\\n\\n
Dr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\\n\\nSeeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\\n\\nOver these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\\n\\nWe are excited about the present, and we look forward to sharing many more successes in the future.
\\n\\nThank you all for being part of the journey. 5,000 times thank you!
\\n\\nNow with 5,000 titles available Open Access, which one will you read next?
\\n\\nRead, share and download for free: https://www.intechopen.com/books
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Preparation of Space Experiments edited by international leading expert Dr. Vladimir Pletser, Director of Space Training Operations at Blue Abyss is the 5,000th Open Access book published by IntechOpen and our milestone publication!
\n\n"This book presents some of the current trends in space microgravity research. The eleven chapters introduce various facets of space research in physical sciences, human physiology and technology developed using the microgravity environment not only to improve our fundamental understanding in these domains but also to adapt this new knowledge for application on earth." says the editor. Listen what else Dr. Pletser has to say...
\n\n\n\nDr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\n\nSeeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\n\nOver these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\n\nWe are excited about the present, and we look forward to sharing many more successes in the future.
\n\nThank you all for being part of the journey. 5,000 times thank you!
\n\nNow with 5,000 titles available Open Access, which one will you read next?
\n\nRead, share and download for free: https://www.intechopen.com/books
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-partners-with-ehs-for-digital-advertising-representation-20210416",title:"IntechOpen Partners with EHS for Digital Advertising Representation"},{slug:"intechopen-signs-new-contract-with-cepiec-china-for-distribution-of-open-access-books-20210319",title:"IntechOpen Signs New Contract with CEPIEC, China for Distribution of Open Access Books"},{slug:"150-million-downloads-and-counting-20210316",title:"150 Million Downloads and Counting"},{slug:"intechopen-secures-indefinite-content-preservation-with-clockss-20210309",title:"IntechOpen Secures Indefinite Content Preservation with CLOCKSS"},{slug:"intechopen-expands-to-all-global-amazon-channels-with-full-catalog-of-books-20210308",title:"IntechOpen Expands to All Global Amazon Channels with Full Catalog of Books"},{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"}]},book:{item:{type:"book",id:"58",leadTitle:null,fullTitle:"Holography, Research and Technologies",title:"Holography",subtitle:"Research and Technologies",reviewType:"peer-reviewed",abstract:"Holography has recently become a field of much interest because of the many new applications implemented by various holographic techniques. This book is a collection of 22 excellent chapters written by various experts, and it covers various aspects of holography. The chapters of the book are organized in six sections, starting with theory, continuing with materials, techniques, applications as well as digital algorithms, and finally ending with non-optical holograms. The book contains recent outputs from researches belonging to different research groups worldwide, providing a rich diversity of approaches to the topic of holography.",isbn:null,printIsbn:"978-953-307-227-2",pdfIsbn:"978-953-51-4515-8",doi:"10.5772/591",price:139,priceEur:155,priceUsd:179,slug:"holography-research-and-technologies",numberOfPages:468,isOpenForSubmission:!1,isInWos:1,hash:null,bookSignature:"Joseph Rosen",publishedDate:"February 28th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/58.jpg",numberOfDownloads:60626,numberOfWosCitations:94,numberOfCrossrefCitations:28,numberOfDimensionsCitations:71,hasAltmetrics:0,numberOfTotalCitations:193,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 11th 2010",dateEndSecondStepPublish:"June 8th 2010",dateEndThirdStepPublish:"September 13th 2010",dateEndFourthStepPublish:"November 12th 2010",dateEndFifthStepPublish:"January 26th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7,8",editedByType:"Edited by",kuFlag:!1,editors:[{id:"16544",title:"Prof.",name:"Joseph",middleName:null,surname:"Rosen",slug:"joseph-rosen",fullName:"Joseph Rosen",profilePictureURL:"https://mts.intechopen.com/storage/users/16544/images/1608_n.jpg",biography:"Joseph Rosen is a professor at the Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Israel. He received his BSc, MSc, and DSc degrees in electrical engineering from the Technion - Israel Institute of Technology in 1984, 1987, and 1992, respectively. \nHe is a fellow of the Optical Society of America. His research interests include holography, image processing, optical microscopy, diffractive optics, interferometry, biomedical optics, pattern recognition, optical computing, and statistical optics. 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Even newborn babies know how to utilize their sense of touch to interact with their surrounding environment. Many of the typical tasks around us require touch which without it even a very basic task would be challenging to accomplish. Just imagine how difficult it can be to grab any object if you cannot feel its shape and weight or determine the amount of force you need to apply to hold it. Touch is very important to human being, and we rely on our touch sense more than we think we do [1].
Modern technologies in this digital era added new interactive agents around us which require our touch input. Touchscreen consumer electronics such as smartphones and tablet devices are among them. They are a versatile device that displays visual content and takes touch input simultaneously. More specifically, smartphones are an inevitable part of our daily life. Users spend a significant amount of time interacting with the digital contents on their mobile phones. So, equipping such devices with functionality to provide some sort of touch feedback was inevitable and seemed to be a natural course of technological development. However, despite technological advances, these devices lack the ability to provide programmed tactile feedback, which can be essential for more natural and intuitive interaction. At best, they provide some simple monotonic vibration patterns in response to the user’s touch input. This is neither appealing nor satisfactory given the expectations users have from such modern devices [1].
With the introduction of variable friction displays, this limitation has been addressed by technologies collectively called
The rest of the chapter is organized as following. In the next section, a brief overview of the fundamental operation of the electrovibration technology is given. Next, the literature has been reviewed for the studies, and applications have been built upon. In the final section, conclusions and future remarks are provided.
The earliest known observation of electrical attraction between the human skin and a charged surface was made by Gray in 1875 [3, 4]. Forgotten for a while, a similar phenomenon was rediscovered later and called
Interaction between the finger, the isolating part of the skin (stratum corneum), and the conductive plate.
The induced friction is perceived by the mechanoreceptors in the fingertip skin. In general, mechanoreceptors are responsible to perceive sensations such as pressure, vibration, and texture, and there are four types of them in hairless skin, Merkel discs, Meissner’s corpuscles, Ruffini corpuscles, and Pacinian corpuscles, as shown in Figure 2. They are categorized into fast-adapting (Pacinian and Meissner) and slow-adapting (Merkel and Ruffini) receptors. The former ones detect small and fast changes such as surface roughness, while the latter ones detect static perception such as pressure. It has been shown that the electrovibration is primarily perceived through the Pacinian channel [9].
Touch mechanoreceptors in the hairless (glabrous) skin of the human fingertip [
Nevertheless, when a potential is applied, the electrostatic force,
This electrostatic stimulation was introduced into a tactile display by Strong et al. [10]. They developed the first electrostatic display using a stimulator array consisting of a large number of small electrodes. They reported that the intensity of the perceived vibration was mainly due to the peak applied voltage. Later, a polyimide-on-silicon electrostatic fingertip tactile display was fabricated with 49 electrodes arranged in a square array [11]. They conducted experiments to assess the intensity and spatial resolution of the tactile percepts. In a following study, its application to present various spatial tactile patterns such as line, triangle, square, and circle to the visually impaired users is investigated [12]. In all these works, the dryness of fingertip is emphasized to be the key factor maintaining the percept, reporting that a small amount of sweat could cause the percept to fade or disappear. The direct method has difficulty in stable stimulation because of finger perspiration. Indirect stimulation was suggested as a solution. Yamamoto et al. built a display with a thin slider film between electrostatic stator electrodes and fingertip for presenting surface roughness [13]. In another work, multiple contact pads are used for multi-finger interaction with a large electrostatic display [14]. This was mainly to address finger perspiration during direct interaction and also to create larger force by applying higher voltage. This also enables multi-finger interaction.
