亚微米/纳米通道电渗流及控制

通过联立分析双电层泊松-玻兹曼方程、液体流动纳维-斯托克斯方程,以及外加基电压-通道-液体耦合系统电场方程,获得了外加基电压调控下的亚微米/纳米通道电渗流的解析解.分析了固-液界面Zeta电位随外加基电压的响应,得到电渗流速度与外加基电压的关系特性.进一步研究了控制外加基电压以控制电渗流的方法,实时调控电渗流以满足增大输送的溶液流量、反向流动、多溶液混合等输送要求.     

毛细管反相电色谱中电渗流测定方法的研究

根据反相高效液相色谱中同系物保留值的碳数规律,通过迭代分析的方法测定了毛细管电色谱中的电渗流速率,并与一般的测定方法加以比较,探讨了影响电渗流速率测定结果的可能原因。     

尿蛋白分离中微流控芯片的制作与电渗流速度检测的研究

提出了微流控芯片应用于尿蛋白分离中的芯片制作与电渗流速度检测方法,讨论了用SG4009匀胶铬版玻璃制作微流控芯片过程中提高芯片质量的方法;采用以CCD为图像传感器的微通道尺寸的检测方法和以Rh123中性分子为标定物的直接测定电渗流速度的方法进行尿蛋白分离.结果表明,该法可提高临床的诊断率.     

基于电渗流驱动的涡流诱导微混合器

 以电渗流为驱动,设计出一种采用涡流诱导增强混合的微米级混合器。通过控制混合方腔上下壁面电渗流的大小和方向,可诱导腔内流体产生不同的涡流形态,本文重点研究电渗流驱动下形成一个涡流和两个涡流时的混合特性,称相应涡流形态诱导混合下的模式为单涡模式和双涡模式,并采用数学模拟方法定量地研究了两种混合模式下典型的稳态特性和动态特性。研究结果表明：所设计的混合器具有流道短、结构简单,调控方便,可实现高效、连续和稳定的混合等特点;两种混合模式中,双涡诱导混合模式具有更好的应用价值。     

8-羟基喹啉改性铁钛开管柱电色谱

建立8—羟基喹琳改性铁钛开管柱毛细管电色谱法。研究操作条件如流动相组成，pH值对柱电渗流的形响，结果表明改性毛细管柱在碱性条件下稳定，可提供稳定的电渗流与表面性质，有利于建立稳定的电色谱方法。     

C_(60)-g-(乙二胺基)丙基键合硅胶填充柱毛细管电色谱

建立C60-g-(乙二胺基)丙基键合硅胶填充柱毛细管电色谱法。研究操作条件如流动相组成、pH值对柱电渗流的影响.结果表明填充柱与流动相之间存在着快速平衡,可建立稳定的电色谱方法,并且填充柱可以在pH 2.5-7的范围内提供稳定的电渗流,有利于电色谱分离。     

毛细管电色谱聚丙烯酰胺类整体柱对芳香酮类化合物分离性能考察

在N-甲基甲酰胺与三(羟甲基)胺基甲烷(Tris)组成的混合体系中合成了聚丙烯酰胺类毛细管电色谱柱,以实验室自行合成的N,N-二乙基丙烯酰胺取代传统的丙烯酰胺,增强了固定相的疏水性,使分离更彻底.实验考察了电场强度、乙腈浓度、pH值等参数对电渗流的影响,同时对电渗流的重现性及柱寿命进行了评价,实现了7种芳香酮类(含单酮及1,2-二酮)化合物的快速基线分离.     

基于改进型泊松-玻尔兹曼方程的电渗流建模与分析

建立了双电层的离子分布模型，基于经典Poisson-Boltzmann(PB)方程和改进型MPB(modified Poisson Boltzmann)方程对不同浓度和激励电压的离子分布进行了理论研究.结果发现在电压高于0.4V，且自由离子浓度小于10^-4mol/L时，双电层内部的扩散层厚度存在较大的误差.这直接导致了基于Debye长度模拟电渗流运动与实际观测不符，主要因为Debye-Hückel公式具有线性关系不适用于仿真高电压条件下的电渗流运动.因此借助非线性MPB方程求解扩散层厚度，更能精确得到正、负电极宽度为500μm，间距为25μm，在±1V，500Hz电信号产生的最大电渗流速度为1034.31μm/s.     

