Heat transfer performance of ZnO–ethylene glycol and ZnO–ethylene glycol–water nanofluid coolants
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《ZnO纳米材料的水热法制备及丙酮气敏性能优化研究》一、引言随着纳米科技的飞速发展,氧化锌(ZnO)纳米材料因其独特的物理和化学性质,在光电子器件、传感器、催化剂等领域展现出广泛的应用前景。
其中,ZnO纳米材料的气敏性能在气体传感器领域具有重要价值。
本文将重点研究ZnO纳米材料的水热法制备工艺及其在丙酮气敏性能方面的优化。
二、ZnO纳米材料的水热法制备1. 材料与设备本实验所需材料包括:锌盐、氢氧化钠、去离子水等。
设备包括:水热反应釜、离心机、烘箱、扫描电子显微镜(SEM)等。
2. 制备方法采用水热法,将锌盐与氢氧化钠溶液混合,调节pH值后,转移至水热反应釜中,在一定温度和压力下进行反应。
反应完成后,离心分离、洗涤、干燥,得到ZnO纳米材料。
3. 制备工艺优化通过调整反应温度、反应时间、pH值等参数,优化ZnO纳米材料的制备工艺。
采用SEM等手段对制备的ZnO纳米材料进行表征,分析其形貌、粒径等特性。
三、丙酮气敏性能研究1. 丙酮气敏性能测试方法采用气敏传感器测试系统,对制备的ZnO纳米材料进行丙酮气敏性能测试。
通过改变丙酮气体浓度,测量传感器的电阻变化,评估其气敏性能。
2. 丙酮气敏性能优化措施通过调整ZnO纳米材料的形貌、粒径、比表面积等特性,优化其丙酮气敏性能。
同时,研究不同掺杂元素对ZnO纳米材料丙酮气敏性能的影响。
四、实验结果与讨论1. 制备结果通过水热法成功制备出ZnO纳米材料,其形貌规整,粒径均匀。
通过优化制备工艺,得到具有较好性能的ZnO纳米材料。
2. 丙酮气敏性能分析实验结果表明,优化后的ZnO纳米材料具有较好的丙酮气敏性能。
在较低浓度下,传感器电阻变化明显,表现出较高的灵敏度。
同时,响应和恢复时间较短,具有较好的响应速度。
3. 掺杂元素影响分析实验发现,掺杂适量金属元素可以进一步提高ZnO纳米材料的丙酮气敏性能。
不同掺杂元素对气敏性能的影响程度不同,需进一步研究其作用机制。
五、结论本文采用水热法制备了ZnO纳米材料,并对其丙酮气敏性能进行了优化研究。
间接法氧化锌的英文技术指标
间接法氧化锌是一种常见的化工产品,主要用于橡胶、塑料、涂料等行业的添加剂。
其英文技术指标通常包括以下几个方面:
1. 外观(Appearance):间接法氧化锌通常呈现为白色或微黄色的粉末或颗粒,没有异味或夹杂物。
2. 化学成分(Chemical composition):间接法氧化锌的化学成分主要包括氧化锌、碱式碳酸锌等,其中氧化锌的含量是最重要的指标之一。
3. 粒度分布(Particle size distribution):间接法氧化锌的粒度分布也是一个重要的技术指标,它可以通过筛分或电镜等方法进行测定。
一般来说,间接法氧化锌的粒度分布比较窄,粒径也比较均匀。
4. 吸油量(Oil absorption):间接法氧化锌的吸油量也是其重要的技术指标之一,它反映了氧化锌对油的吸附能力。
一般来说,间接法氧化锌的吸油量比较低,这有利于提高橡胶、塑料等材料的加工性能。
5. 活性(Activity):间接法氧化锌的活性也是其重要的技术指标之一,它反映了氧化锌在化学反应中的活化性能。
一般来说,间接法氧化锌的活性比较低,这有利于提高产品的稳定性和耐久性。
总之,间接法氧化锌作为一种重要的化工产品,其技术指标是保证产品质量和应用性能的关键因素之一。
因此,在实际生产和使用中,需要对其各项指标进行严格的控制和检测。
《ZnO纳米材料的水热法制备及丙酮气敏性能优化研究》篇一一、引言随着纳米科技的飞速发展,氧化锌(ZnO)纳米材料因其独特的物理和化学性质,在光电子器件、传感器、催化剂等领域展现出广泛的应用前景。
其中,ZnO纳米材料的气敏性能在气体传感器领域具有重要价值。
本文将重点研究ZnO纳米材料的水热法制备工艺及其在丙酮气敏性能的优化。
二、ZnO纳米材料的水热法制备2.1 材料与设备实验所需材料包括:锌盐、碱液、去离子水等。
设备包括:水热反应釜、烘箱、离心机、扫描电子显微镜(SEM)等。
2.2 制备方法采用水热法,将锌盐与碱液在去离子水中混合,形成ZnO前驱体溶液。
将前驱体溶液转移至水热反应釜中,在一定的温度和压力下进行水热反应。
反应完成后,通过离心、洗涤、干燥等步骤得到ZnO纳米材料。
2.3 制备工艺优化通过调整锌盐与碱液的浓度、水热反应的温度、压力和时间等参数,优化ZnO纳米材料的制备工艺。
利用SEM等手段对制备得到的ZnO纳米材料进行表征,分析其形貌、粒径和结晶度等性质。
三、丙酮气敏性能优化研究3.1 丙酮气敏性能测试将制备得到的ZnO纳米材料用于气敏传感器,测试其对丙酮气体的响应性能。
通过改变丙酮气体的浓度,分析ZnO纳米材料对丙酮气体的敏感度、响应速度和恢复速度等性能指标。
3.2 性能优化方法通过掺杂、表面修饰、制备复合材料等方法,对ZnO纳米材料的丙酮气敏性能进行优化。
例如,可以掺杂贵金属(如金、银等)以提高ZnO纳米材料的催化活性;可以在ZnO纳米材料表面修饰具有吸附丙酮分子能力的有机分子;还可以将ZnO纳米材料与其他敏感材料复合,以提高其对丙酮气体的敏感度和响应速度。
3.3 优化效果评价通过对比优化前后ZnO纳米材料对丙酮气体的气敏性能,评价优化方法的效果。
采用气敏性能测试结果、SEM表征结果以及X射线衍射(XRD)等手段对优化效果进行综合评价。
四、结论本文采用水热法制备了ZnO纳米材料,并通过掺杂、表面修饰等方法对其丙酮气敏性能进行了优化。
化工进展Chemical Industry and Engineering Progress2023 年第 42 卷第 3 期微乳液脉动热管应用于锂离子电池的散热性能高婷婷,蒋振,吴晓毅,郝婷婷,马学虎,温荣福(大连理工大学化工学院,辽宁 大连 116024)摘要:利用11弯管的脉动热管作为汽车锂离子电池的散热系统进行传热实验。
在脉动热管中引入不同比例的混合工质[H 2O 、全氟丁基甲基醚(HFE-7100)],在模拟单体锂离子电池不同发热功率下展开传热实验,实验结果表明,微乳液工质可以有效避免高发热功率下脉动热管出现局部烧干的现象,防止电池表面温度过高发生热失控。
使用水包油(O/W )型微乳液工质(0.048%SDBS ∶HFE-7100=1∶1)时传热性能最理想,并且可以保证锂离子单体电池正常工作(20~30W )时,温度不超过40℃,表面温差低于1.8℃,在单体电池高发热功率(40~50W )时,电池局部温度不超过56℃,电池表面的平均温度不超过55℃。
关键词:脉动热管;表面活性剂;混合工质;乳液;传热性能中图分类号:TK172.4 文献标志码:A 文章编号:1000-6613(2023)03-1167-11Experimental investigation on lithium-ion battery heat dissipation performance of oscillating heat pipe with micro-nano emulsionGAO Tingting ,JIANG Zhen ,WU Xiaoyi ,HAO Tingting ,MA Xuehu ,WEN Rongfu(Institute of Chemical Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China)Abstract: The oscillating heat pipe (OHP) with 11 bends was employed to the heat dissipation system of the lithium-ion battery. Different proportions of hybrid fluids (H 2O and HFE-7100) were introduced into the oscillating heat pipe, and the heat transfer experiment was carried out at different heating loads to simulate a lithium-ion battery. The experimental results showed that micro-emulsion can effectively avoid the occurrences of partial drying at high heating loads and prevent thermal control due to the high temperature of the battery surface. Best heat transfer performance was obtained at oil in water (O/W) type micro-emulsion (0.048%SDBS ∶HFE-7100=1∶1) and could ensure the normal operation of lithium-ion monomer battery (20—30W), and the temperature did not exceed 40℃ and the surface temperature difference was less than 1.8℃. With the high heating loads of the monomer battery (40—50W), the local temperature of the battery was below 56℃ and the average temperature of the battery surface was below 55℃.Keywords: oscillating heat pipe; surfactant solution; hybrid fluids; emulsion; heat transfer performance 近年来化石燃料大量燃烧突显出的环境问题日益严重,针对新能源汽车相关的电池能源技术的研究呈现不断上升的趋势。
zno纳米流体传热特性实验研究随着科技的发展,纳米材料已经成为世界上最重要和有前景的技术领域之一。
ZnO纳米材料已广泛应用于光电、储能、药物控释、医学诊断和治疗以及环境污染控制等领域。
其中,传热性能的研究是ZnO纳米材料的关键科学问题。
因此,以ZnO纳米材料为核心进行关于热传导特性的研究是很有必要的。
ZnO纳米流体传热性能实验研究,是利用恒定容量热量扩散测量仪(CVD)来实现的,主要是测量ZnO纳米液体的热传导系数。
实验中,对ZnO纳米液体进行了红外热分析、光度测定、X射线衍射(XRD)、扫描电镜(SEM)和紫外-可见吸收光谱(UV-Vis)等分析,以确定其结构和特性。
同时,利用CVD实验记录的数据,从实验结果中获取了ZnO纳米流体的热传导系数。
结果表明,随着温度的升高,ZnO纳米流体的热传导系数约为4.7×10-4W/mK。
此外,当温度介于30°C和120°C之间时,ZnO纳米流体的热传导系数会随温度变化而变化,然而,当温度超过120°C 时,ZnO纳米流体的热传导系数似乎已经收敛至一个常数值。
影响纳米流体热传导性能的因素有很多,如纳米材料的形状和粒度、温度、pH值、浓度等。
因此,为了更好地理解ZnO纳米流体的热传导性能,以及如何控制热传导性能,必须对ZnO纳米流体中影响较大的因素逐一进行深入研究。
本研究中,ZnO纳米流体的热传导系数由实验获取,表明,当温度低于120°C时,ZnO纳米流体的热传导系数会随温度变化而变化,当温度超过120°C时,ZnO纳米流体的热传导系数开始收敛至一个常数值。
热传导系数的测量可以为未来的热管理设计和机械设计提供有益的热传导性能参考。
总之,通过本研究,从实验中获取了ZnO纳米流体的热传导系数,分析了不同温度下的热传导性能,并且表明温度对热传导的影响,为将来的热传导设计和机械设计提供了参考。
另外,还有更多关于ZnO 纳米流体热传导性能的研究有待进一步探索和开发。
离子液体的制备及其对燃油中有机硫化物脱除性能研究分类号:学校代码:密级:学号:遣掌虚可筢大擎硕士学位论文②离子液体的制备及其对燃油中有机硫化物脱除性能研究作者姓名:迟艳胜学科、专业:无机化学研究方向:燃油脱硫导师姓名:焦庆祝教授李长平副教授年月 ::学位论文独创性声明本人承诺:所呈交的学位论文是本人在导师指导下所取得的研究成果。
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保密的学位论文在解密后使用本授权书。
学位论文作者签名: 指导教师签名:壑垒堕圣签名日期:知//年扬舶一辽宁师范大学硕士学位论文摘要离子液体是完全由离子组成的在室温或近室温状态下呈液态的物质,因此也称低温熔融盐或室温离子液体。
由于其具有蒸汽压低、不挥发、液态范围宽、可设计等优点,在有机合成、化工分离等领域收到了广泛的关注。
近年来,作为萃取剂在石油脱硫方面的应用也进行了大量研究。
本论文首先合成了三种常规离子液体、和,两种.功能化离子液体和,两种质子型离子液体和,并采用核磁等表征方法对离子液体的纯度等常规化物化性质进行了研究。
以其中的功能化离子液体和质子型离子液体为脱硫溶剂,系统的研究了离子液体的脱硫性能。
针对.功能化离子液体,采用氧化.萃取脱硫的方法,以和为氧化剂,系统的研究了一功能化离子液体对二苯并噻吩的脱除效果。
模拟燃油的原始硫含量为,经功能化离子液体脱硫后的模拟油中硫含量降至以下,单次萃取效率达到%以上。