Electrovibration regained attention in 2010 after a collaboration between Disney Research and Carnegie Mellon University yielded to a system for rendering 3D textures onto an electrovibration touchscreen. Called TeslaTouch [15], the developed system could deliver variable friction to user’s sliding finger by modifying amplitude and frequency of the excitation signal. Implemented on top of a tablet computer, a user could perceive real-time tactile feedback correspond to the displayed digital content. Different tactile effects could be generated mimicking surface geometry such as bumps and ridges or surface texture such as frictional patterns to enhance user experience interacting with the objects in the scene.
The core of TeslaTouch is a transparent capacitive touch panel (Microtouch, 3 M, USA) driven by a high-voltage signal to modulate friction on a sliding finger. The panel is made of a thick glass layer on the bottom, a transparent electrode (indium tin oxide; ITO) in the middle, and a thin insulator layer on the top. In the usual setup, the electrode is excited by high AC voltage, and the human body is grounded electrically. The big advantage of TeslaTouch is that the capacitive panel is a commercial off-the-shelf product which requires only an additional high-voltage amplifier for proper operation. The same panel has been used in electrovibration displays by other groups [16, 17, 18, 19, 20, 21, 22]. Radivojevic et al. at Nokia introduced a flexible and bendable version by replacing indium tin oxide (ITO) with graphene [23].
While TeslaTouch was mainly designed for desktop applications, a company in Finland, Senseg, developed Tixel [24], a transparent electrostatic film targeting handheld devices. The touch panel is made of transparent electrodes on a glass plate coated with an insulating layer. By applying a periodic voltage to the electrodes via connections used for sensing a finger’s position on the screen, the researchers were able to effectively induce a charge in a finger dragged along the surface. By changing the amplitude and frequency of the applied voltage, the surface can be made to feel as though it is bumpy, rough, sticky, or vibrating. The major difference is the specially designed control circuit that produces the sensations.
The tactile experience comes from two components: a coating layered atop touchscreen and electronics that modulate the electrostatic field and produce textures. Senseg’s Tixel is the means by which Senseg’s technology transmits electrovibration stimulus. It is an ultrathin durable coating on the touch interface that outputs tactile effects. The hardware inside a device modulates the signal for varied intensities of tactile sensation and types of tactile effects and provides accurate spatial resolution over the entire Tixel surface area.
Senseg later introduced a short-lived commercial product called Feelscreen, a 7″ Android tablet overlaid with Tixel, into the market between 2014 and 2016. Feelscreen has been used in several projects such as 3D shape rendering [25], texture gradients [26], and visual and haptic latency [27]. At the moment, Tanvas [28], a startup company in the USA, is commercializing similar products but on a larger 10″ tablet with some improvements such as generating stronger friction forces and not requiring an external power supply.
Some other researchers developed their own electrovibration display not using the 3 M capacitive touch panel. Pyo et al. built a tactile display that provides both electrovibration and mechanical vibration on a large surface [29]. They fabricated an insulated ITO electrode on top of an electrostatic parallel plate actuator, both operating based on the electrostatic principle. A nontransparent electrostatic friction display was also developed in [30, 31] using an aluminum plate covered with a thin plastic insulator film.
These displays do not support multi-touch or localized friction modulation, and all fingers in contact with the surface experience the same sensation. This issue was addressed by several prototypes presenting local stimulation. For example, a display panel was developed with multiple horizontal and vertical ITO electrodes in a grid enabling localized stimulation at the region where the vertical and horizontal electrodes cross each other [32]. In [14], a multi-finger electrostatic display was developed consisting of a transparent electrode and multiple contact pads on which users place their fingers. Applying different voltages to the pads and electrically grounding the transparent electrode induce different frictional stimuli to the multiple fingers.
The relationship between input signal and output friction in electrostatic friction displays is not clearly understood, and a number of studies have shown great interest in defining such relationship. Researchers have worked on this topic either by measuring friction forces using a tribometer [16, 31] or by estimating perceived intensities in psychophysical experiments [17, 33]. For instance, Meyer et al. [16] developed a tribometer to make precise measurements of finger friction and confirmed the expected square law of frictional force to driving voltage. They also showed a linear mapping between friction and normal force, confirming the Coulombic model of dry friction. Conducting a six-value effect strength subjective index rating, Wijekoon et al. showed a significant correlation (0.8) between signal amplitude and perceived intensity but no correlation between frequency and perceived intensity [33]. In [17], participants assigned a number between 0 and 100 to the subjective friction intensity. A linear fit in log-log scale was observed in the normalized results relating applied voltage amplitude to perceived friction force intensity.
As well as fabrication, various properties of electrovibration have been investigated too. The polarity effect of the actuation signal is studied in [34], reporting that tactile sensation is more sensitive to negative than positive pulses. Meyer et al. showed an expected square law dependence of frictional force, measured by a tribometer, on actuation voltage [16]. A similar approach is taken by Vezzoli et al. to develop a model for electrovibration effect considering frequency dependence [31]. Kim et al. proposed a current control method to provide more uniform perceived intensity of electrovibration [19]. In another work and by comparing two actuation signals, it is reported that square waves are more detectable than sine waves at frequencies lower than 60 Hz while they are same at higher frequencies [35]. Testing three methods, amplitude modulation, adding DC offset, and their combination, Kang et al. investigated low-voltage operation of electrovibration display [22]. They showed all methods increased dynamic friction force, while only DC offset increased static friction force.
To perceive the friction force generated on an electrovibration display, one requires to drag or slide their finger over the surface. While this type of interaction is natural and intuitive for most of handheld touchscreen devices, however, it limits the range of applications can benefit from this functionality. It is worth to recall that the two key attributes of real and simulated objects are shape (surface geometry) and texture (simply surface frictional properties) [36]. Addressing these two attributes separately, in this section we review the relevant work in the literature.
Rendering 3D objects on a flat surface, either using a haptic interface or a variable friction display, has not been addressed much in the literature. In an early work regarding haptic perception of curvature, Gordon and Morison showed that the gradient is an effective stimulus for curvature perception and humans rely on local curvature when perceiving surface [37]. Later, Minsky et al. demonstrated that tangential force alone can be sufficient for rendering surface texture assuming it is made of little bumps [38]. They introduced
Based on the
This study was foundational to the gradient-based algorithm of Kim et al. [17] for rendering 3D features on a touchscreen using electrovibration. In their work, a psychophysical perceptual model, subjectively relating the perceived friction to the applied voltage, was formulated. The model was a straight line in log–log scale, fitted over average users’ ratings of the perceived friction intensity in a scale of 0–100. The model then utilized to modulate friction and render three lateral force profiles: height, slope, and rectangular. They compared users’ preference for three types of force profile for a visual bump displayed on the screen. Results indicated that the slope profile best matched the visual bump. They generalized this finding to a 2D gradient-based rendering algorithm for 3D features and applied the algorithm to many user interface examples.
In Ref. [25], the authors presented an effective rendering method for improving the recognition of 3D features rendered on a touchscreen using an electrostatic friction display. First, a formative user study is carried out using a basic gradient-based algorithm adapted from [41] in order to assess users’ ability of recognizing primitive 3D shapes based on lateral force feedback provided by an electrostatic tablet and a force-feedback interface. Experimental results demonstrated that users are not able to associate electrovibration patterns with geometric shapes in an absolute manner without contextual information. However, when such guidance was given, participants achieved moderate recognition. Then, they extended the basic algorithm to support general 3D mesh objects. The generalized algorithm computes the frictional rendering force by estimating the gradient at the touch point and also emphasizes sharp edges on the surface by rendering perceptually salient friction effects. Lastly, they conducted a summative user study to evaluate the effectiveness of their proposed shape rendering algorithm in reducing the visual uncertainty in 3D shape perception. They found that when frictional feedback was provided, the correct recognition performance was notably increased in comparison with when only visual rendering was presented.
Compared to the problem of rendering 3D geometries on a flat electrostatic display, rendering surface textures seems more feasible and intuitive on such displays. As mentioned earlier, depending on the actuation signal, an electrovibration display generates different textural patterns. A simple illustration is given in Figure 3. On one hand, a sinusoid actuation signal creates a smooth bumpiness underneath of sliding finger. On the other hand, a square wave signal generates a rough and edgy feeling. A more complicated texture can be re-created using a proper complex signal.