流-固-电多物理场耦合模型的红细胞流变学研究

红细胞(red blood cell, RBC)受到流体应力发生机械形变的研究越发成熟,但在结合电场、声场、光场或热力场等多物理场的研究依旧不足.通过COMSOL有限元软件建立了流-固-电(流场、固体场和电场)的3场物理耦合模型,对球形和正常RBC 2种不同形状的RBC分别进行迁移模拟研究.与流-固耦合模型相比,发现电场形成的电渗流使细胞运动迁移时,球形细胞受到的von Mises应力高于正常细胞.电渗流效应形成180μm/s的流速导致RBC变为卷曲“C”形姿态,因形状差异,球形和正常RBC在遇到针尖障碍物时的旋转方向不同.针对本文提出的多物理场耦合模型,两种细胞运动轨迹的差异显示了电渗流对不同形状细胞实施空间分离的可行性.     

面向典型微流控芯片的流场测速技术研究

介绍了微流体流动特性测试技术的发展和应用概况,选用激发光源、荧光显微镜和高精度CCD摄像机等建立了显微粒子图像测速装置,用于测量微流控芯片内部电渗流流动特性,并给出显微成像单元、激发光源、示踪粒子的技术指标和适用范围．根据微流控芯片的特征尺寸和内部电渗流速度．分析了应用显微粒子图像测速技术测量微流场速度分布的测量分辨率、测量精度、测速范围等关键问题．研究结果表明：在电场强度100V／cm、宽度50μm的玻璃微通道内,硼砂电渗流速度约为220μm／s,放大倍率低于40倍,MicroPIV动态测速范围能满足流场测速要求;选用直径．300nm的荧光粒子,在高于10倍放大倍率下,粒子像大干3个CCD像元的尺寸,可以进行观测;MicroPIV测速系统的测速精度则与光学系统、图像处理技术、电场力、布朗运动等有关系．     

Temporal and spatial variabilities of sea surface heights in the northeastern South China Sea

Analyses of sea surface height anomalies (SSHA) from Jan. 1993 to Dec. 2001 measured by TOPEX/Poseidon (T/P) satellite altimetry indicate that there are two energy highs of SSHA fluctuations on both sides of the Luzon Strait. The highs centered at (19.5°N, 119.5°E) and (22.0°N, 124.0°E) respectively, are separated by a low energy band in the Strait. Empirical Orthogonal Function (EOF) analysis on the "Far Field" suggests that fluctuations of these two areas are mutually independent. EOF analysis on the "Near Field" shows that SSHA oscillation in the northeastern South China Sea (SCS) is dominated by seasonal variations accompanied with significant intra-seasonal and inter-annual fluctuations. Among which, EOFI and EOF2 reflect 66.7% of the total variance. They are both seasonal but showing three months difference in phase. The basic pattern of EOFI appears to be the seasonal SSHA oscillation centered at (18.0°N, 119.0°E) northwest off Luzon Island, which shows maximums (minimums) in August/Septemb     

Spatial and temporal variations of light rain events over China and the mid-high latitudes of the Northern Hemisphere

Based on observed daily precipitation data, monthly gridded radiosonde upper air temperature and sea surface temperature data from the UK Met Office Hadley Centre, monthly surface air temperature from the Climatic Research Unit at the University of East Anglia and the NCEP/NCAR monthly reanalysis data, this study investigates the spatial and temporal variations of light rain events over China and the mid-high latitudes of the Northern Hemisphere during 1961-2010, and discusses the relationship between the change of light rain events and atmospheric stability, sea surface temperature and atmospheric circulation. The light rain events over East China display a decreasing trend of 3.0%/10 a in summer and winter half years. Over Northwest China, an increasing trend of 4.1%/10 a is found in winter half years, but there is no trend in summer half years. Using empirical orthogonal function (EOF) analysis, it is found that the first two principal components of light rain events over the mid-high latitudes of the Northern Hemisphere show long time scale variations in summer and winter half years. The first EOF modes (EOF1s) for summer and winter half years both depict a long-term increase in light rain events over North America and Southern Europe as well as Northwest China (except in summer half years), and a long-term decrease over most of the Eurasia (Central Europe, Eastern Europe, North Asia and East China). The second EOF mode (EOF2) for summer half year shows that light rain events increase over North America, Southern Europe and South China, but decrease over Eurasia north of 45°N from 1961 to early 1980s, while the trends reverse from late 1980s to 2010. The second EOF mode (EOF2) for winter half years indicates that light rain events increase over North America and South and North China, but decrease over Eurasia north of 40°N from 1961 to early 1980s, while the trends reverse from late 1980s to 2009. Correlation analysis and linear regression analysis suggest that EOF1s may be related to the change in atmospheric static stability associated with global warming, and EOF2s are possibly linked to the AMO.     

