现性和稳定性。结果表明,较佳测试条件是:取样量为2.0~2.5 g、相对真空度(表压)为-0.09 MPa、烘箱温度150℃、恒温时间40 min,在此条件下测试的甲基乙烯基硅橡胶生胶挥发分数据与采用常规检测方法测得的数据比较吻合,精密度、再现性较好,且测试时间比常规检测方法缩短2 h。     

Application of the reaction engineering approach (REA) for modeling intermittent drying under time-varying humidity and temperature

A ‘good’ drying model is important for the design of dryer, evaluation of dryer performance and prediction of product quality. Among the available models, the reaction engineering approach (REA) is a lumped model, proven to be simple, robust and accurate to model drying of several materials. In this paper, the REA is implemented to model intermittent drying, which is usually practiced for saving energy consumption and maintaining product quality during drying, under time-varying drying air temperature and humidity, which is a challenging drying case to model. For this purpose, the equilibrium activation energy (ΔE_v,b) is defined according to the drying settings in each time period and combined with the relative activation energy (ΔE_v/ΔE_v,b) generated from the convective drying experimental data obtained under constant drying conditions. The mass and heat balances also implement the corresponding drying settings in each time period during the intermittent drying. The results indicate that the REA can describe both the moisture content and temperature profiles of the intermittent drying under time-varying drying air temperature and humidity well. The accuracy, simplicity and robustness of the REA for the intermittent drying under time-varying drying air temperature and humidity are proven here. This has provided a major and significant extension of the REA on modeling challenging drying cases.