How the input actuation signal makes the perceived friction different.
Therefore, the type of input signal, its waveform, its amplitude, and its frequency components play a significant role on the generated textural patterns. Hence looking at the problem from a systematic standpoint, knowing the input–output relationship of the display is vital for this problem. As stated earlier, several efforts have been made modeling the display and drawing a relationship between the input actuation voltage and the output friction force. However, aside from the fact that the output force is somehow proportional to the squared input voltage, there exists no reliable general model covering all type of input signals across a wide range of frequencies. This suggests an alternative method, the so called data-driven texture rendering. Data-driven, or measurement-based, haptic rendering is a general approach that uses recordings from real objects to generate realistic haptic feedback in virtual environments [42, 43]. It can be either parametric- and physics-based, to optimize parameters of a predefined model, or nonparametric and generic. It is usually accompanied by a generic interpolation scheme to handle the data sets not being measured. It provides a unified framework to capture and display a diverse range of physical phenomena, while not requiring simulations of complex contact dynamics. This data-driven approach enables researchers to bypass the complex step of hand tuning a dynamic simulation of the target interaction to try to match a haptic sensation. Instead, the goal of the modeling process is to capture the output response of the system (e.g., force and acceleration) given some set of user inputs (e.g., position, velocity, and force). Such methods shift the focus from reproducing the physics of the interaction to reproducing the real sensations felt by the user, and thus they have been largely successful at realistic haptic simulation [44].
While the problem of data-driven haptic texture rendering has been fairly addressed in the literature using conventional or customized haptic interfaces [45, 46, 47, 48, 49, 50, 51], little work has been done on variable friction displays and particularly using electrovibration attraction.
An electrostatic friction display creates clearly perceptible stimuli when the surface is laterally scanned, but not when the finger is stationary. This fundamental limitation has confined the application of electrostatic friction displays mostly to texture rendering. In the only relevant work [18], Ilkhani et al. proposed a data-driven texture rendering method by recording accelerations from three real materials and playing them back on an electrovibration display. Their automated data collection is done under single constraint condition (contact force 0.35 N and scanning velocity 0.74 m/s) using a servomotor controlled by an Arduino Uno. They conducted a user study to compare the perceived surface roughness generated with their data-driven signals and with that of square wave signals. The frequency of each square wave is set based on the main frequency of the corresponding acceleration. Using a visual indicator, they made the user to keep a constant scanning velocity, but not equal to the data collection velocity and presumably very slower than that. In addition, there is no mention of contact force status during experimentation. Nevertheless, they reported higher percentage of similarity between data-driven textures and real ones than square wave patterns. In their extended work [52], they applied the same approach on the data from Penn Haptic Texture Toolkit [53] and performed MDS analysis to create a perceptual space and to extract underlying dimensions of the textures. Their results showed roughness and stickiness as the primary dimensions of texture perception.
In ref. [54], a data-driven neural network for realistic texture rendering on an electrovibration display is proposed. First, a motorized linear tribometer is developed to collect lateral frictional forces from the textured surfaces under various scanning velocities and normal forces. Then an inverse dynamics model of the display is created to describe its output-input relationship using nonlinear autoregressive with external input (NARX) neural networks. Forces resulting from applying a full-band pseudorandom binary signal (PRBS) to the display are used to train each network under the given experimental condition. A comparison between the real and virtual forces in frequency domain shows promising results and reveals the capabilities and limitations of the proposed technique.
In this chapter, we have introduced the concept behind electrostatic friction displays (also called electrovibration displays) and their potential applications for shape and texture rendering. The potential uses for the technique are exciting. Electrovibration could make interactive textbooks more engaging on tablets, allowing students to explore the three-dimensional features of an object directly on each page. Software for iOS or Android could be augmented with unique haptic feedback for button presses and swipe gestures. Games could incorporate electrovibration to add a new layer of interactivity to touch controls. With some smart design, it could really improve the functionality of touchscreens used in other fields, as well. For instance, the use of touchscreens in automobiles to navigate the map or control the music playback persuades drivers to avert their eyes from the road. Possibly, with an appropriate design, the same control functionalities could be delivered using a variable touch-based feedback without the need to take our eyes off the road. Given the commonness of capacitive touchscreens, the addition of richer tactile feedback through electrovibration promises to enhance almost all of our interactions with digital contents.
While the technique has a lot of potential, the form factor remains a primary barrier to adoption. Implementing the alternating voltage results in a much bulkier device than with an ordinary capacitive touchscreen. As the technology sees more frequent use, however, there may be technological developments that allow more smartphone and tablet manufacturers to feature electrovibration without sacrificing the compactness of their designs.
I would like to thank Prof. Seungmoon Choi for his extensive personal and professional guidance teaching me a great deal about both scientific research and life in general. As my teacher and mentor, he has taught me more than I could ever give him credit for here. He has shown me, by his example, what a good scientist (and person) should be. I also would like to thank Dr. Jin Ryung Kim for his constant support and encouragement.
I certify that I have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.
Microfluidics is a broad terminology covering various disciplines and scopes while focusing on life science, biochemical and chemical applications. It applies to the devices that process fluids at a dimension below the millimeter scale, and the maximum fluidic volume is within milliliters. Current applications are more related to fluids from microliters to nanoliters in volumes [1, 2]. Two devices in the late 1970s marked the birth of microfluidics. IBM first reported the inkjet printer heads [3] in 1977, and now millions of such units have been shipped worldwide, enabling color printing into every corner of human life. Another device is the micro gas chromatography made on a 5 cm silicon wafer by Stanford University in 1979 [4]. This
The majority of applications of the current microfluidics are for liquid handling other than the gaseous materials. DNA/Gene analysis and point of care disease diagnosis are extensively studied with microfluidic devices [12, 13, 14, 15]. The microfluidic devices can integrate both active and passive elements inside the fluidic channels, enabling the polymerase chain reaction devices that help the DNA amplification. The detailed analyses of the DNA samples become possible. Such information is critical for identifying diseases and understanding the origins of the abnormality to the search for possible recovery routes. The other important and advantageous benefits of these microfluidic-based diagnostic devices are fast processing time with small sample volume. These features are combined with today’s communication infrastructure, making the remote diagnosis a fascinating scenario. However, current devices are still less sophisticated to acquire the necessary data for the desired tasks. Most of the devices available are based on colorimetric or optical images or limited electrical signals. These data are similar to the analog ones in the electronic age. Additional
Microfluidics advancement, on the other hand, greatly relies on the device fabrication technologies of micromachining. The earlier simple passive microfluidic chips having the only microchannels are no longer the mainstream but components of the current devices. A sophisticated microfluidic chip would have both passive structures and active components, which is a challenge for the micromachining process technologies that do not have standard protocols. The multi-discipline features further complicate the availability of process tooling. Fortunately, microfluidics’ growth is parallel with the significant advancement in the MEMS and LSI/VLSI IC industry. With ever-improving micromachining device fabrication technologies, the microfluidics once was only viable on a 2″ wafer, and now 8″ and even 12″ wafers are being routinely produced. Many more foundries are available with specialized alternative substrates of glasses, plastics, polymers, and even papers. In recent years, 3D printing, precision micro-injection, laser processing, hot embossing [20, 21, 22, 23], and other alternative tools also greatly enriched the variety of microfluidic devices. The progress significantly solves the issues for chemical and bio-compatibility and, in some cases, for commercialization, but the cost to fabricate a desired microfluidic chip is still far from satisfactory. Moreover, the interactions among the device components and the fluids are also likely and sometimes are mandatory, adding additional requirements for better materials and fabrication technologies. Several key components, including microfluidic channels, microvalves, micropumps, needles, mixers, and sensors, are considered the necessary ones for the desired microfluidic chip or system. These relatively complicated components and the substrate make the process compatibility with the electronics a dilemma. Therefore, package, interface, and system design will become critical for the device’s final footprint, manufacturability, and successful deployment.