南海海面风与海面温度耦合模态分析

为了研究南海海面风与海面温度的相互关系,利用相关分析、经验正交函数分解、奇异值分解等方法对49a的COADS资料的南海海域的海表面温度异常(SSTA)和海表面风异常(SSWA)进行分析。SSTA的EOF1解释了总方差的50.8%,该模态与整个南海SSTA同步变化,时间系数主周期为2~3a,该系数滞后5个月,与Nino3.4指数的相关系数达到0.423;SSWA的EOF1解释了总方差的25.1%,与整个南海SSWA同向变化,时间系数的主要周期为4~8a,但与Nino3.4指数的同步相关系数只有0.04,SSTA和SSWA的SVD分析结果第一模态的方差贡献为86.7%,空间分布很好地体现了SSTA和SSWA之间的正反馈机制,左右奇异向量时间系数达到0.5,且时间系数的主要周期都为4~8a,证实了南海海域海-气耦合的主模态为ENSO模态。     

基于险度函数的无人机备件库存量风险损失度量

为了研究南海海面风与海面温度的相互关系,利用相关分析、经验正交函数分解、奇异值分解等方法对49 a 的COADS 资料的南海海域的海表面温度异常(SSTA) 和海表面风异常(SSWA) 进行分析。SSTA 的EOF1 解释了总方差的50.8%,该模态与整个南海SSTA 同步变化,时间系数主周期为2 ~3 a,该系数滞后5个月,与Nino3.4 指数的相关系数达到0. 423;SSWA 的EOF1 解释了总方差的25. 1%,与整个南海SSWA同向变化,时间系数的主要周期为4 ~8 a,但与Nino3.4 指数的同步相关系数只有0.04,SSTA 和SSWA 的SVD分析结果第一模态的方差贡献为86.7%,空间分布很好地体现了SSTA 和SSWA 之间的正反馈机制,左右奇异向量时间系数达到0.5,且时间系数的主要周期都为4 ~8 a,证实了南海海域海-气耦合的主模态为ENSO模态。     

吕宋海峡黑潮表层形态EOF模态分析

应用Argos表层漂流浮标资料所指示的浮标轨迹图以及基于卫星高度计资料和三维水动力模型海面高度场数据的经验正交函数(EOF)模态分析,探讨了黑潮在吕宋海峡形变的时空分布特征.结果表明:吕宋海峡黑潮的形态呈现明显的季节变化,其中跨隙形态为其最基本的形态;秋冬两季,部分黑潮水会以流套和分支的形式入侵南海,流套最西可延伸至118°E;春夏季节则儿乎不出现流套或者分支的结构,相反会有一部分南海水汇入黑潮主干.模型数据模态分析结果还再现了冬季黑潮水沿着南海北部陆坡向西入侵的形态.     

Retrieval and analysis of sea surface air temperature and relative humidity

Air temperature and relative humidity have been the main parameters of meteorology study.In the past data could be obtained from in-situ observations,but the observations are local and sparse,especially over ocean.Now we can get them from satellites,yet it is hard to estimate them from satellites directly so far.This paper presents a new method to retrieve monthly averaged sea air temperature(SAT) and relative humidity(RH) near sea surface from satellite data with artificial neural networks(ANN).Compared with the observations in Pacific and Atlantic,the root mean square(RMS) and the correlation between the estimated SAT and the observations are about 0.911 and0.99,respectively.The RMS and the correlation of RH are about 3.73%and 0.65,respectively.Compared with the multiple regression mediod,the ANN methodology is more powerful in building nonlinear relations in this research.Thus the global monthly average SAT and RH are retrieved from the fixed ANN network from July 1987 to May 2004.In general the annual average SAT shows the increasing trend in recent 18 years.The abnormality of SAT is decomposed with the empirical orthogonal function(EOF).The leading three EOFs could explain 84%of the total variation.EOF1(76.1%) presents the seasonal change of the SAT abnormality.EOF2(4.6%) is mainly related with ENSO.EOF3(3.3%) shows some new interesting phenomena appearing in the three main currents in Pacific,Atlantic and Indian Ocean.     