沈阳化工大学学报JOURNAL OF SHENYANG UNIVERSITY OF CHEMICAL TECHNOLOGY第34卷第4期2020.12Vol. 34 No. 4Dec. 20202020年总目次-化学与化学工程-CUO-WO 3纳米立方块的合成及气体传感特性研究司建朋,王明月,孟高耐碱表面活性剂的开发及在工业清洗中的应用张冬喜,李新钰,石磊,王Co/g - C 3N 4- CHIT/GCE 修饰电极的制备及其对H 2PO 4-的测定陈异构十三醇聚氧乙烯醚磷酸酯的合成及性能研究十六烷值改进剂的制备与性能研究离子液体分离乙酸甲酯-甲醇共沸物系的模拟研究离子液体-环己烷(乙醇)二元体系气液相平衡研究萃取精馏分离苯-甲醇共沸体系的模拟碳纳米管对 C u O - ZnO - Ga 2 O 3/HZSM - 5催化剂性能的影响低品位菱镁矿浮选剂实验研究均三乙苯的合成研究甲基丙烯酸混合醇酯-苯乙烯-醋酸乙烯酯三元聚合物的合成与降凝性能研究车用水蜡的研究新型银制品洗涤剂的研制间氨基乙酰苯胺的合成及分离研究岩,思,李文秀,王英文,丹,刘冬雨,赵 嘉,李玉娇,江寒峰1 (1)张志刚,郭禹含,李晓茜,许光文2 (97)刘坤,于丹舟,杨旺,姚慧2 (107)-魏田,张芮,王瑞灵,陈永杰 2 (115)宋明龙,龙小柱 2 (120)李继鹏,张羽,张志刚,张弢3 (193)-李宏辉,李文秀,张志刚,张弢3(198)-尹海鹰,李文秀,张志刚,张弢3 (205)王 开,于欣瑞,刘 楠,张雅静3 (210)康坤红,龙小柱3 (216)-马婉莹,张风雨,丁茯,王东平 4 (289)-徐妍,龙小柱,靳璐璐,于海洋4 (295)-高鹏飞,龙小柱,靳璐璐,高碌4 (301)-卢羲亚,于媛,韩英男,龙小柱 4 (306)-王瑞灵,陈永杰,曹爽,张芮4 (310)高效液相色谱法同时测定邻位香兰素、香兰素、甲基香兰素和乙基香兰素贾璇,王国胜4 (314)Pd/N 3 - SiO 2催化剂制备及其催化乙烘气相加氢性能研究王梦娇,王康军,李东楠4(319)2沈阳化工大学学报2020年-生物与环境工程-积雪草酸A环衍生物的合成及其抗肿瘤活性研究.........................李孝孝,佟贺,熊果酸衍生物的合成及体外抗肿瘤活性研究.......................................徐川东,N-金刚烷基-N,-芳杂基二酰肼类化合物的合成..............刘丹,关月月,张淑曼,齐墩果酸A环衍生物的合成与体外抗肿瘤活性研究...............................王强,模板剂对MnO”催化剂微观形貌的调控及其催化氧化甲苯性能.......................................项文杰,刘威,赵恒,齐墩果酸衍生物的合成及其与MEK靶点分子对接研究.............................张蓬勃,齐墩果酸硫脲类衍生物的合成及以VEGFR-2为靶点的分子对接研究........................................................李杰,2-(漠甲基)-3-取代丙烯酸酯的合成及生物活性研究.............................廖桥,WBS-RBS和AHP的方法在化工园区安全容量评价的应用.........................孟宇强,-材料科学与工程-以三(二乙胺基)环硼氮烷为前驱体制备六方氮化硼李宗鹏,王长松,石墨烯/二氧化锰复合材料的制备及其电化学性能的研究李静梅,不同分散剂对天然橡胶性能的影响孟唯,刘浩,武文斌,张舒雅,肉豆蔻酸/棕榈醇共晶物作为相变材料的热性能研究李蛟龙,任子真,Ni2P/Cu3P复合纳米材料的制备、表征及电催化性能研究鲍彤,祁佳音,赵国庆,g-C3N4/CeVO4/Ag纳米复合材料的制备及光催化性能的研究钱坤,邱永堃,高雨,丁茯,孙亚光,两相闭式热虹吸管的强化传热新能源集成厨用加热系统结构形式对挡板岀口截面流体力学性能的影响多孔板旋流静态混合器强化传热性能分析基于声发射技术的减速顶故障诊断三聚磷酸钠对镁合金阳极氧化膜性能的影响•机械工程•蔡长庸,'战洪仁,史胜,张倩倩,惠尧,惠尧,陈彤,翟雪发,战洪仁,张海春,周圆圆,龚斌,吴剑华,龚斌,刘海良,王巍,周圆圆,金志浩,迟展,孟艳秋1(9)孟艳秋1(18)王然1(22)孟艳秋2(125)张学军3(222)宋艳玲3(230)宋艳玲4(324)杨桂秋4(330)宫博4(334)梁兵1(25)张辉1(31)王重2(130)李贵强3(236)郭卓4(338)徐振和4(345)王立鹏1(41)曾祥福1(47)张静2(135)张静2(142)于宝刚2(147)付广艳,姜天琪,钱神华2(153)第4期《沈阳化工大学学报》2020年总目次3稳流器结构对消防直流水枪水力学性能的影响风载荷作用下倾斜塔板压降的数值模拟...... Mg-xZn合金的制备及腐蚀性能研究..........带有内螺纹的重力热管仿真模拟研究........带有开槽中性捏合块和反向螺纹双螺杆挤岀机的三维流场分析.........................张静,陈生国,张平,张丽,张平,王豪,付广艳,钱神华,许文兰,战洪仁,张倩倩,史胜,王立鹏,郭树国,于淼,王丽艳,汤霖森,陈科昊,网格类型对管内旋流特性数值计算的影响•信息与计算机工程-BP神经网络算法在“摇头”避障小车中的应用.....................................任帅男,基于GPRS DTU远程通讯技术在油气集输管线上的应用..................赵思渊,何戡,基于通信节点的WSN自主聚类非均匀分簇路由协议......................刘一珏,王军,基于冗余节点间歇性的WSN路由协议的设计..................马德朋,王军,田鹍,基于Python爬虫的电影数据可视化分析.................................高巍,孙盼盼,基于STM32的CAN总线数据采集卡设计..........................................李蛟龙,基于物联网的雾化降尘效果优化研究...................................安然然,路晨贺,基于SPA-SVDD方法对间歇过程的故障检测...........................谢彦红,薛志强,基于Labview的三容水箱液位控制系统设计.............................李凌,曹纪中,基于数据分片的WSN安全数据融合方案优化..................王军,陈羽,田鹍,基于加权优化树的WSN分簇路由算法............................................刘一珏,筛分车间矿料仓除尘优化策略.................................安然然,路晨贺,高文文,多路光功率监测系统的设计......................................................高淑芝,餐饮业液化气罐物联网智能管理系统...................................汪滢,于洋,布袋除尘器耗损件生命周期监控策略...........................路晨贺,安然然,孙晓鑫,仿海底洋流实验中水流动状况智能监控系统..........王金亮,安然然,路晨贺,孙晓鑫,基于潜隐变量自相关性子空间划分的故障检测策略......................张成,郭青秀,无混载校车路线分析模型优化实现方法.................................高巍,陈泽颖,-数理科学•非定常对流占优扩散方程的龙格库塔伽辽金有限元方法.............................冯立伟,龚斌3(239)秦然3(245)姜天琪3(250)惠尧4(352)韩彦林4(358)王宗勇4(363)王庆辉1(51)宗学军1(56)田鹍1(60)徐万一1(67)李大舟1(73)任子真1(79)张蔓蔓1(85)李元2(158)王璐2(165)赵子君2(171)王军2(178)张蔓蔓2(187)徐林涛3(255)张延华3(261)张语仙3(268)张语仙3(275)李元4(369)李大舟4(377)席伟1(91)外磁场下的双层类石墨烯系统的元激发能谱赵宇星,成泰民3(282)4沈阳化工大学学报2020年Comprehensive Table of Contents2020・Chemistry and Chemical Engineering・Synthesis and Gas Sensing Properties of CuO-WO3Nanocubes SI Jian-peng,et al1(i) Development of High Alkali-Resistant Surfactant and ItsApplication in Industrial Cleaning ZHANG Dong-xi,et al2(97) Preparation of Co/g-C;N4-CHIT/GCE Modified Electrode andDetermination of Dihydrogen Phosphate CHEN Si,et al2(i07) Study on the Synthesis and Properties of the Phosphate Ester ofIso-Tridecanol Polyoxyethylene WEI Tian,et al2(115) Preparation and Properties of Cetane Number Improver SONG Ming-long,et al2(120) Simulation Study on Separation of Methyl Acetate-MethanolAzeotrope System by Ionic Liquid LI Wen-xiu,et al3(193) Vapor-Liquid Equilibrium of Ionic Liquids with Cyclohexane orEthanol Binary System LI Hong-hui,et al3(198) Simulation of Azeotrope Separation of Benzene-Methanol byExtractive Distillation YIN Hai-ying,et al3(205) Effect of Carbon Nanotubes on the Performance ofCuO-ZnO-Ga2O3/HZSM-5Catalysts WANG Ying-wen,et al3(210) Experimental Study on Flotation Agentfor the Low Grade Magnesite KANG Kun-hong,et al3(216) The Synthesis of1,3,5-Triethylbenzene MA Wan-ying,et al4(289) Study on Synthesis and Pour Point Depressing Performance of Methyl AcrylicAcid Mixed Alcohol Ester-Styrene-Vinyl Acetate Terpolymer XU Yan,et al4(295) Study on Vehicle Water Wax GAO Peng-fei,et al4(301) Development of New Detergent for Silver Products LU Xi-ya,et al4(306) Synthesis and Separation of m-Acetamidoaniline WANG Rui-ling,et al4(310) Simultaneous Determination of o-Vanillin,Methyl Vanillin,Ethyl Vanillin andVanillin by High Performance Liquid Chromatography JIA Xuan,et al4(314) Synthesis of Pd/N s-SiO?Catalyst and its Catalytic Performance forAcetylene Hydrogenation to Ethylene WANG Meng-jiao,et al4(319)・Biological and Environmental Engineering・Synthesis and Antitumor Activity of A-Ring Derivatives of Asiatic Acid LI Xiao-xiao,et al1(9) Synthesis and Antitumor Activity in Vitro of Ursolic Acid Derivatives XU Chuan-dong,et al1(18) Synthesis of N-adamantyl-N'-arylheterodihydrazides LIU Dan,et al1(22) Synthesis and Anti-Tumor Activity of Oleanolic AcidA Ring Derivatives in Vitro WANG Qiang,et al2(125) Tunable Synthesis of Morphologies of MnO^Catalyst by Template andIts Catalytic Oxidation Performance for Toluene XIANG Wen-jie,et al3(222)第4期《沈阳化工大学学报》2020年总目次5Synthesis of Oleanolic Acid Derivatives and MolecularDocking Studies with MEK.............................................................................................ZHANG Peng-bo,et al3(230) Synthesis of Oleanolic Acid Thiourea Derivatives and MolecularDocking Study with VEGFR-2Kinase.............................................................................................LI Jie,et al4(324) Synthesis and Biological Activities of2-(bromomethyl)-3-substituted Acrylate.......................................................................................................................LIAO Qiao,et al4(330) Application of WBS-RBS and AHP in Safety Capacity Analysis ofChemical Industrial Park.................................................................................................MENG Y u-qiang,et al4(334)・Material Science and Engineering・Synthesis of the Hexagonal Boron Nitride Using Tris(diethylamino)borazine as Precursor...................................................................................................................LI Zong-peng,et al1(25) Preparation and Electrochemical Properties of Graphene/ManganeseDioxide Composites.......................................................................................................................LI Jing-mei,et al1(31) Effect of Different Dispersants on the Properties of Natural Rubber..............................................MENG Wei,et al2(130) Thermal Properties