The inkjet printer head that handles the ink droplets remains an outstanding example of a successful microfluidic application. The envisioned microfluidic future in life science and others are still missing a bridge, mostly from the ease of reach and cost-effectiveness [9, 24, 25, 26]. The research data for the current microfluidic market have excluded the inkjet applications, addressing only the diagnostic devices and pharmaceutical and life science tools [27]. Nevertheless, by comparing the market reports from the same market research firm issued a decade ago to the current data, one could find that even the most optimal old forecast has nothing to beat the real growth. On the other hand, today’s multi-billion dollar market and the double digital growth predicted by various market research firms are more from the companies making the system level products but not the direct values of the key components. These data for the value-added systems are, in a sense, could deceit the current research focus on components. While the system level products enable various applications, the lack of a miniaturized, standalone, performance dramatizing, and cost-effective device would not maintain the expected or envisioned phenomenal growth. In this chapter, standalone flow sensor products for microfluidics will be discussed, including the technologies, standards, factors that will impact the performance, integrations, and manufacturability or scalability.
Microfluidic studies have covered a huge spectrum of processes. For this chapter’s limited space, only continuous flow sensing technologies are discussed with applicable pulsed flow features. Droplet flow, nanofluidic flow, microfluidic manipulation or handling, and biological and chemical-related flow phenomena will not be addressed.
Microfluidic sensors are critical components for a complete system. Many research works on sensors have been dedicated to the biomedical and chemical sensing development based on electrochemical, optical, mass, or magnetic sensing principles. Electrochemical sensors are mostly studied and often composed of several electrodes that are easy to fabricate together with the microchannels. This limited integration with a simple configuration allows a fast response with reasonably good sensitivity and enables multiple reagents on a single microfluidic chip. The electrode embedded inside a microfluidic channel can also be used for cell counting and estimate the flow volume. With the assistance of a miniaturized LED, pH measurement could be achieved as well [28, 29, 30, 31]. However, many of the proposed biosensors or chemical sensors are very specific, and most are research-orientated, as being determined by the catalytic or affinity properties of the biological recognition agent in a particular study and the sensor itself requires a sophisticated electronic system for readout or analysis. The standalone or large scale commercial applications are yet to emerge.
Flow meters using traditional thermal capillary and Coriolis measurement are commercially available for micro flow measurement before the microfluidics being intensively studied. Researches on microfluidic flow sensing approaches are for miniaturized, cost-effective, and integrable products. In this scope, both flow and pressure sensors have been extensively studied [28]. In some cases, the differential pressure sensor can be used for flow measurement. Flow measurement is one of the most important factors in microfluidic handling for data analysis and precise system control. Without the knowledge of the fluid quantity in the process, analytical results would not be easy to establish the needed and convincing statistics. The conventional flow sensors might be the first commercially available standalone sensing products for microfluidics. The technologies are still limited, and their package formality is bulky and far off the cost target for the desired microfluidic system. Many studies proposed integrating flow sensors into the microfluidic system. However, there are still many factors that impact data acquisition. The existing sensor products on the market also have some unsolved reliability issues in applications. The commercialization route to a well-performed and cost-effective sensor is yet to be demonstrated.
The available flow sensors applied to microfluidics are classified as thermal and non-thermal sensors [1]. Thermal flow sensors have been applied to small flow measurement for both gas and liquid before the microfluidic concept emerged. Therefore thermal flow sensors are mostly studied and applied in microfluidic applications, and products with various thermal sensing principles are commercially available. Coriolis microfluidic sensor is a non-thermal sensor, and it has an even higher cost. Other “non-thermal” flow sensors are mostly at the research stages. Before the form factor, cost, and reliability issues can be solved, large scale applications are still not possible.
For the traditional flow sensors, the metrology characteristics will hardly enable a self-calibration. Therefore, a primary standard or a reference defined by an international norm governs the manufacture of a flow sensing product with specific sensing technology. The same should then apply to microfluidics. Demanding to establish an international standard for microfluidics has long been proposed [32, 33]. Still, only in recent years, an international microfluidic association has been established, and an international standard (ISO) working committee has been organized with a serial of workshops [34]. It has been proposed that the new ISO standard for the microfluidic shall be having four sub-standards, including
Several efforts to establish a primary standard or a traceable reference system for flow metrology in microfluidics applications have been made in the past years [35, 36, 37]. The widely adapted primary standards are the gravimetric and volumetric principle. The comparison of such standards among different European national metrology institutes indicated an uncertainty (
For almost all flowrate ranges in microfluidics, the Reynold numbers are within 1000, indicating that the flow of interests is within the laminar flow regime. Therefore in a desired large dynamic range, the flow profile would not be the same at the different flowrates, which adds complexity to maintain the measurement accuracy. Meanwhile, the flow channels are small in micrometer dimensions. The interfaces between fluid and channel wall become pronounced, which differ from those described for laminar flow by Moody Diagram in the classic fluid dynamics. Besides, cavitation would play a critical role, and dissolution will also contribute to metrology. These are among the new challenges for the on-going metrology standards for microfluidics.
The thermal mass flow measurement using calorimetric capillary sensors has been used to measure a very low flow to nanoliter per minute for quite a long time [40]. The sensors are composed of thin metal wires winded outside the wall of a tiny tube of a micrometer in diameter. The tube is usually made of thermally conductive materials such as stainless steel or fused silica. These sensors normally require a higher power to ensure the heat transfer resulting in a small dynamic measurement range and a low accuracy towards the low measurement end. The required manufacture process makes these sensors very costly without being able to be volume produced. Integration of such a sensor into a microfluidic system would be unlikely. In the following discussions, only micromachined sensors will be addressed. The micromachined sensors are mostly made on silicon or glass substrate. A microheater and plural numbers of sensing elements are deposited on a membrane structure, and the air or gas-filled cavity below the membrane provides the desired thermal isolation. The tiny sensing elements enable a fast response time. The membrane is frequently made with silicon nitride or silicon nitride and oxide combination. The sensing elements can be metals with a large temperature coefficient such as platinum, nickel, tungsten, or in the case for the process compatibility, doped polycrystalline silicon is used instead. The micromachined thermal flow sensors’ structure has no moving parts, and the surface can be treated with various passivation and post-process coating for better reliability. The micromachining process for the flow sensors is well established today. Most MEMS foundries have the necessary equipment for manufacturing such sensors, which allows a very favorable cost and makes it possible for high volume applications. The first micromachined thermal flow sensor made for microfluid is used in micro gas chromatography [4]. It is for gaseous flow and not a standalone product and only manufactured in a minimal quantity as the OEM product. The commercially available micromachined thermal microfluidic flow sensors for liquid were incepted in the last decade. These commercial products utilize different thermal sensing principles [41, 42, 43] that cover the three major technologies with thermal calorimetry, anemometry, and thermal time-of-flight approaches. There are some research activities on other thermal flow sensing designs, such as thermal capacitive utilizing the temperature dependence of dielectric constants, [44] and temperature dependence of the PN-junction in a diode [45]. The measurement scheme of flowrate with these alternative thermal sensing designs could also be classified into the above three thermal sensing principles. Figure 1 is the graphic illustration of these three measurement principles for the typical micromachined thermal flow sensors on a silicon substrate.
Graphic illustration of the micromachined thermal flow sensors (on silicon) with the flow sensing principles: (a) calorimetry; (b) anemometry and (c) thermal time-of-flight.