Signals of Antarctic Circum-polar Wave over the Southern Indian Ocean as recorded in an Antarctica ice core

Oxygen stable isotopic and ionic records, covering a period of 1745--1996, are recovered in DT001 ice core drilled in Princess Elizabeth Land, East Antarctica.Using empirical orthogonal function (EOF) analysis of the annually resolved glaciochemical time series, we find the first EOF (EOFI) represents sea-salt aerosols and is the proxy of sea level pressure (SLP) over a quasi-stationary low in the Southern Indian Ocean (SIO). δ^18O represents the sea surface temperature (SST) of the same ocean area. In the past two decades, four climatic waves as represented by SLP and SST proxies are found in the DT001 ice core, which in coincident with four Antarctic Circum-polar Waves (ACW) as revealed by NCEP/NCAR reanalysis. The phase difference between SST and SLP in the ice core is also coincident with that in ACW. Both ice-core record and reanalysis suggestthat there were no signals of ACW during 1958--1980, none during the overall recording period between 1745--1996, as there is no regular phase difference between SST and SLP.The ACW signal after early 1980s is probably attributable to the climate shift occurring over Antarctic Peninsula-Drake Passage region.     

冬季全球大气季节内振荡的特征分析

利用欧洲中期数值天气预报中心的ERA-40逐日再分析资料,计算得到350 K等熵面上45年冬季气候平均位势高度场,再利用Butterworth滤波器得到等熵面上位势高度30～60 d低频波.应用经验正交分解(EOF)对冬季350 K等熵面上的低频位势高度场进行时空分析,结果表明:在第1主分量场上,空间分布特征最明显的是南极涛动(AAO)、北极涛动(AO)、北美-太平洋涛动(PNA)以及经向偶极型低频变化.这种空间分布形式说明在350 K等熵面上南北半球间通过太平洋地区的经向低频波列传播,使得AAO与AO相互影响,相互作用.第2主分量场上,空间分布特征则表现出全球经向和纬向上的低频波列特征,以及南北半球在大西洋地区的相互作用.将EOF分解得到的前2个主分量场的时间系数投影到1957—2002年冬季的时间序列中,发现冬季全球大气低频振荡在20世纪70年代末80年代初发生了明显的年代际突变,并在80年代末以后逐渐加强.说明在80年代末以后冬季南北半球的低频变化相互作用有所加强,也说明太平洋,大西洋上的经向传播特征更为明显.     

全球对流层顶温度场演变的气候学特征分析

 利用经验正交函数分解(EOF)方法对57 a(1948~2004年)NCEP/NCAR全球对流层顶月平均温度场进行分析,并讨论了57 a的主要特征向量空间分布及其对应的时间系数的演变,结果分析表明:第1模态的时空分布特征能够较好地反映对流层顶温度场结构的分布状况,且具有明显的季节变化;南北半球的温度场的空间分布结构不太一致,南半球纬向分布较为平稳,而北半球经向和纬向活动都比较强,且有明显的温度槽脊结构;南北半球的极地对流层顶温度结构在不同的季节有不同的变化趋势;南北半球热带对流层的第1模态温度场全年具有整体一致型分布;温度场各个季节的时间系数变化具有明显的多时间尺度特征.     

Preliminary results of a new global ocean reanalysis

Using a new global ocean reanalysis of the second generation Global Ocean Data Assimilation System of the Beijing Climate Center(BCC_GODAS2.0) spanning the period 1990-2009,we firstly quantify the accuracy of BCC_GODAS2.0 in representing the temperature and salinity by comparing with OISST and SODA data.The results show that the assimilation system may effectively improve the estimations of temperature and salinity by assimilating all kinds of observations,especially in the equatorial eastern Pacific.Moreover,the root mean square errors of monthly temperature and salinity are respectively reduced by 0.53℃ and 0.28 psu,compared with the model control simulation results.Then,the applicability of this ocean reanalysis for sea surface temperature(SST) anomaly variability in the tropical Pacific is evaluated with the observational HadISST data.The NINO3 index of the new reanalysis shows a good agreement with that of HadISST,with a correlation of 93.6%.Variations in SST from BCC_GODAS2.0 are similar to those obtained from HadISST data along the equator,showing the major large zonal-scale features such as the strong magnitude of seasonal cycle.The amplitude of SST anomaly standard deviation in the equatorial eastern Pacific is also closer to observations(HadISST) than NCEP GODAS does.Besides,the first two leading empirical orthogonal function(EOF) modes of the monthly SST anomalies over the tropical Pacific region are explored.The EOF1 pattern of BCC_GODAS2.0 captures a traditional El Ni o pattern,which improves magnitudes of the positive SST anomaly in the cold tongue of the eastern Pacific.The EOF2 pattern exhibits a El Ni o Modoki pattern.Comparatively,the EOF2 pattern of BCC_GODAS2.0 extends more strongly toward the subtropics.It also overcomes the problem that negative loadings are confined in the narrow equatorial eastern Pacific.Consequently,the magnitude and spatial distribution of the leading EOF patterns of BCC_GODAS2.0 are well consistent with those of HadISST.