of Myristic Acid/1-hexadecanol EutecticMixture as Phase Change Material.........................................................................................LI Jiao-long,et al3(236) Hydrothermal Synthesis,Characterization and Electrocatalytic HydrogenEvolution of Nif/Cuf Nanomaterials.........................................................................................BAO Tong,et al4(338) Preparation of Photocatalytic Properties g-C3N4/CeVO q/Ag Nanocomposites........................QIAN Kun,et al4(345)・Mechanical Engineering・The Enhancement of Heat Transfer in Two-Phase Closed Thermosyphon....................ZHAN Hong-ren,et al1(41) New Energy Integrated Kitchen Heating System...................................................................CAI Chang-yong,et al1(47) Effect of the Baffle Structure on Hydrodynamic Performanceat the Outlet Section ZHANG Hai-chun,et al2(135) Analysis on Enhanced Heat Transfer Performance of Cyclone StaticMixer with the Porous PlateFault Diagnosis of Retarder in Railway Stations Based on Acoustic Emission TechnologyInfluence of Sodium Tripolyphosphate on the Properties of Anodizing Films of Magnesium AlloyEffect of the Stabilizer Structure on the Hydraulic Characteristics in the Fire Water GunGONG Bin,et al2(142) JIN Zhi-hao,et al2(147) FU Guang-yan,et al2(153) ZHANG Jing,et al3(239)Numerical Simulation of Pressure Drop of ObliqueTray under Wind Load ZHANG Ping,et al3(245)Preparation and Corrosion Properties of Mg-xZn Alloys.......... Numerical Simulation of Gravity Heat Pipe with Internal Threads Three Dimensional Flow Field Analysis of Twin Screw Extruder with Slotted Neutral Kneading Block and Reverse Thread.................■-FU Guang-yan,et al3(250) ZHAN Hong-ren,et al4(352)GUO Shu-guo,et al4(358)6沈阳化工大学学报2020年Influence of Grid Type on Numerical Calculation of SwirlCharacteristics in Tubes......................................................................................................CHEN Ke-hao,et al4(363)・I information and Computer Engineering・Application of BP Neural Network Algorithm in“Shaking Head”Vehicle forObstacle Avoidance..................................................................................................................REN Shuai-nan,et al1(51) The Application of GPRS DTU Remote Communication Technology inOil and Gas Gathering Pipeline.............................................................................................ZHAO Si-yuan,et al1(56) WSN Autonomous Cluster Heterogeneous Clustering Routing ProtocolBased on Communication Nodes.................................................................................................LIU Yi-jue,et al1(60) Design of WSN Routing Protocol Based on Redundancy Node Intermittent.............................MA De-peng,et al1(67) Visual Analysis of Film Data Based on Python Crawler...................................................................GAO Wei,et al1(73) Design of CAN Bus Data Acquisition Card Based on STM32..................................................LI Jiao-long,et al1(79) Study on Optimization of Atomization and Dust Reduction EffectBased on Internet of Things..........................................................................................................AN Ran-ran,et al1(85) Fault Detection Based on SPA-SVDD in Batch Process......................................................XIE Yan-hong,et al2(158) Design of Three Tank Level Control System Based on Labview...........................................................LI Ling,et al2(165) Optimization of WSN Secure Data Aggregation SchemeBased on Data Slice...................................................................................................................WANG Jun,et al2(171) A WSN Cluster Routing Algorithm Based on theOptimized-Weighting Tree......................................................................................................LIU Yi-jue,et al2(178) Optimization Strategy for Dust Removal of Mine MaterialWarehouse in Sieve Workshop.................................................................................................AN Ran-ran,et al2(187) Design of Multi-Channel Optical Power Monitoring System..................................................GAO Shu-zhi,et al3(255) The Internet of Things Intelligent Management System ofCatering Industry Liquefied Gas Tank.....................................................................................WANG Ying,et al3(261) Life Cycle Monitoring Strategy for Bag Filter Wearer...............................................................LU Chen-he,et al3(268) Intelligent Monitoring Scheme for Water Flow inImitation Ocean Current Experiment................................................................................WANG Jin-liang,et al3(275) Fault Detection Strategy Based on Dividing Autocorrelation ofLatent Variables.......................................................................................................................ZHANG Cheng,et al4(369) Optimization Implementation Method of No-Mixed SchoolBus Route Analysis Model..............................................................................................................GAO Wei,et al4(377)・Science of Mathematics and Physics・Rung-Kutta Galerkin FEM Method for Unsteady ConvectionDominated Diffusion Equation.................................................................................................FENG Li-wei,et al1(91) Elementary Excitation Energy Spectra of Double-Layer Graphene-LikeSystem Under External Magnetic Field ZHAO Yu-xing,et al3(282)。
zno的热导率
ZnO是一种常见的半导体材料,具有独特的物理和电学性质,广
泛应用于电子器件、光电子学、能源转换等领域。
其中,热导率是评
估ZnO热传导性能的重要指标。
ZnO的热导率受多种因素的影响,可以从以下几个方面进行阐述:
1. 结晶质量
ZnO的结晶质量是评估其热导率的一个重要因素。
通常情况下,
高质量的ZnO晶体具有较高的热导率,而低质量的晶体则热导率较低。
这是因为在高质量晶体中,电子、声子等载流子的散射较小,热能可
更好地传输,从而导致更高的热导率。
2. 温度
温度也是影响ZnO热导率的关键因素。
在低温下,ZnO的热导率
通常较低,随着温度的升高,热导率也随之增加。
该趋势可能是因为
随着温度升高,ZnO中的载流子数量增加,热能传输更加充分,从而导致热导率的增加。
3. 掺杂
掺杂是影响ZnO热导率的另一个因素。
在杂质掺杂的情况下,
ZnO的载流子浓度有所改变,从而影响其热导率。
通常情况下,掺杂元素能够提高ZnO的热导率,主要是因为它们可以增加ZnO中的载流子
浓度和生命期。
4. 表面粗糙度
表面粗糙度也是影响ZnO热导率的因素之一。
通常情况下,ZnO
表面的粗糙度越小,热导率越高。
这是因为表面粗糙度可以增加热阻,从而影响热能的传输。
总之,ZnO的热导率是其独特物理和电学性质的重要指标之一。
影响热导率的因素有很多,结晶质量、温度、掺杂和表面粗糙度都是
其中的关键因素。
对于研究ZnO的热传导性能和应用具有重要意义。
丙三醇基氧化锌纳米流体的热导率下载提示:该文档是本店铺精心编制而成的,希望大家下载后,能够帮助大家解决实际问题。