The majority of the current micromachined commercial thermal flow sensors are utilizing the calorimetric principle. Most successful applications are for gaseous fluids, of which the automotive airflow sensors for fuel control are the dominant application. The structure showed in Figure 1(a) is a typical one for a micromachined calorimetric mass flow sensor on which a microheater is placed at the center of the membrane. Two temperature sensors are made symmetrically at the up and downstream of the microheater. These two temperature sensors can be simple resistors of identical resistance values or identical thermal-piles. There are a variety of approaches to realize data acquisition. The commonly used ones are either to keep the microheater at a constant heating power or to maintain a constant temperature from the up and downstream sensor and then measure the heat transfer or temperature differences between the measurements of the up and downstream sensors as the flowing fluid will take away the heat from the microheater resulting in a heat redistribution. By calibration, such heat transfer can be correlated to the mass flowrate of the fluids. In this approach, the measurement is susceptible to low flowrate. As its nomenclature indicates, the measurement is dependent on the fluidic thermal properties of thermal capacitance and thermal conductivity. The thermal sensing using the resistor-based microheater and resistor sensing has the intrinsic temperature effects associated with the environmental conditions, which need to be compensated for better accuracy. For this purpose, another sensor placed on the substrate (the yellow element shown in Figure 1) is used to gauge the environmental temperature and correct the resistance value due to environmental temperature variations. The detailed theoretical interpretation and governing physics can be found in the literature as well as the international standard [1, 46].
The major challenge of applying the micromachined thermal sensor to meter microfluidic is the package. For the gaseous sensors, the membrane often has openings that balance the surface’s fluidic pressure against the membrane deformation. The change of the membrane position will greatly impact the measurement as the sensor position will be significantly altered with membrane flatness changes. However, for microfluidic measurement, the opening will be detrimental once the liquid-filled up the cavity underneath the membrane. Therefore, the commercially available approach [41] for the package is to have the sensor placed outside the channel with the sensor’s surface close to the outer channel wall. Therefore, the channel will need to be thin enough and have good thermal conductivity for heat transfer effectiveness. One of the selections of the channel is a fused silica tube. As the membrane that supports the sensing element is typical with a thickness of 1 micrometer, attach the think tube to the sensor is a very tedious process with a high cost. In addition, compared to the applications for gaseous fluids, the thermal wall of the fused silica also reduces the sensitivity of the sensor, leading to a significantly smaller measurement dynamic range (<50: 1), which is certainly not desired for microfluidic applications. The commercially available calorimetric microfluidic sensors offer a typic <40:1 dynamic range with the lowest detection flowrate of 7.5 nL/min and the best accuracy of ±5% of reading at the full scale. There are also concerns about the constant thermal power at the channel’s specific area during the measurement in practical applications. This will be discussed later in detail.
The first micromachined thermal flow sensor on silicon is made with the anemometric flow sensing principle [47]. Thermal anemometry is also known as energy dissipative sensing, and its measurement scheme is relatively simple, as shown in Figure 1(b). Only one sensing element is placed downstream. Alternatively, the sensing element can also be placed upstream, as the measurement of the fluidic flowrate is only from the microheater (a sensing element). The temperature sensor is used as a fluid temperature reference. Therefore, instead of measuring the fluidic flow-induced changes of the temperature profile at the centralized microheater with calorimetry, the anemometry measures the heat loss due to the forced convection. In this case, with the supporting control circuitry, adjusting the microheater power will allow the measurement to be much easier for higher flowrates. Simultaneously, the sensitivity at low flow will be lower compared to the sensing principle of calorimetry. Another character of the anemometry is that its correlation with the fluidic thermal properties has a larger nonlinear effect resulting in the difficulties to apply a constant fluidic conversion factor for correction of the flowrate data when the measured fluid has different thermal properties from those of the calibration fluid. For the same reason, the temperature compensation scheme for the anemometry is more complicated than that for the calorimetry.
One commercially available anemometric microfluidic flow sensor, per the structure described in the company’s webpage, [43] also takes the package approach similar to the earlier mentioned one of the calorimetric microfluidic sensors. The sensor is placed at the outer wall of a thermally conductive fine quartz glass tube by machining the tube surface into a smooth flat. Instead of a single micromachined sensing chip, two chips are used. A special glue was applied to attach the chip to the quartz tube’s flat surface, forming a close contact for the required heat transfer. The heater chip and temperature chip are separated at a certain distance forming the configuration of an anemometer. The heat transfer needed for the measurement provided by the sensor is achieved via thermal diffusion. These package approaches are also similar to the traditional capillary thermal mass flow sensors, where the hot wires are winded onto the surface of a special stainless tube. However, the micromachined sensor will have a much lower heating temperature than those by the capillary sensor. Because of the heat diffusion, control the heat for the low flowrate measurement would be very challenging, resulting in a small dynamic range and large measurement errors (full-scale error rate) towards the low detection limit. The current offered anemometric microfluidic flow meter has a guaranteed dynamic range of 50:1 with the lowest detectable flowrate of 100 μL/min and the best accuracy of ±5% of reading.
Both the calorimetric and anemometric flow sensors require a calibration of the real fluid for the desired precision or metrological accuracy, as the fluidic properties will have a nonlinear response in the full dynamic range. The limited dynamic range and the accuracy would not be desirable for the precision requirements for many microfluidic applications such as drug infusion. Also, these flow sensing products could only provide mass flowrate measurements. The microfluidic applications would appreciate additional fluidic information such as fluidic concentration, physical or even chemical properties of the fluids at the same time. To this end, thermal time-of-flight sensing technology offers much of the competitive advantages. The thermal time-of-flight sensing concept can be traced back to the late 1940s [48] and has been an interest in many subsequent research works [49, 50, 51]. The thermal time-of-flight sensing measures the heat transfer transient time as well as the responses at each sensing element. Several sensing elements can be placed downstream of the microheater. Consequently, this approach can measure additional parameters other than the flowrates [52]. The sensor works with a thermal pulse or modulated thermal wave signals. Compared to calorimetry or anemometry, the transient time-domain data are much more immutable to the background interferences. Despite the advantages, a commercially available thermal time-of-flight flow meter is not seen until the past decade [42]. One reason could be that the microheater must possess a mass as small as possible for the needed thermal response to enable the measurement scheme. In the traditional approach, such a tiny wire is extremely vulnerable for reliability in actual applications. On the other hand, pure time-of-flight will only measure the flow velocity. In contrast, the other parameters require advanced and complicated electronics that are not readily accessible until recent years. Nevertheless, the sensor build and package limitation will still lead to a non-pure time-of-flight, and calibration will be required to remove those effects. On the other hand, these effects can also be used to provide additional fluidic information. For the microfluidic applications, the microheater is driven with a modulated microheater, the constant heating spot in the flow channel is therefore eliminated. The sensor outputs flow velocity as well as fluidic mass flowrate and the additional data of the fluidic properties, making the thermal time-of-flight technology an ideal approach for the desired microfluidic flow measurement applications.
Figure 2 shows a typical structure of a micromachined thermal time-of-flight sensor chip [53]. The micromachined process has a wide spectrum of materials selection to allow the sensor with excellent thermal isolation while not sacrificing reliability. This is particularly important for the thermal time-of-flight sensing that requires a super-fast thermal response. The blue materials showed in Figure 2(b) can be silicon or glass substrate. The gray colored block will be for thermal isolation. For example, a 10 ~ 15 μm parylene conformal layer will provide the properties of the good material of stiffness and robustness for the application. The green-colored materials need to have good thermal conductivity while excellent surface passivation for reliability. Ideal materials include multi-layered silicon nitride or silicon carbide. Underneath the microheater and sensing elements, a cavity will enhance the thermal performance of the sensor chip. The brown-colored elements are for microheater and sensing elements. One sensing element is placed directly on the substrate to measure the environmental temperature that provides the compensation of the microheater’s temperature performance and control. In the photo shown in Figure 2(a), the central element has another sensing element at the proximity of the microheater, which is used to fine-tune the microheater temperature or power with those other physical properties such as thermal conductivity can be precisely acquired.
Example of a micromachined thermal time-of-flight sensing chip: (a) optical photo of the chip, top view; (b) cross-section schematic.
