Asymmetric surface roughness measurements and meniscus modeling of polysilicon surface micromachined flaps

Polycrystalline silicon (polysilicon) films are primary structural materials for microelectromechanical systems (MEMS). Due to relatively high compliance, large surface-to-volume ratio, and small separation distances, micromachined polysilicon structures are susceptible to surface forces which can result in adhesive failures. Since these forces depend on surface properties especially surface roughness, three types of microhinged flaps were fabricated to characterize their roughness and adhesive meniscus properties. The flaps enabled access to both the top and bottom surfaces of the structural polysilicon layers. Roughness measurements using an atomic force microscope revealed that MEMS surfaces primarily exhibit non-Gaussian surface height distributions, and for the release procedures studied, the bottom surface of the structural layers was significantly smoother and prone to higher adhesion compared to the top surface. A non-symmetric surface roughness model using the Pearson system of frequency curves was coupled with a capillary meniscus adhesion model to analyze the effects of surface roughness parameters (root-mean-square, skewness, and kurtosis), relative humidity, and surface contact angle on the interfacial adhesion energy. Using the measured roughness properties of the flaps, four different surface pairs were simulated and compared to investigate their effects on capillary adhesion. It was found that since the base polysilicon layer (poly0) was rougher than the base silicon nitride and the structural layer on poly0 was also rougher than that on silicon nitride, depositing MEMS devices on poly0 layer rather than directly on silicon nitride will reduce the adhesion energy.     

Zigzag machining surface roughness modelling using evolutionary approach

Milling is one of the common machining methods that cannot be abandoned especially for machining of metallic materials. The cutters with appropriate cutting parameters remove material from the workpiece. Surface roughness has the major influence on both obtaining dimensional accuracy and quality of the product. A number of cutter path strategies are employed to obtain the required surface quality. Zigzag machining is one of the mostly appealing cutting processes. Modeling of surface roughness with traditional methods often results in inadequate solutions and can be very costly in terms of the efforts and the time spent. In this research Genetic Programming (GP) has employed to predict a surface roughness model based on the experimental data. The model has produced an accuracy of 86.43%. In order to compare GP performance, Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) techniques were utilized. It was seen that the surface roughness model produced by GP not only outperforms but also enables to produce more explicit models than of the other techniques. The effective parameters can easily be investigated based on the appearances in the model and they can be used in prediction of surface roughness in zigzag machining process.     

Effect of surface roughness,wavelength, illumination,and viewing zenith angles on soil surface BRDF using an imaging BRDF approach

Compared to non-imaging instruments, imaging spectrometers (ISs) can provide detailed information to investigate the influence of scene components on the bidirectional reflectance distribution function (BRDF) of a mixed target. The research reported in this article investigated soil surface reflectance changes as a function of scene components (i.e. illuminated pixels and shaded pixels), illumination and viewing zenith angles, and wavelength. Image-based BRDF data of both rough and smooth soil surfaces were acquired in a laboratory setting at three different illumination zenith angles and at four different viewing zenith angles over the full 360° azimuth range, at an interval of 20°, using a Specim V10E IS (Specim, Spectral Imaging Ltd., Oulu, Finland) mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5). The BRDF of the smooth soil surface was dominated by illuminated pixels, whereas the shaded pixels were a larger component of the BRDF of the rough soil surface. As the illumination zenith angle was changed from 60° to 45° and then to 30°, the shadowing effect decreased, regardless of the soil surface. Soil surface reflectance was generally higher at the backscattering view zenith angles and decreased continuously to forward scattering view zenith angles in the light principal plane, regardless of the wavelength, due to the Specim V10E IS seeing more illuminated pixels in the backscattering angles than in the forward scattering angles. Higher soil surface reflectance was observed at higher illumination and viewing zenith angle combinations. For both soil surface roughness categories, the BRDF exhibited a greater range of values in the near-infrared than at the visible wavelengths. This research enhances our understanding of soil BRDF for various soil roughness and illumination conditions.     

High relative humidity measurements using gelatin coated long-period grating sensors

A long-period grating (LPG) coated with gelatin was developed as a high relative humidity (RH) sensor. The resonance dip or coupling strength of the LPG spectrum varies with RH. Experimental investigations on the sensor yield a sensitivity of 0.833%RH/dB with an accuracy of ±0.25%RH, and a resolution of ±0.00833%RH. The LPG RH sensor also offers repeatability, hysteresis and stability errors of less than ±0.877, ±0.203 and ±0.04%RH, respectively. In addition to the characterization of the LPG RH sensor, further studies were conducted to determine the effect of grating periodicities on the sensitivity of the sensor. Results show that higher order cladding modes from smaller grating periods enable the sensor to achieve higher sensitivity to humidity. This method is proposed to be more cost effective as compared to more complex spectroscopic methods based on wavelength detection. This sensor can also help to solve problems in measuring high humidity with existing relative humidity measurement systems.     