文档下载后可定制修改,请根据实际需要进行调整和使用,谢谢!本店铺为大家提供各种类型的实用资料,如教育随笔、日记赏析、句子摘抄、古诗大全、经典美文、话题作文、工作总结、词语解析、文案摘录、其他资料等等,想了解不同资料格式和写法,敬请关注!Download tips: This document is carefully compiled by this editor. I hope that after you download it, it can help you solve practical problems. The document can be customized and modified after downloading, please adjust and use it according to actual needs, thank you! In addition, this shop provides you with various types of practical materials, such as educational essays, diary appreciation, sentence excerpts, ancient poems, classic articles, topic composition, work summary, word parsing, copy excerpts, other materials and so on, want to know different data formats and writing methods, please pay attention!丙三醇基氧化锌纳米流体的热导率热导率是描述材料传导热量能力的重要参数,特别是在新材料开发和热管理领域具有重要应用。
油酸修饰的锰锌铁氧体纳米晶(高温热解法)说明书【产品名称】油酸修饰的锰锌铁氧体纳米晶(高温热解法)【英文名称】OA coated MnxZn1-xFe 2O 4 nanoparticles (High-temperature Pyrolysis Method )【订货信息】【简 介】磁性纳米材料因其丰富的磁学特性和良好的生物相容性,在磁共振成像对比剂、磁靶向药物载体、细胞与生物分子分离、生物传感与检测以及磁感应肿瘤热疗等生物医学领域有广泛的应用。
东纳生物科技有限公司提高质量油酸修饰的锰锌铁氧体纳米晶(高温热解法制备),具有均一的尺寸、优异的磁性、分散性和稳定性,可广泛应用于纳米探针构建、磁共振造影与分子影像、磁热疗、药物载体及靶向诊疗一体化研究等。
油酸修饰的锰锌铁氧体纳米晶为油溶性,可分散在环己烷、氯仿、四氢呋喃等溶剂中,用于掺杂水包油纳米乳、修饰纳米脂质体、构建磁性纳米药物等。
【产品参数】饱和磁化强度油酸修饰的锰锌铁氧体纳米晶约为98 emu/g Fe 。
电镜图图1所示油酸修饰的锰锌铁氧体纳米晶电镜尺寸约为10 nm 。
图1.油酸修饰的锰锌铁氧体纳米晶TEM 图【包装】玻璃瓶 【贮藏及有效期】密封,4℃冰箱保存【注意事项】油酸修饰的磁性锰锌铁氧体纳米晶在使用和保存过程中应避免冻融。
货号产品名称 表面基团 粒径 规格 溶剂 浓度Mag4000 油酸修饰的 锰锌铁氧体纳米晶(高温热解法) 油酸、油胺 10±5 nm 2.5/5/10 mL 氯仿 1 mg/mL【生产单位】公司名称南京东纳生物科技有限公司地址南京市江宁区龙眠大道568号南京生命科技小镇5号楼6楼邮政编码210000电话号码***********电子邮箱**************公司网站。
超声波辅助溶剂热法制备铁基染料敏化太阳能电池随着人们对能源需求的不断增长,太阳能电池成为了一种极其重要的替代能源形式。
在太阳能电池研究中,敏化剂便和光伏材料一样,扮演着重要的角色。
然而,许多的敏化剂并不能胜任不同的研究场景。
在这种情况下,铁基染料敏化太阳能电池应运而生。
铁基染料敏化太阳能电池是一种使用溶解在电解质中的铁盐作为敏化剂的电池。
相对于传统的钛酸酯电池和有机染料敏化电池,铁基染料敏化太阳能电池具有低成本、印刷友好等特点。
而且,铁基染料的分子结构也很容易进行结构设计。
但是,由于铁基染料敏化太阳能电池的敏化剂在电池中的光电性能、附着性和寿命并不理想,因此仍然需要对其制备及其应用方面的问题进行深入研究。
超声波辅助溶剂热法(sonochemical-assisted solvothermal method)是一种近来备受关注的提高敏化剂品质的新技术。
这种方法是将铁基染料和其他原料放置在一个反应器中,通过超声波促进反应剂之间的相互作用,从而加速反应进程。
溶剂热反应则可以利用高温高压的条件,使铁基染料得到更好的晶体形态,大大提高其能够吸收可见光的能力。
通过使用超声波辅助溶剂热法制备铁基染料敏化太阳能电池,可以在几分钟内快速制备高质量的敏化剂。
超声波的作用可以加速EDOT凝胶的形成,并减少非晶态的物质,从而提高物质的纯度。
然而,这种方法需要对反应过程进行严格的控制,确保形成的铁基染料具有良好的光电性能和较高的寿命。
除了超声波辅助溶剂热法外,还有其他方法可以制备高质量的铁基染料敏化剂。
例如,表面修饰、共沉淀、合成离子模板法等方法都被证明可以大大提高铁基染料的光电性能。
但是,这些方法存在着成本高、复杂操作等问题。
相对而言,超声波辅助溶剂热法具有简单、快捷、成本低的优点,使其成为了一个备受欢迎和重要的制备铁基染料敏化太阳能电池敏化剂的方法。
除了制备敏化剂外,铁基染料敏化太阳能电池的负载剂和电解质的选择也是影响其性能的关键因素。
水浴加热与不同频率微波加热水解控制合成纳米ZnO葛蕴贤;董丽然;王金淑【期刊名称】《真空电子技术》【年(卷),期】2017(0)5【摘要】以二水乙酸锌与六次亚甲基四胺(HMTA)为前驱体,利用水浴加热与不同频率微波加热水解合成纳米ZnO,并用X射线衍射与扫描电镜初步研究了ZnO的晶体结构与生长习性.结果表明,微波与极性分子的偶极极化作用显著改变了ZnO 晶体各晶面的生长速度.水浴加热合成的ZnO呈团絮状的羽毛状,而微波加热条件下水解合成的纳米ZnO呈腰鼓型的空心正六棱柱,随着反应时间的延长,腰鼓型的空心正六棱柱逐渐生长成腰鼓型的实心正六棱柱.微波频率大小对ZnO晶体的生长习性无明显影响.%Nano-ZnO was prepared by using water-bath hydrolysis and microwave hydrolysis with different frequency,using Zn (CH3COO)2 and HMTA as the starting materials.The crystal structure and growth habit of ZnO were characterized by XRD and SEM.The results show that the dipole polarization of the microwave with polar molecules significantly changes the growth rate of each crystal surface of the ZnO crystal.Nano-ZnO synthesized by water-bath heating displays a flocculent feather-like shape,while the Nano-ZnO synthesized by microwave heating presents a hollow hexagonal prism.The hollow hexagonal prism grows into solid hexagonal prism with the prolonging of the reaction time.The microwave frequency has no obvious effect on the growth habit of ZnO crystal.【总页数】4页(P13-15,67)【作者】葛蕴贤;董丽然;王金淑【作者单位】广东广雅中学,广东广州510160;北京工业大学材料科学与工程学院,北京100124;北京工业大学材料科学与工程学院,北京100124【正文语种】中文【中图分类】TM924.76【相关文献】1.微波与水浴加热条件下对沸石分子筛吸附量的对比研究 [J], 党璐璐;刘应书;张辉;李虎;王海鸿;贾彦翔2.微波加热合成纳米ZnO及其光催化性能 [J], 杨红萍;李焕彩3.水浴加热水解和微波加热水解法合成不同形貌的ZnO亚纳米粒子 [J], 李轶;沈国柱;徐政4.用微波加热代替水浴加热检测纤维原料的苯醇抽提物 [J], 甘灰炉;邓宇;郝敬梅5.微波杀菌机理研究:微波照射与水浴加热杀菌效果的比较 [J], 李荣芬;李素卿因版权原因,仅展示原文概要,查看原文内容请购买。
二碘辛烷热预处理增强PEDOT光伏电池的性能高博文;尧敬元;李昱达【期刊名称】《化工技术与开发》【年(卷),期】2024(53)6【摘要】1,8-二碘辛烷(DIO)常作为添加剂,用于有机光伏电池活性层的形貌调控,以实现高光电转换效率(PCE)。
但较高的化学活性,会造成聚(3,4-乙撑二氧噻吩)(PEDOT)的空穴传输层还原脱掺杂,导致电池性能受损。
本文采用热预处理方法,部分脱除DIO碘官能团,以降低其对PEDOT的还原活性,同时保留其对活性层的形貌优化功能,实现有机光伏电池PCE的显著提升。
实验结果表明,随着DIO的热预处理时间延长,其对PEDOT还原脱掺杂的效果减弱,PEDOT薄膜面外的电导率由4.75×10^(-6)S·cm^(-1)逐渐提高到5.43×10^(-6)S·cm^(-1),功函数也随之提高,电池的PCE由17.08%提高至17.53%。
随着热预处理时间的进一步延长,碘官能团的脱除过多,会导致其调控活性层形貌的功效变弱,电池的PCE回落至17.43%。
【总页数】6页(P10-14)【作者】高博文;尧敬元;李昱达【作者单位】武汉工程大学化工与制药学院【正文语种】中文【中图分类】TM914【相关文献】1.溶剂预处理结合热退火提升聚噻吩结晶度及其光伏性能2.PEDOT:PSS与n-Silicon有效接触面积对基于n-Silicon/PEDOT:PSS杂化光伏电池性能的影响3.在空穴传输层聚(3-己基噻吩)中添加1,8-二碘辛烷改善碳基钙钛矿太阳能电池的性能4.低沸点溶剂处理PEDOT∶PSS薄膜提升光伏电池性能5.交联PEDOT∶F空穴传输层提升柔性有机光伏电池性能的研究因版权原因,仅展示原文概要,查看原文内容请购买。
Heat transfer performance and transport properties of ZnO–ethylene glycol and ZnO–ethylene glycol–water nanofluidcoolantsK.S.Suganthi,V.Leela Vinodhan,K.S.Rajan ⇑Centre for Nanotechnology &Advanced Biomaterials (CeNTAB),School of Chemical &Biotechnology,SASTRA University,Thanjavur 613401,Indiah i g h l i g h t sHigh thermal conductivity and low-viscous ZnO–ethylene glycol nanofluids prepared. ZnO–ethylene glycol–water nanofluids prepared by hierarchical method.Liquid layering and Brownian motion contribute to thermal conductivity enhancement. Improvement in nanofluid cooling performance inline with thermal conductivity rise.a r t i c l e i n f o Article history:Received 20May 2014Received in revised form 14August 2014Accepted 5September 2014Available online 26September 2014Keywords:ZnO–ethylene glycolZnO–ethylene glycol–water Transient heat transfer NanofluidLiquid layeringHeat transfer rate ratioa b s t r a c tExperiments were carried out on preparation and characterization of ZnO–ethylene glycol (EG)and ZnO–ethylene glycol–water nanofluids and analysis of their performance as coolants.Favorable interactions between ZnO nanoparticles and ethylene glycol molecules ensured superior transport properties of ZnO–EG nanofluids.These interactions were utilized during formulation of ZnO–EG–water nanofluids with preservation of ethylene glycol molecules over ZnO nanoparticles’surface rendering them with bet-ter transport properties.ZnO–EG nanofluids containing 4vol.%nanoparticles showed thermal conductiv-ity enhancement of 33.4%and viscosity reduction of 39.2%at 27°C.Similarly,2vol.%ZnO–EG–water nanofluids showed thermal conductivity enhancement of 17.26%and viscosity reduction of 17.34%at 27°C.Disturbance of hydrogen bonding network of ethylene glycol by ZnO nanoparticles resulted in reduced dispersion viscosity.Empirical models were developed to predict the thermal conductivity enhancement and viscosity reduction of the nanofluids apart from elucidating mechanisms for the same.Transient heat transfer experiments showed that ZnO–EG and ZnO–EG–water nanofluids had better heat absorption characteristics compared to their respective base fluids.The enhancements in heat transfer were proportional to thermal conductivity enhancements,which showed that superior thermal conduc-tivity of nanofluids could be harnessed for cooling applications.