The heat transfer in the thermal time-of-flight configuration is measured by the temperature
Where
Therefore, if the sensor only has a microheater and a sensing element pair, the measurement will still be dependent on the flow medium properties. The microheater and the sensing elements all have the fluidic dependent response that needs to be removed for the complicated fluids. Simple calibration with the conventional fluid can be applied for the fluid measurement without losing the metrology accuracy. A micro-machining process’ advantages allow placing multiple sensing elements on the same chip without adding any cost that makes it possible to have the measurement independent of the fluidic properties. The thermal time-of-flight will not be a simple flow velocity measurement. The measured changes in the amplitude are directly proportional to the heat transfer between the microheater and the sensing elements that will provide the mass flowrate similar to the calorimetric or anemometric approach per the data acquisition process. The time-domain data yield additional information, which allows the acquisition of additional fluidic thermal dynamic properties such as thermal conductivity and specific heat. In the microfluidic flow measurement, the liquid is generally non-compressible. The pressure effects of compressibility can be considered secondary. Compared to the gaseous fluids, liquid has a much large heat capacitance making the sensing element resistance-related temperature effects less pronounced. And most importantly, with the multiple sensing elements on a single chip, the measurement dynamic range can be substantially extended. A practical 7500:1 dynamic range can be achieved with two or three pairs of sensing elements.
Coriolis mass flow sensing principle has been well documented, and the first commercial product was introduced to the market in 1977 by Micro Motion. It is a true mass flow sensing technology with very high precision by utilizing an exciting tube which fluid is flowing through, and the tube oscillates artificially. The changes of the tube oscillation in time and space are a direct measure of the mass flow. One advantage of the Coriolis sensing approach is that the fluid density can be simultaneously determined from the oscillation frequency of the measuring tube. But it also requires a minimum density of fluid such that the resolution of the oscillation can be registered. It also suffers a high-pressure loss and a smaller dynamic range. The high cost of the measuring tube manufacture sparked the attempt with micromachining, and the first research paper was published in 1997 [55]. With the micromachining process, the MEMS Coriolis mass flow sensor can be well applied for microfluidic flow measurements. The commercially available Coriolis meters sensors via micromachining either consists of a silicon microtube via silicon wafer fuse bonding and an integrated temperature sensor [56] or a silicon-rich silicon nitride tube coupled with a strain gauge readout [57, 58]. The micromachined Coriolis sensor using silicon nitride tube has a thin tube wall of about 1.2 μm and is much lighter than the silicon tube. Hence, the light-weighted tube would have a smaller mass than the fluid it measures that simplify the package, and leads to the possibility to measure the fluids at ambient pressure. The demonstrated Coriolis sensor could measure liquid mass flow, density, and temperature (if a temperature sensor is integrated) simultaneously. Another advantage for the MEMS Coriolis mass flow sensor is that it usually operates at a much higher resonant frequency with substantially less vibratory influences from the environments than those for the traditional Coriolis mass flow technology.
Like the MEMS thermal mass flow sensors, the micro Coriolis mass flow sensor also requires clean fluid. Even fine particles can damage or clog the sensor, considering the measuring tube’s tiny channel. Besides, the sensor will not function well in liquid with high viscosities and liquid with chemical reactions. The high-speed liquid flow may also alter the performance of the sensor unless bypass configuration is applied. The superior true mass flow accuracy of a Coriolis sensor is overshadowed by its footprint, complication in the package, and cost in the manufacturing process that diminishes high volume and/or disposable applications, which would be a necessity in some microfluidic applications for cross-contamination prevention. The fluidic property independence measurement characteristics also limit its measurements only for flowrate and density. Other fluidic property measurements will require integrating additional sensing elements, further enlarging the sensor footprint, indicating an even higher cost for the final product manufacture. Therefore, although the micromachined Coriolis sensor’s demonstration has been over two decades, the applications are still very limited.
Flow sensors are likely the ones that can be made with the most versatile technologies and are vastly selectable to the applications. More than twenty different physical measurement principles are commercially available on the market for flow metrology. However, for microfluidics, the options are limited. Other than the commercially available thermal mass flow sensors and Coriolis flow sensors, micromachining advancement offers opportunities for many studies with a wide spectrum of technologies applied for microfluidic flow sensing. But commercialization of many of those is still in question. Some selected researches micromachined flow sensing technologies are discussed below.
In addition to micromachined thermal and Coriolis sensors, micromachined ultrasonic sensors are also commercially available. Ultrasonic flow sensing is one of the well-documented technology for flow metrology with high accuracy. By measuring the time differences of the ultrasonic signals propagating in the opposite direction of a fluidic medium, the flow speed can be accurately measured. Therefore, it has the advantage of a pure velocity measurement independent of the fluidic properties. As a sound propagation, it will not require direct contact with the fluids that it measures, or it is non-invasive, which is very attractive for microfluidic related medical applications. However, it will normally require dual transducers placed in opposite directions or at a certain angle with respect to a reflector. This prevents the reduction in footprint and cost. For the microfluidic applications, its signals reduce significantly at the low flow speed, and it is also very sensitive to the fluids where cavitation or dissolution may exist. The current commercially available ultrasonic flow meters for microfluidics have about a 50:1 dynamic range and a detection limit of 300 μL/min [59]. Some research indicated that the ultrasonic transducer could be integrated into the microfluidic channel, but the capability for flow metrology is yet to be demonstrated [60].
Acoustic device applications in microfluidics are mostly for fluid handling, and surface acoustic wave (SAW) sensing and actuation is another approach that can be integrated into the microfluidic channels [61]. Some efforts were also made to measure the flowrate with the SAW devices. It has been reported that a micromachined interdigital transducer (IDT) could direct the fluidic droplets via the excited acoustic streaming that is fast and material independent [62]. In another study, [63] a SAW sensor with dual symmetrical IDTs made on a 30 mm by 30 mm square quartz crystal substrate was used to measure the flowrate in a designed channel by recording the delay times and the corresponding frequencies. A close to a linear correlation between the phase shift from the delay time and flowrate was established. The SAW sensors can be independent of the fluidic properties; however, they require a much larger footprint, and temperature compensation is also complicated compared to thermal sensing approaches.
Measurement of flowrate with differential pressure is one of the oldest flow sensing technologies. Micromachined differential pressure sensors have been well established and are widely available on the market at a very low cost. Most sensors are made on a silicon nitride membrane or diaphragm with the piezoresistive sensing elements at the edges of the membrane or with a capacitance measuring principle for the low differential pressures [64, 65]. The advantages of a differential pressure sensor for flow measurement are lower power consumption and relatively easy installation with fewer effects on the flow conditioning. They are also independent of the fluidic properties. The microfluidic flow regime is purely laminar, and the pressure loss is linear with the flow velocity. However, limited by its sensitivity, the measurement dynamic range of a differential pressure sensor is normally small. In particular, for microfluidic applications, the pressure drop at a tiny distance may not even generate enough sensitivity for the measurement. The dependence of the microfluid’s pressure loss on the dynamic viscosity also requires a temperature sensor at the proximity for the needed compensation. Other phenomena such as cavitation or multi-phase flow will have a big impact on the measurement of the pressure and hence the accuracy of the deduced flowrate.
Flow measurement with drag force is an alternative pressure-related flow sensing approach. Due to the size restriction, such a sensor does not favor being placed inside the microfluidic channel. However, in an ideally integrated microfluidic system, there will be valves and other actuators. The drag force-sensing approach could be combined with the actuation parts in the system. A typical drag force sensor is to utilize a cantilever or a diaphragm [66]. The mechanical deflection can be read out with an optical microscope or photodiode. Another approach to measuring the deflection is to utilize the piezoresistive or piezoelectric elements embedded at the positions where maximal deformation could occur at the designed cantilever or diaphragm. To increase the measurement sensitivity, the Fabry Perot spectrum’s fringe shift was used to measure the cantilever movement correlated flowrate, which, however, complicated the data acquisition and limited the package options [67]. The materials used to make the micro-cantilevers are silicon nitride, SU8, and polydimethylsiloxane (PDMS). An integrated micro-cantilever inside the microfluidic channel via the microfluidic favorable PDMS process achieved a capability of detecting 200 μL/min flowrate but only have a small 5:1 dynamic range [68]. Most of the micro-cantilevers measure microliter per minute flowrate, even though nanoliter per minutes sensitivity was reported, but the required optical readout often makes the fine readings and subsequent digitization a challenge [69]. While piezoresistive or piezoelectric configuration is more preferred as no optical assistance in readout will be needed. On the other hand, as the piezoelectric cannot detect a static flow, piezoresistive is considered a better choice. The cantilever sensors are more sensitive than diaphragm sensors, but there are still concerns for their reliability and repeatability per the moving cantilever. The sensitivity of these sensors also requires meaningful pressure or critical mass to activate the deformation of the cantilever or diaphragm. Such pressure is not necessarily existing in the microfluid subject to measurement.