Effect of tool vibrations on surface roughness during lathe dry turning process

Choice of optimized cutting parameters is very important to control the required surface quality. In fact, the difference between the real and theoretical surface roughness can be attributed to the influence of physical and dynamic phenomena such as: built-up edge, friction of cut surface against tool point and vibrations. The focus of this study is the collection and analysis of surface roughness and tool vibration data generated by lathe dry turning of mild carbon steel samples at different levels of speed, feed, depth of cut, tool nose radius, tool length and work piece length. A full factorial experimental design (288 experiments ) that allows to consider the three-level interactions between the independant variables has been conducted. Vibration analysis has revealed that the dynamic force, related to the chip-thickness variation acting on the tool, is related to the amplitude of tool vibration at resonance and to the variation of the tool's natural frequency while cutting. The analogy of the effect of cutting parameters between tool dynamic forces and surface roughness is also investigated. The results show that second order interactions between cutting speed and tool nose radius, along with third-order interaction between feed rate, cutting speed and depth of cut are the factors with the greatest influence on surface roughness and tool dynamic forces in this type of operation and parameter levels studied. The analysis of variance revealed that the best surface roughness condition is achieved at a low feed rate (less than 0.35 mnt/rev), a large tool nose radius (1.59 mm) and a high cutting speed (265 m/min and above). The results also show that the depth of cut has not a significant effect on surface roughness, except when operating within the built-up edge range. It is shown that a correlation between surface roughness and tool dynamic force exist only when operating in the built-up edge range. In these cases, built-u edge formation deteriorates surface roughness and increases dynamic forces acting on the tool. The effect of built-up edge formation on surface roughness can be minimized by increasing depth of cut and increasing tool vibration. Key words:design of experiments, lathe dry turning operation, full factorial design, surface roughness, measurements, cutting parameters, tool vibrations.     

Minimal roughness property of the Delaunay triangulation

A set of scattered data in the plane consists of function values measured on a set of data points in R². A surface model of this set may be obtained by triangulating the set of data points and constructing the Piecewise Linear Interpolating Surface (PLIS) to the given function values. The PLIS is combined of planar triangular facets with vertices at the data points. The roughness measure of a PLIS is the L² norm squared of the gradient of the piecewise linear surface, integrated over the triangulated region and obviously depends on the specific triangulation. In this paper we prove that the Delaunay triangulation of the data points minimizes the roughness measure of a PLIS, for any fixed set of function values. This Theorem connects for the first time, as far as we know, the geometry of the Delaunay triangulation with the properties of the PLIS defined over it.     

表面粗糙度光学测量方法研究进展

表面粗糙度对工件的性能有很大的影响,由于机械、电子及光学工业的飞速发展,对精密机械加工表面的质量及结构小型化的要求日益提高,使得表面粗糙度测量显现出越来越重要的地位。采用光学方法测量表面粗糙度具有非接触、无损伤、测量精度高等优点。介绍了用光散射法、像散法、散斑法、光干涉法、光学触针法测量表面粗糙度的原理及研究进展,讨论了上述方法各自的优缺点,对表面粗糙度测量的发展方向进行了预测。     

用VBA在AutoCAD中添加标注表面粗糙度专用命令的方法

介绍了应用Ｖｉｓｕａｌ Ｂａｓｉｃ Ａｐｐｌｉｃａｔｉｏｎ语言在ＡｕｔｏＣＡＤ中添加标注表面粗糙度专用命令的方法,给出了具体的编程步骤。     

Surface exploration using laparoscopic surgical instruments: The perception of surface roughness

During laparoscopic surgery video images are used to guide the movements of the hand and instruments, and objects in the operating field often obscure these images. Thus, surgeons often rely heavily on tactile information (sense of touch) to help guide their movements. It is important to understand how tactile perception is affected when using laparoscopic instruments, since many surgical judgements are based on how a tissue ‘feels’ to the surgeon, particularly in situations where visual inputs are degraded. Twelve naïve participants used either their index finger or a laparoscopic instrument to explore sandpaper surfaces of various grits (60, 100, 150 and 220). These movements were generated with either vision or no vision. Participants were asked to estimate the roughness of the surfaces they explored. The normal and tangential forces of either the finger or instrument on the sandpaper surfaces were measured. Results showed that participants were able to judge the roughness of the sandpaper surfaces when using both the finger and the instrument. However, post hoc comparisons showed that perceptual judgements of surface texture were altered in the no vision condition compared to the vision condition. This was also the case when using the instrument, compared to the judgements provided when exploring with the finger. This highlights the importance of the completeness of the video images during laparoscopic surgery. More normal and tangential force was used when exploring the surfaces with the finger as opposed to the instrument. This was probably an attempt to increase the contact area of the fingertip to maximize tactile input. With the instrument, texture was probably sensed through vibrations of the instrument in the hand. Applications of the findings lie in the field of laparoscopic surgery simulation techniques and tactile perception.     