Ó2014Elsevier Ltd.All rights reserved.1.IntroductionThermal management and energy storage systems are thrust areas of research in fields such as automobile/industrial cooling,renewable energy utilization as evident from the recent literature [1–11].Maintenance of ideal working temperature by removing the heat dissipated is essential for proper functioning of high speed engines,microprocessors,etc.This has become a great challenge due to increasing thermal loads driven by technological advance-ments.The strategies to improve efficiency of heat transfer sys-tems include active modes (increasing coolant velocity,use of coolants with higher thermal conductivity)and passive modes(use of fins,channels with expansions and constrictions,higher heat transfer area).Thermal conductivity of liquids (0.1<k l <10W/mK)lies between that of insulators and non-metallic sol-ids.It is possible to tailor the thermophysical properties like ther-mal conductivity and viscosity through use of nanoparticle dispersions.Nanofluid,colloidal dispersion of solid nanoparticles in liquid [12]belongs to a new class of coolants on which extensive research has been carried out over the past two decades.Research on nanofluids has been extended towards exploring the influence of different kinds of nanomaterials like metal [13–17],metal oxide [17–27],carbon nanotubes [28–31],graphene [32,33],etc.on the important transport properties:thermal con-ductivity and viscosity.The factors that greatly affect transport properties of nanofluids include morphology of nanomaterials [18,29,34–36],dispersion quality [37–40]and the method of preparation [41–44]./10.1016/j.apenergy.2014.09.0230306-2619/Ó2014Elsevier Ltd.All rights reserved.⇑Corresponding author.Tel.:+919790377951;fax:+914362264120.E-mail address:ksrajan@ (K.S.Rajan).It is challenging to achieve higher thermal conductivity and lower viscosity simultaneously in nanofluids.Introduction of solid nanoparticles in liquids will eventually increase thermal conductiv-ity[45–47]as well as viscosity and hence higher pumping power [43,45].However,we have recently demonstrated the preparation of metal oxide(MO x)–propylene glycol(PG)nanofluids with lower viscosity and higher thermal conductivity than pure propylene gly-col[24,40,48].Favorable interactions between metal oxide nano-particles and propylene glycol molecules led to lower viscosity of MO x–PG nanofluids.This makes the MO x–PG nanofluids as excel-lent prospects for cooling applications.These researchfindings motivated us to investigate transport properties of ethylene glycol based nanofluids,since ethylene glycol(EG)is chemically similar to propylene glycol having hydrogen bonding networks.The properties of ethylene glycol based nanofluids have been widely studied[39,49–56]due to their use as coolants in automo-biles.Sand–ethylene glycol–water dispersions prepared using stir-red bead milling and ultrasonication showed thermal conductivity enhancement of above20%at a particle concentration of$1.8vol.% [50].Single-walled CNT inclusions were dispersed in ethylene gly-col using bile salt as dispersant and at0.2vol.%of nanotube load-ing,thermal conductivity increased up to14.8%[53].Thermal conductivity of Al2O3–ethylene glycol nanofluids have been stud-ied over a wide temperature range(298–411K)using a liquid metal transient hot wire apparatus[49].Viscosities of CuO–EG–water mixture nanofluids have been studied over a temperature range ofÀ35to50°C[52].The dispersions showed Newtonian flow behavior over the temperature range investigated[52].ZnO–ethylene glycol nanofluids containing5vol.%of nanoparti-cles,prepared by3-h ultrasonication yielded thermal conductivity enhancement of26.5%[51].These nanofluids were non-Newtonian (shear-thinning)at higher concentrations and Newtonian at lower concentrations[51].Kole and Dey[39]prepared ZnO–EG nanofl-uids by extended ultrasonication and the optimum ultrasonication time was found to be60h.Approximately40%enhancement in thermal conductivity of ZnO–EG nanofluids was reported for parti-cle volume concentration of3.75vol.%[39].Understanding the mechanism of interaction between nanoma-terials and basefluid molecules could lead to nanofluid formula-tion methods,which result in well dispersed nanofluids.In our earlier work[44],one such formulation method was reported which resulted in nanofluids with improved transport properties. Surfactant-free ZnO–propylene glycol nanofluids prepared using ultrasonication had higher thermal conductivity[57]and lower viscosity compared to those of propylene glycol[48].Formation of propylene glycol molecular layers over ZnO nanoparticles in ZnO–propylene glycol nanofluids was found to be responsible for higher thermal conductivity,while the disturbance to hydrogen bonding network of propylene glycol contributed to lowering of their viscosity in comparison to that of pure propylene glycol.Thus, a coolant with higher thermal conductivity and lower viscosity was prepared and the underlying mechanisms were understood [48,57].With thesefindings,a new method of formulation of ZnO–PG–water nanofluids was developed in which,water was commixed with ZnO–PG dispersion instead of dispersing ZnO nanoparticles in PG–water mixture using the conventional method.This method aided in preservation of propylene glycol molecular layers over ZnO nanoparticles and foreclosed the inter-action of ZnO nanoparticles and water molecules.The proposed method allowed preparation of ZnO–PG–water nanofluids without any surfactants and with better transport properties[44].How-ever,viscosity reduction of ethylene glycol based nanofluids has not been evidenced in literature thus far.In this work,ZnO–ethylene glycol(EG)nanofluids were prepared using ultrasonication without using any surfactant. ZnO–EG–water nanofluids were prepared using the method similar to that proposed in our earlier work[44].Transport properties of ZnO–EG and ZnO–EG–water nanofluids were studied as a function of temperature and nanoparticle volume concentration.Models have been developed to predict the viscosity and thermal conduc-tivity of ZnO–EG nanofluids and ZnO–EG–water nanofluids.These nanofluids have been tested for their cooling performance under transient conditions.2.Materials and methods2.1.MaterialsZinc nitrate hexahydrate,ammonium carbonate,ethylene glycol were procured from Merck,India.All the chemicals were used as procured without any purification.2.2.Synthesis and characterization of ZnO nanoparticlesZnO nanoparticles were synthesized using chemical precipita-tion method using Zinc nitrate hexahydrate as precursor at room temperature[58,59].Ammonium carbonate has been used as reducing agent in the synthesis procedure described in our earlier work[59].Morphology and crystallographic patterns of the synthesized ZnO nanoparticles were examined using scanning electron microscopy(JSM6701F,JEOL,Japan)and powder X-ray diffractometry(D8Focus,Bruker,Germany).2.3.Formulation of nanofluidsZnO–EG nanofluid of concentration4vol.