The non-invasive approach is always preferred in microfluidic applications, for which life science is the major focus. A microwave microfluidic flow sensor is reported [70] to achieve a large dynamic range of 1-300 μL/min with a high resolution of 1 μL/min. The detection of the flowrate with the microwave is via the measurement of a membrane that was a part of a microfluidic channel and on which the fluid is flowing over, causing the deflection of the membrane. Therefore, it could also be a type of differential pressure sensing. The measurement element is the microwave resonator that detects the effective capacitance because of the changes in the deflected thin membrane’s effective permittivity due to the channel pressure changes by the flowing fluid at different flowrates. This configuration is much easier to be packaged with the microfluidic channel, and it is a true noncontact detection that can be miniaturized compared to the optical assisted readout. The microwave flow sensor is consisting of two critical components. One is the microfluidic channel with the membrane that was micromachined with PDMS soft lithography and replica molding. PDMS is a preferred material for microfluidics for its compatibility, and more importantly, it is transparent to microwave with a low loss. The membrane is about 1.5 to 3 mm in diameter and 100 μm in thickness, strong enough to hold the fluidic pressure inside the microfluidic channel. Simultaneously, it is thin enough for the sensitivity of the resonator function needed for the measurements. The second component of the flow sensor is the microwave resonator, designed into an open-ended half-wavelength ring resonator with a microstrip structure on a high-performance microwave substrate made of a 35 μm copper layer on top and bottom surfaces. The resonator operated at a 4 GHz resonant frequency. The fabrication is via the cost-effective conventional printed circuitry board processing. However, the integration with the microchannel made strong application dependence and difficulties in controlling the cost. Also, the metrological performance of this sensor was not well documented.
Optical flow sensing is attractive to the microfluidic application for its non-invasive and high accuracy features. Laboratory flow measurements such as particle image velocimetry, infrared thermal velocimetry, and laser interferometry are reported for microfluidic metrology studies [71, 72, 73, 74]. These optical technologies are all having complicated bulk settings and require the microfluidic channels to be optically transparent. While the miniaturization efforts continue to focus on microfluidics, optofluidics is now a dedicated field for the studies of the combined optics and microfluidics with targeted miniaturized optical integration sensing functions into a single microfluidic chip. In a microscale optical flow sensor report, [75] an optical fiber structure was fabricated in the form of a drag force cantilever to measure the microfluidic flow. A stripped single-mode optical fiber was positioned across a microfluidic channel and aligned with a multi-mode fiber receiver. The microfluidic flow in the perpendicular directions will displace the fiber cantilever tip, causing the light intensity change at the aligned receiver. The reported sensor had achieved a measurement dynamic range over 60:1 and a minimal detection of 7 μL/min. However, the making of the sensor would be quite complicated with the fiber alignment, and direct contact of the flowing fluid with the fiber cantilever is also required. In another report using the optical approach for flow sensing, miniaturized fluorescence sensing is attempted for micro molecular tagging velocimetry in microfluidics [76], but these methods are not cost-effective and yet to reach the small footprint.
In an alternative optical sensing approach, [77] a collimated light beam was employed to excite the surface plasmon resonance at a gold film on top of a polymethyl methacrylate (PMMA) microfluidic channel. The fluidic flow will cause the temperature redistribution inside the microfluidic channel, which alters the refractive index above the metal film. The refractive index is inversely proportional to the temperature. By acquiring and analyzing the image of the excited surface plasmon, the flowrate could be measured. However, since surface plasmon resonance is very sensitive to temperature, and the response is nonlinear, a full functional measurement scheme and affirmation of metrology parameters will need additional efforts.
The impedance flow sensing principle is also a topic in the studies for microfluidics. The electrical impedance flow measurement has the advantage of simplicity. The configuration has fewer requirements for environmental parameter compensation and can be applied to a wide range of fluids. A cascade finger structure of the electrical impedance sensor could help the measurement accuracy of pulsed flow. However, the electrical impedance measurement is strongly dependent on the fluid properties and is only applicable to conductive fluids. In a report [78] of an electrical impedance microfluidic flow sensor, the simple two surface electrodes are embedded inside a microfluidic channel. An alternating current signal was applied across the microfluidic channel. The fluid is equivalent to a diffuse layer capacitance impedance or the parallel capacitance impedance, and the electrode forms the serial capacitance impedance with the fluid. By optimizing the applied voltage frequency, the measured impedance can be well correlated to the flowrate. The reported data achieved a 50 nL/min detection limit and about 10:1 dynamic range.
In another approach, the measurement of the magnetic impedance of a hair microfluidic flow sensor offers the ultra-low-power option [79]. The sensor was made by depositing a giant magnetoimpedance (GMI) layer on top of a glass substrate. A PMMA master pillar mold was then applied to the pre-formed magnetic nanocomposite of permanent magnetic nanowire and PDMS mixture on the GMI layer. The formed flow sensor was placed inside the microfluidic channel. When the fluid flows through the pillars, the flow will force the pillars to bend, resulting in the change of the magnetic field sensed by the GMI layer and output the signals that can be correlated to the flowrate. The results showed a measurement of the water flow speed up to 7.8 mm/sec and a resolution of 15 μm/sec with a typical power of 31.6 μW. The study also indicated that by optimizing the parameters, the power could be further lowered to about 80 nW.
The flow metering at the microfluidic scale is quite different from those in a large pipeline. Many factors that may be trivial in the conventional fluidic dynamics become critical for microfluidic metrology. In this section, some critical factors are discussed.
In the classic fluidic dynamics, the Moody chart indicates that at laminar flow, the friction factor is inversely proportional to Reynolds number where only viscosity of the fluid plays the role and diffusion is normally not in consideration. In the dimension of a microfluidic channel, the surface area relative to the volume is dramatically larger than those in a large pipe. For the flow speed of interests, factors such as surface tension and diffusion are all having their critical contributions to the microfluidic flow metrology. The capillary number then would be much more important than the Reynolds number [80]. Besides, the majority of microfluidic processes are water-based. Water has a molecular size of about 0.27 nanometer, and it is dipolar in nature. Water interaction with the solid surface is inevitable, and such interaction will be pronounced as interaction will involve a significant portion of the total volume of the microfluidics. Most of the solid surfaces at the microscale would be imperfections that are full of defects with dimensions larger than the water molecule. Water viscosity is also very sensitive to temperature in the applicable ranges. These effects will be even more pronounced in the biological fluid case where the electrolyte is often present as the chemical state of the surface would be altered, either by ionization of covalently bound surface groups or by ion adsorption [81]. Hence, to ensure the accuracy in the flow measurement for microfluidics, the interactions between fluid and solid channel surface must be considered, especially for the long term repeatability, reproducibility, or reliability.