Surface exploration using laparoscopic surgical instruments: the perception of surface roughness

During laparoscopic surgery video images are used to guide the movements of the hand and instruments, and objects in the operating field often obscure these images. Thus, surgeons often rely heavily on tactile information (sense of touch) to help guide their movements. It is important to understand how tactile perception is affected when using laparoscopic instruments, since many surgical judgements are based on how a tissue 'feels' to the surgeon, particularly in situations where visual inputs are degraded. Twelve na?ve participants used either their index finger or a laparoscopic instrument to explore sandpaper surfaces of various grits (60, 100, 150 and 220). These movements were generated with either vision or no vision. Participants were asked to estimate the roughness of the surfaces they explored. The normal and tangential forces of either the finger or instrument on the sandpaper surfaces were measured. Results showed that participants were able to judge the roughness of the sandpaper surfaces when using both the finger and the instrument. However, post hoc comparisons showed that perceptual judgements of surface texture were altered in the no vision condition compared to the vision condition. This was also the case when using the instrument, compared to the judgements provided when exploring with the finger. This highlights the importance of the completeness of the video images during laparoscopic surgery. More normal and tangential force was used when exploring the surfaces with the finger as opposed to the instrument. This was probably an attempt to increase the contact area of the fingertip to maximize tactile input. With the instrument, texture was probably sensed through vibrations of the instrument in the hand. Applications of the findings lie in the field of laparoscopic surgery simulation techniques and tactile perception.     

Least-squares linear estimators using measurements transmitted by different sensors with packet dropouts

The least-squares linear estimation problem (including prediction, filtering and fixed-point smoothing) from measurements transmitted by different sensors subject to random packet dropouts is addressed. For each sensor, a different Bernoulli sequence is used to model the packet dropout process. Under the assumption that the signal evolution model is unknown, recursive estimation algorithms are derived by an innovation approach, requiring only information about the covariances of the processes involved in the observation equation, as well as the knowledge of the dropout probabilities at each sensor.     

Estimation of cutting forces and surface roughness for hard turning using neural networks

Metal cutting mechanics is quite complicated and it is very difficult to develop a comprehensive model which involves all cutting parameters affecting machining variables. In this study, machining variables such as cutting forces and surface roughness are measured during turning at different cutting parameters such as approaching angle, speed, feed and depth of cut. The data obtained by experimentation is analyzed and used to construct model using neural networks. The model obtained is then tested with the experimental data and results are indicated.     

Interrogation of surface plasmon resonance sensors using temporally stretched ultrashort optical pulses

We propose a novel technique that has the potential to realize interrogation of surface plasmon resonance (SPR) sensors at very high speed. In contrast to the incoherent light source used in the traditional wavelength interrogation schemes, a broadband coherent laser generating short optical pulses at a high repetition rate is used along with a highly dispersive optical element. The dispersion causes strong broadening of the optical pulses, and the temporal pulse shape could exactly resemble the spectral distribution of the pulses due to the induced linear chirp. Therefore, by measuring the changes in the pulse shapes with a single high-speed photodetector, the spectral response of the SPR sensor can be obtained for each input pulse and the interrogation speed could reach the repetition rate of the pulse train. This could enable SPR measurements at the speed of tens of MHz or higher, which is well beyond that of other current SPR interrogation techniques. We experimentally demonstrate that, by measuring the variations in the pulse shapes of the chirped pulses, sensitive SPR measurements can be made. Implementing this scheme with a femtosecond fiber laser and other fiber optic components also show the potential to realize more compact and integrated SPR systems.     

Influence of soil surface roughness on soil bidirectional reflectance

The non-Lambertian behaviour of soil surfaces depends on its roughness at micro-scale and larger scales, as well as on the incident angle of the direct solar beam on the surface. A geometrical model, taking into account the diffuse as well as the specular component of energy leaving soil surfaces in the visible and near-infrared, is used in the paper to describe the influence of soil surface roughness, caused by soil aggregates or soil clods, on the soil bidirectional reflectance distribution. A rough soil surface in the model is simulated by equalsized opaque spheroids lying on a horizontal surface. The model was tested in outdoor conditions on artificially formed soil surfaces made of two spectrally different soil materials: a mineral loam, and a loam with high organic matter content. The spectral data were measured by a field radiometer in the three SPOT (HRV) bands. The model predicts that at specific illumination conditions, soils surfaces with the highest roughness, expressed by the minimum distances between soil aggregates, can show lower variation of reflectance in the view zenith angle function than soil surfaces of a lower roughness.     