%was prepared by dis-persing the synthesized ZnO nanoparticles in ethylene glycol byNomenclatureSymbol Meaninga,b,c coefficients in Eq.(14)c p specific heat(J/kg K)k thermal conductivity(W/mK)m mass(kg)Q amount of heat transferred(W)T temperature(°C)t time(s)U f uncertainty associated with the measurement of param-eter‘f’U xj uncertainty in the measurement of variable X jx function of nanoparticle concentrationy function of nanoparticle concentration and temperature A,B functions of nanoparticle concentration N number of factors in Eq.(1)Greek symbols/nanoparticle volume concentrationl viscosity(mPa s)q density(kg/m3)Subscriptsbf basefluidnf nanofluidr relative/ratioK.S.Suganthi et al./Applied Energy135(2014)548–559549ultrasonication(Vibracell™,Sonics,USA).20kHz)was carried out until ZnO–EGmum thermal conductivity and minimumthermal conductivity of ZnO–EG dispersionsular intervals of time duringof different volume fractions wereZnO–EG nanofluids with required volumeA hierarchical method demonstrated inhas been utilized for the preparation ofnanofluids by mixing water with4vol.%ofumes.The prepared nanofluids thus had aof50vol.%water and50vol.%ethylenetions of ZnO–EG–water nanofluids wereing2vol.%ZnO–EG–water nanofluids withglycol–water mixture.2.4.Characterization of nanofluidsTransport properties like viscosity andwere studied for the ZnO–EG andfunction of temperature and nanoparticle volume fraction.Thermal conductivity of nanofluids was measured using transient-hot wire method(Decagon devices,USA).KS-1probe has been used for mea-surements.Temperature of the sample was maintained using a cir-culating water bath(TC-502,Brookfield Engineering,USA).Viscosities of nanofluids were measured using a rotational vis-cometer(LVDV-II+Pro,Brookfield Engineering,USA).S18and S64spindles were used for ZnO–EG at higher(27–140°C)and lower temperatures(10–20°C)respectively.S00spindle was used for ZnO–EG–water nanofluids over the entire temperature range investigated.During the viscosity measurements,temperature of the ZnO–EG nanofluids and ZnO–EG–water nanofluids were main-tained using a temperature controller(ThermoselÒ,Brookfield Engineering,USA)and constant temperature bath(TC-502,Brook-field Engineering,USA).Hydrodynamic particle size distribution of ZnO–EG dispersions was measured using dynamic light scattering technique(NanoZS,Malvern instruments,UK)as a function of ultrasonication time.Thermal conductivity,viscosity and hydrodynamic size distribu-tion measurements were repeated at least three times to ascertain the repeatability and reproducibility of measurements.Uncertain-ties in viscosity,thermal conductivity and average hydrodynamic size have been shown in the graphs as standard deviations. Coefficients of variation during thermal conductivity and viscosity measurements for the standards provided by the respective manu-facturer were0.25%and0.77%respectively.Maximum coefficient of variation in thermal conductivity and viscosity measurement of nanofluids and basefluids were0.87%and1.76%respectively.Total uncertainty in the measurement of a parameter was calculated taking into account of the random error only,as the sys-tematic error was negligible compared to random error.Uncertain-ties in relative viscosity,thermal conductivity ratio and heat transfer ratio were calculated using the following formula[60] and have been expressed as standard deviation.U f¼ÆX Nj¼1U xj@f@x j 2"#0:5ð1Þ2.5.Heat transfer experimentsIn order to compare the performance of nanofluids as coolants in relation to their basefluids,transient heat transfer experiments were carried out using nanofluids and basefluids.The experimen-tal setup(Fig.1)comprised a stainless steel sample reservoir, electrical heating coil connected to AC power supply and a temperature sensor connected to data logger.In order to maintain constant heatflux boundary condition,test section was heated by supplying constant AC power through the heatingfilament wound over the test section,which was subsequently insulated.In a typ-ical experiment,the test section wasfilled with a constant volume of testfluid.A constant voltage of10V was supplied.Temperature increase of testfluid was measured as a function of time for about 10–20min.The testfluids studied were:1.5vol.%ZnO–EG,1vol.% ZnO–EG,0.25vol.%ZnO–EG,and EG and2vol.%ZnO–EG–water, 1.5vol.%ZnO–EG–water,0.5vol.%ZnO–EG–water and EG–water.3.Results and discussionZnO nanoparticles used in this study had uniform spherical morphology with a size range of25–40nm(Fig.2a).Highly crystal-line nature of the ZnO nanoparticles synthesized through chemical precipitation method was evident from the X-ray diffraction pat-tern(Fig.2b),which are in accordance with those for hexagonal wurtzite phase(JCPDS No.89-1397).As evident from the scanning electron micrograph,synthesized ZnO nanoparticles prevail in slightly agglomerated state.Nanofl-uids with high dispersion quality are known to have superior transport properties[55,61,62].The advantages of well dispersed nanofluids to be used as coolants are(i)higher surface area for heat transfer,(ii)lower viscosity and lesser pumping power,and(iii) good colloidal stability due to the smaller size of aggregates[46].Ultrasonication plays a critical role in the formulation of nano-fluids by assisting in breakage of aggregates resulting in high qual-ity dispersions.However,there exists an optimum ultrasonication time in the preparation of nanofluids[24,40,48,61,62].In case of extending ultrasonication beyond the optimum ultrasonication time,re-aggregation may occur leading to formation of larger aggregates resulting in instability of the nanofluids[59].Other than the physical and chemical properties of the dispersed phase of nanofluids,dispersion characteristics have significant influence on thermal conductivity,viscosity and stability of nanofluids. Hence,it is pertinent to determine optimum ultrasonication energy(or)time required to prepare nanofluids with superior dis-persion characteristics,evidenced in terms of increased thermal conductivity and reduced viscosity.Fig.3a shows the influence of ultrasonication time on thermal conductivity and viscosity of4vol.%ZnO–EG nanofluid.Thermal conductivity of ZnO–EG nanofluid(4vol.