The detailed studies on the fluidic handling and flowrates impacted by the fluid and microchannel interactions are not well documented. However, in a few reports on the long-term stability of the commercially available calorimetric flow sensors for microfluidics, it was reported that the measurement accuracy tended to have a time-dependence. The long-term
Cavitation is often known as a detrimental phenomenon in high-speed flows that leads to mechanical damages at the flow path. However, it can also be utilized for industrial processing in classic fluidic dynamics. In microfluidics, cavitation inception is via the diffusion of dissolved gas into the available nuclei. It can occur even at a pure Stokes flow, but the cavitating flow will not normally lead to mechanical defectiveness due to the relatively low energy release, but it can dramatically generate the local flow speed spike. Cavitation has become a growing research topic in microfluidics. It is not only because the cavitation flow is inevitable in many applicable microfluidic flow conditions, but it can also be employed as a tool for microfluidic manipulation such as pumping and mixing via the control of cavitation size alternation. The cavitation can harvest and release energy upon collapse in the microfluidic process. The removal of cavitation can be done with properly designed materials for the microfluidic channels [83, 84, 85, 86].
The cavitation presence will greatly impact the measurement reproducibility or accuracy for any flow sensors regardless of the measurement principles. The calibration setup for a microfluidic meter normally requires a degassing device in serial to the calibration line, and degassing is always performed before the start of calibration [39]. The cavitating flow is in fact a two-phase flow. Therefore when a flow sensor calibrated at a cavitation-free condition is applied to measure a cavitating flow, the measurement deviations will be inevitable. The current tools of the cavitation studies are visualization approaches such as colorimetry or via high-speed camera for which a transparent flow channel will be required to collect the data. However, in practical applications, the channels are often opaque. Therefore, it is of interest to have additional measurement approaches that can alert
Left - Example of the response of a micromachined thermal time-of-flight sensor to air bubbles passing in a DI-water microfluidic channel; and right – shows the same sensor response at 20mL/min flow to the channel conditions: A – as calibrated DI water; B – tested after sensor powered on in a null flow DI water channel for 48 hours; C – After B test and degassing for 15 minutes; D – after C and full scale full (30mL/min) flow for 30 minutes; E – after D, the channel dried with N2 and re-test.
While manipulating the microfluidics inside the designated microchannel, mixing two or more fluids is a common practice. The mixture of the fluids, depending on the physical properties, can be miscible or immiscible. The miscible fluids will result in a fluid with a new
Microfluidic dissolution phenomena impose big challenges in metering the flow for a desired metrological accuracy, either with immiscible or miscible fluids. The dual-phase or multi-phase flow for the immiscible fluids would involve various liquid–liquid, gas–liquid, liquid–gas–liquid, and supercritical fluid flows beyond the capabilities of the conventional flow sensing approaches. Even with the miscible fluids, the microbubbles would likely present in all cases. The changes in the mixture’s density and physical properties will lead to completely different heat and mass transfer, which will significantly deviate the metering values that are always reference to those at the calibration conditions. Optical or image processing would help understand the physical or even chemical process, but it would not help improve the flow measurement accuracy. Therefore, new flow sensing technologies are required for metering these types of microfluidics.
Figure 4 shows the polar plots of a thermal time-of-flight sensor measurement of the deionized water and methanol, respectively, at 3 individual flowrates of 1, 3, and 5 mL/min. The flowrates were set via a precision syringe pump. The sensor’s microheater was modulated with a sine wave, and the phase-shifts at the sensing elements were recorded for the flowrate calibration. The fluidic dependent measurement can be seen for the single sensing element configuration as indicated by the differences in measured polar angles between water and methanol. With the dual-sensing elements, the measurements of the two polar plots are overlapped. Therefore, the water calibrated sensor can be directly applied to measure another fluid with different fluidic properties. For the fluidic mixing process with miscible fluids, this dual thermal time-of-flight sensing approach can provide a more desirable measurement than the other thermal sensing approaches. Moreover, as each sensing element’s data can be individually acquired, the sensor can also output any changes in its measured fluid. The concentration of the dual miscible fluids can be deduced from the thermal properties measured by comparing the data in the registers at the calibration.
Thermal time-of-flight measurement of deionized water and methanol flow rates.
Drug infusion has been in medical practice for over 300 years. Precision control of drug delivery is getting increasing attention in recent years. In a European
Drug infusion example: left – commercial infusion pump (Alaris 8100 ) output at 0.1 mL/hr; and right comparison between the outputs at 20mL/hr by Alaris (red) and a precision syringe pump (blue, KD Scientific Legato 210) measured by a thermal time-of-flight sensor.
Metering the microfluidic flow is critical for many microfluidic applications requiring precise control of the desired microfluidic process or handling. Precision in the flow metering will also improve the performance of the current instrumentation, including the widely applicable drug infusion apparatus, which are nontrivial for the advancement in the medical application and general applications in microfluidics. At the dimensions of interest, current flow sensing technologies are not fully capable of serving the demands. Factors such as fluid and channel interface/interactions, cavitation, and dissolution play critical roles in impacting microfluidic metrology. Additional sensing elements must be integrated with the current flow sensing approaches to compensate, assist, and enhance the flow metrology. In a most recent review, [95] many available technologies can be used to acquire the microfluidic thermodynamic properties such as viscosity, density, diffusion coefficient, solubility, and phase equilibrium directly from the microfluidic channels on a chip. However, many of these technologies are bulky, costly, and not easily integrated with the microfluidic channels. They also often require a transparent microfluidic channel, which would not be readily available in real applications. Although the advancement of micromachining in both the process tooling and application technologies greatly enrich the options for microfluidic flow sensing, a capable device is yet to be demonstrated. The recently developed thermal time-of-flight sensing technologies for microfluidics offer a multiparameter capability and unprecedented dynamic measurement range. The surface acoustic wave flow sensing as a simple yet non-invasive approach is also very promising. Integrating with additional sensing elements and decomposing the acquired information might provide additional viable tools serving to understand, advance, and better control the microfluidic process and handling.
The author appreciates his colleagues at Siargao Ltd., who have been dedicated to the challenges and innovations in the commercialization of microfluidic sensing devices since 2009.
We believe financial barriers should not prevent researchers from publishing their findings. With the need to make scientific research more publicly available and support the benefits of Open Access, more and more institutions and funders are dedicating resources to assist faculty members and researchers cover Open Access Publishing Fees (OAPFs). In addition, IntechOpen provides several further options presented below, all of which are available to researchers, and could secure the financing of your Open Access publication.
",metaTitle:"Waiver Policy",metaDescription:"We feel that financial barriers should never prevent researchers from publishing their research. With the need to make scientific research more publically available and support the benefits of Open Access, more institutions and funders have dedicated funds to assist their faculty members and researchers cover the APCs associated with publishing in Open Access. Below we have outlined several options available to secure financing for your Open Access publication.",metaKeywords:null,canonicalURL:"/page/waiver-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"At IntechOpen, the majority of OAPFs are paid by an Author’s institution or funding agency - Institutions (73%) vs. Authors (23%).
\\n\\nThe first step in obtaining funds for your Open Access publication begins with your institution or library. IntechOpen’s publishing standards align with most institutional funding programs. Our advice is to petition your institution for help in financing your Open Access publication.
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\\n\\nFor Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
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\\n\\nThe application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
\\n\\nDownload Waiver Request Form
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\\n"}]'},components:[{type:"htmlEditorComponent",content:'At IntechOpen, the majority of OAPFs are paid by an Author’s institution or funding agency - Institutions (73%) vs. Authors (23%).
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\n\nHowever, as Open Access becomes a more commonly used publishing option for the dissemination of scientific and scholarly content, in addition to institutions, there are a growing number of funders who allow the use of grants for covering OA publication costs, or have established separate funds for the same purpose.
\n\nPlease consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
\n\nFor Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
\n\nOur mission is to support Authors in publishing their research and making an impact within the scientific community. Currently, 14% of Authors receive full waivers and 6% receive partial waivers.
\n\nWhile providing support and advice to all our international Authors, waiver priority will be given to those Authors who reside in countries that are classified by the World Bank as low-income economies. In this way, we can help ensure that the scientific work being carried out can make an impact within the worldwide scientific community, no matter where an Author might live.
\n\nThe application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
\n\nDownload Waiver Request Form
\n\nFeel free to contact us at oapf@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
\n\nNote: All data represented above was collected by IntechOpen from 2013 to 2017.
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