Effects of molecular level surface roughness on electroosmotic flow

Electroosmotic flow is widely used to transport and mix fluids in micro- and nanofluidic systems. Though essentially all surfaces exhibit certain degrees of roughness, the effects of surface roughness on electroosmotic flow is not well-understood. In this paper, we investigate how the electrical double layer and electroosmotic flow are affected by molecular level surface roughness by using molecular dynamics simulations. The simulation results indicate that, when the thickness of the electrical double layer is comparable to the height of surface roughness, presence of sub-nanometer deep concave regions on a rough surface can alter the electrical double layer near the surface, and reduce the electroosmotic flow significantly.     

基于室温离子液体的肼蒸气传感器

利用电化学循环伏安法研究了水合肼蒸气在室温离子液体BmimPF6中的电化学行为,测得其在0.94V处可以被电化学氧化,且该氧化峰电流受肼在BmimPF6中的扩散所控制并推算出其氧化反应电子数为0.8.在此基础上,构建了以BmimPF6为电解质的准固态肼蒸气电化学气体传感器.该传感器对浓度范围为1.1～25.4μmol/L的水合肼蒸气呈线性响应.同时,该传感器也表现出了良好的稳定性与重复性.     

微电极生物化学传感器的表面修饰研究

以电流型微电极葡萄糖传感器为检测平台,对四种不同的电极表面修饰方法:氧化、铂化、聚合吡咯以及铂化并聚合吡咯进行了理论分析及实验验证。其中,铂化并聚合吡咯方法之前未见过报道。实验结果表明:铂化并聚合吡咯是一种很有效的电极表面修饰方法。     

Characterisation of surface roughness and sediment texture of intertidal flats using ERS SAR imagery

High resolution, synoptic information on sediment characteristics of intertidal flats is required for coastal management, e.g., for habitat mapping and dredging studies. This study aims to derive such information from space-borne Synthetic Aperture Radar (SAR). Estimates of the backscattering coefficient were extracted from ERS-1 SAR and ERS-2 SAR PRI imagery of four intertidal flats in the Westerschelde (southwest Netherlands). They were related to field measurements of surface roughness, moisture conditions and sediment texture. The field data were also used as input to the backscattering model IEM. The data and model predictions show that on the intertidal flats, backscattering depends mainly on vertical surface roughness, with rougher surfaces associated with more backscattering. Surface roughness, mainly determined by the ripple structure of the bed, decreased with the amount of mud in the sediment. This resulted in a significant negative correlation between backscattering and mud content, and a significant positive correlation between backscattering and median grain-size of the sediment. Sediment texture was also correlated with the volumetric moisture content of the sediment, with finer sediments being associated with higher moisture contents. However, moisture contents were generally high, and therefore the backscatter signal was not sensitive to differences in moisture content. The relationships allowed the development of regression models for the prediction of surface characteristics from SAR imagery, from which maps of, for example, mud content, have been derived.     

Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data

The Integral Equation Model (IEM) is the most widely-used, physically based radar backscatter model for sparsely vegetated landscapes. In general, IEM quantifies the magnitude of backscattering as a function of moisture content and surface roughness, which are unknown, and the known radar configurations. Estimating surface roughness or soil moisture by solving the IEM with two unknowns is a classic example of under-determination and is at the core of the problems associated with the use of radar imagery coupled with IEM-like models. This study offers a solution strategy to this problem by the use of multi-angle radar images, and thus provides estimates of roughness and soil moisture without the use of ancillary field data. Results showed that radar images can provide estimates of surface soil moisture at the watershed scale with good accuracy. Results at the field scale were less accurate, likely due to the influence of image speckle. Results also showed that subsurface roughness caused by rock fragments in the study sites caused error in conventional applications of IEM based on field measurements, but was minimized by using the multi-angle approach.     

Analysis and optimization of surface roughness in the ball burnishing process using response surface methodology and desirabilty function

In the present study, an optimization strategy based on desirability function approach (DFA) together with response surface methodology (RSM) has been used to optimize ball burnishing process of 7178 aluminium alloy. A quadratic regression model was developed to predict surface roughness using RSM with rotatable central composite design (CCD). In the development of predictive models, burnishing force, number of passes, feed rate and burnishing speed were considered as model variables. The results indicated that burnishing force and number of passes were the significant factors on the surface roughness. The predicted surface roughness values and the subsequent verification experiments under the optimal conditions were confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface roughness was calculated as 2.82%.