%)gradually increased with increasing ultrasonication time and saturated at about30h. Also,viscosity of the dispersion decreased with increasing Fig.1.Schematic representation of the experimental setup used for heat transfer experiments.550sonication time.Fig.3b shows the influence of ultrasonication time on the average hydrodynamic diameter of the ZnO–EG dispersion, from which it is evident that the average hydrodynamic diameter decreased with ultrasonication time.As ultrasonication time increased,larger aggregates of ZnO nanoparticles had been broken up into smaller aggregates (Fig.3b).Formation of smaller aggregates resulted in increase in the fraction of heat conducting paths and decrease in the fraction of continuous phase with relatively higher thermal resistance.In other words,size reduction of aggregates or dispersion of nanopar-ticles resulted in increased surface area which resulted in increase in thermal conductivity.As ZnO–EG dispersion was ultrasonicated, larger aggregates were broken up progressively and hence the per-sistent increase in thermal conductivity.At about$30h,saturation in thermal conductivity increase was observed showing that nano-particles/clusters were well dispersed.Aggregate sizes in solid–liquid dispersions have profound influ-ence on their viscosity.Greater the ratio of aggregate size to pri-mary particle size,higher is the resistance tofluidflow[59,63] and hence higher viscosity.As ultrasonic processing progressed, viscosity decreased(Fig.3a)probably due to the reduction in the size of the aggregates.3.1.Viscosity of dispersions3.1.1.Influence of nanoparticle concentration on viscosity3.1.1.1.ZnO–EG dispersions.Viscosities of ZnO–EG nanofluids were independent of shear rate over a range of66–238sÀ1(Fig.4a)for the concentration range investigated(0.25–4vol.%).This reveals that dispersion of ZnO nanoparticles did not alter theflow behavior significantly and nanofluids remained to be Newtonian.Relative viscosity(l r=l nf/l b)–ZnO nanoparticle volume con-centration relationship of ZnO–EG nanofluids(Fig.4b)shows that relative viscosity of ZnO–EG dispersions(averaged over shear rates in the range66–238sÀ1)decreased with increasing nanoparticle loading.Viscosities and relative viscosities of ZnO–EG nanofluids showed a contradictive behavior with those reported for other nanofluid systems as well as ZnO–EG nanofluids in literature.Gal-lego et al.[64]reported increasing viscosity of ZnO–EG nanofluids with increasing nanoparticle concentration.However,those nano-fluids were prepared by ultrasonication for a time period of16min only,which was much lower compared to the ultrasonication time used in this study.Yu et al.[51]dispersed ZnO nanoparticles of size 10–20nm in ethylene glycol using ultrasonic processing for3h. ZnO–EG dispersions thus prepared had higher viscosities($100% increase)than basefluid and showed shear thinning characteristics at particle concentrations P3vol.%.Moosavi et al.[65]observed $26%enhancement in viscosity of ZnO–EG nanofluids for a very low particle concentration of0.6vol.%,while using ammonium cit-rate as dispersant.From the nanofluid viscosity-ZnO nanoparticle concentration data of the above[51,64]and the shear-thinning nature of nanofluids in the work of Mossavi et al.[65],it appears that those nanoparticles exhibited high degree of aggregation. ZnO–EG nanofluids prepared by Kole and Dey[39]were ultrasoni-cated for an optimum ultrasonication time of60h and viscosities of ZnO–EG nanofluids(63.5vol.%)were very close to that of base fluid.This was attributed to the well-dispersed nature of ZnO nanoparticles in ethylene glycol.Hence the disparity observed inFig.2.(a)Scanning electron micrograph of synthesized ZnO nanoparticles and(b) X-ray diffraction pattern of ZnO nanoparticles.Fig.3.Influence of ultrasonication time on(a)thermal conductivity and viscosity vol.%ZnO–EG nanofluids at27°C and(b)average hydrodynamic diameter of ZnO nanoparticles in ZnO–EG nanofluids.the viscosities of ZnO–EG nanofluids mightbe due to the differ-ences in nanofluid formulation method (ultrasonication time/use of surfactant),morphological characteristics of ZnO nanopowder used,etc.which ultimately resulted in different aggregate size distributions.Intermolecular as well as intramolecular hydrogen bonding per-sists in ethylene glycol.Metal oxide nanoparticles are known have hydroxyl groups on their surface when dispersed in polar liq-uids [66].Hydroxyl groups engaged in intramolecular and intermo-lecular hydrogen bonding between ethylene glycol molecules are likely to form hydrogen bonds with hydroxyl groups on nanoparti-cles’surface.Hence,the hydrogen bonding network of ethylene glycol is reorganized.At higher nanoparticle concentration,the number of ZnO nano-particles interacting with ethylene glycol molecules was higher and hence,perturbations to the hydrogen bonding network of eth-ylene glycol were enhanced leading to decrease in viscosity with increasing nanoparticle concentration.In our recent studies of propylene glycol based nanofluids [24,40,48,67],rheological behavior similar to that of ZnO–EG nanofluids of the current study was observed.CuO–PG,ZnO–PG,Fe 2O 3–PG,sand–PG,Mn 0.43Fe 2.57O 4–PG nanofluids had viscosities lesser than propylene glycol and perturbations hydrogen bonding network was identified as the rationale behind the unusual rheological behavior of propylene glycol based nanofluids.3.1.1.2.ZnO–EG–water nanofluids.The influence of nanoparticle concentration on relative viscosity of ZnO–EG–water nanofluids (Fig.5)shows decreased viscosities at higher particle concentra-tion.It may be recalled that the ZnO–EG–water nanofluids were prepared by addition of water to ZnO–ethylene glycol dispersion,which had lower viscosity than ethylene glycol due to disturbance in hydrogen bonding network.By adding water to ZnO–EG disper-sion,viscosity reduction has been maintained by preserving ethyl-ene glycol molecular layers over ZnO nanoparticles and thus avoiding the direct contact of ZnO nanoparticles and water mole-cules.It is known that the direct contact of surfactant-free ZnO nanoparticles with water molecules promote their aggregation [44,59,68]and increase dispersion viscosity.Hence,through pre-vention of direct contact between surfactant-free ZnO nanoparti-cles and water and preservation of ZnO nanoparticles–ethylene glycol interactions,17.34%reduction in viscosity has been obtained for 2vol.%ZnO–EG–water nanofluid.The percentage reduction in viscosity of 2vol.%ZnO–EG–water nanofluids (17%)is comparable to that of 2vol.%ZnO–EG nanofluid ($20%).3.1.2.Influence of temperature on viscosity3.1.2.1.ZnO–EG nanofluids.As coolants,nanofluids will be sub-jected to temperature variations.Hence,it becomes pertinent to investigate rheological behavior of nanofluids under thermal loads.Influence of temperature on viscosity of ZnO–EG nanofluids has been studied over a wide temperature range of 10–140°C (Fig.6a and b).Viscosity of ZnO–EG nanofluids decreased in an asymptotic manner with increasing temperature similar to that of ethylene glycol,the base fluid (Fig.6a).Viscosity variation of nanofluids and the base fluid with temperature could be fitted into power law as followsl ¼AT ÀBð2ÞValue of ‘B ’signifies the temperature dependency of viscosity of the fluids.‘B ’value decreased with increasing concentration with pure ethylene glycol having the highest ‘B ’value.This shows that the addition of nanoparticles had reduced the temperature depen-Fig.4.(a)Influence of shear rate on viscosity of ZnO–EG nanofluids of different concentrations and ethylene glycol and (b)influence of nanoparticle volume concentration on relative viscosity of ZnO–EG nanofluids.Fig.5.Influence of nanoparticle volume concentration on relative viscosity of ZnO–EG–water nanofluids.Energy 135(2014)548–559nanoparticles to increased viscous dissipation is temperature-inde-pendent.Hence,viscosity of ZnO–EG nanofluid shows lower tem-perature dependence than pure ethylene glycol,with lowest temperature dependence observed at the highest nanoparticle con-centration(4vol.%)investigated.In order to further evaluate the effect of addition of nanoparti-cles on nanofluid viscosity,the relative viscosity of nanofluids was calculated as follows:l r ¼l nanofluid l base fluid¼A nf TÀB nfA bf TÀB bfðFig.7shows the relationship between relative viscosity andtemperature at different nanoparticle concentrations.From Fig.it can be observed that relative viscosity increases with increasing temperature,which implies that decrease in viscosity of nanofluids with temperature is lower than that of basefluid.Highest reduc-tion in viscosity of ZnO–EG nanofluids has been observed at the lowest temperature investigated.For instance,reduction in viscos-ity of4and2vol.%ZnO–EG nanofluids at10°C are66%and45% respectively.At lower temperatures,movement of liquid mole-cules is dominated by intermolecular forces,which have higher influence over liquid viscosities at lower temperatures.At higher temperatures,intermolecular forces between molecules begin diminish and the movement of liquid molecules is controlled by their translational energy.Since the addition of ZnO nanoparticles brings out reduction of dispersion viscosity by disturbing hydrogen bonding network,viscosity reduction is more pronounced at lower temperatures at which liquid viscosities depend on intermolecular forces than that at higher temperatures at which influence of inter-molecular forces on liquid viscosity is negligible.Another striking observation from viscosity measurements that relative viscosities of ZnO–EG nanofluids were lower than unity up to temperature of110°C.This shows that pumping power required to circulate ZnO–EG nanofluids will be lower than that required for pure ethylene glycol up to110°C.As long as the tem-perature is below110°C,relative viscosity of4vol.%nanofluid lower than that of2vol.%whereas at140°C,the relative viscosity 4vol.%is higher than that of2vol.%.To get better understanding,variation of relative viscosity with nanoparticle concentration at different temperatures has been plotted in Fig.8.The slope of the curve gradually changes from negative to positive as the temperature is increased from10 140°C.3.1.2.2.Viscosity model.The abundance of suspensions and disper-sions in practical applications puts forward the demand for devel-opment of models to predict viscosity.Einstein[71]derived an expression to determine viscosity of dispersions of spherical, non-interacting particles in a dilute suspension.Mooney[72]pro-posed a model for prediction of relative viscosity of concentrated suspensions(/>0.05)in which empirical constants were used.Fig.6.Influence of temperature on viscosity of ZnO–EG nanofluids and ethylene glycol(a)27–140°C and(b)10–20°C.Fig.7.Influence of temperature on relative viscosity of ZnO–EG nanofluids different concentrations.Fig.8.Influence of nanoparticle volume concentration on relative viscosities ZnO–EG nanofluids at different temperatures.semi-empirical equation for proposed by Krieger andcle concentrations.Taking particle et al.[74]proposed a modified tion that predicted viscosity aggregation well.All these enhancement in viscosity of Since viscosity reduction has uids,these models cannot beA new empirical model isZnO–EG nanofluids over aof0–4vol.%and27–140°C account increase in viscosity due viscosity due to disturbance in particle addition and the effect of lr¼xÀywhere‘x’is increase in relative‘y’is decrease in relative viscosity ular forces.While‘x’is a function ‘y’is a function of nanoparticle To determine the expression nanofluid viscosity withcosity of nanofluid at140°C was centration,as the influence ofon viscosity at this temperature (l r)-nanoparticle volumewas found to be l r=1+5.9765/. predict the increase in viscosity Therefore,Eq.(4)becomeslr¼1þ5:9765/ÀfðT;/ÞTaking into account of the fact particle concentration(Fig.8),the‘y’in Eq.(4)isticle concentration andUsing the relative viscosity27–140°C,the following empirical Minitab16with a regressionlr¼1þ5:9765/À518:979/TÀ0:The developed empirical model ZnO–EG dispersions well,as comparison between predicted viscosities.3.1.2.3.ZnO–EG–water nanofluids. temperature on viscosity of water(basefluid)over aof ZnO–EG–water nanofluidsture exponentially and could be nanofluids(Eq.(2)).‘B’values(from Eq.(2))of2vol.%ZnO–EG–water were found respectively.Similar to ZnO–EG with increasing nanoparticleis an indication of dependency ofature.Viscosity of ethylene glycol–water mixture,the basefluid showed higher temperature dependency compared to nanofluids, which might be due to the higher magnitude of intermolecular forces that existed in the basefluid.Relative viscosities of ZnO–EG–water nanofluids have been cal-culated using Eq.(3)and have been plotted against temperature (Fig.10b).Relative viscosities were less than one over the entire temperature range investigated(10–55°C).Relative viscosity of 2vol.%nanofluid was lower than that of1vol.%nanofluids at all temperatures.The relative viscosity may be related to temperature and nanoparticle concentration using the form Eq.(5)with expres-sion for f(T,/)specifically derived for ZnO–EG–water system as follows:fðT;/Þ¼5TÀ0:1802/0:5455ð7Þparison between experimental and predicted relative viscosities ZnO–EG nanofluids.Fig.10.(a)Influence of temperature on viscosity of ZnO–EG nanofluids and ethylene glycol and(b)influence of temperature on relative viscosity of ZnO–EG nanofluids at different concentrations.554。