Academic literature on the topic 'SU8 Sensor Chip'

With the rapid development of today's society, air pollution is becoming one of the hottest topics of humans’ concern. Looking at the daily life, some peoples’ awareness in the dangers of indoor air pollution and household gas safety is not enough, so it may lead to a number of respiratory diseases, or "sub-health" conditions. (Such as influenza, pharyngitis and other diseases) On the other hand, some families, because of a gas leak, has not been timely warning of fires and caused the tragedy. To solve these problems, this work is designed based on low-power microcontroller as the master chip HT32F1765 100LQFP between the various smart sensors and did data exchange with the home environment monitoring system. The HT chip use as the master chip and combined with using Sharp PM2.5 gas sensors, temperature and humidity sensors, gas concentration sensor as gas sensing devices. We use all these sensors as information collection module, to collect the data information of air quality, temperature, humidity and combustible gas concentration in different rooms and different locations. The real-time data acquisition and sensor would be displayed on the touch screen. In addition, the creation of data monitoring hardware devices, as well as match the mobile phone in APP. Our users can log on the APP remotely to view home monitoring information, or to receive alarm information.. Thus, adults can safely work outside, avoiding unnecessary worry.

Colloidal quantum dots (CQDs) are gaining increasing attention for gas sensing applications due to their large surface area and abundant active sites. However, traditional resistor-type gas sensors using CQDs to realize molecule recognition and signal transduction at the same time are associated with the trade-off between sensitivity and conductivity. This limitation has restricted their range of practical applications. In this study, we propose and demonstrate a monolithically integrated field-effect transistor (FET) gas sensor. This novel FET-type gas sensor utilizes the capacitance coupling effect of the CQD sensing film based on a floating gate, and the quantum capacitance plays a role in the capacitance response of the CQD sensing film. By effectively separating the gate sensing film from the two-dimensional electron gas (2DEG) conduction channel, the lead sulfide (PbS) CQD gate-sensitized FET gas sensor offers high sensitivity, a high signal-to-noise ratio, and a wide range, with a real-time response of sub-ppb NO2. This work highlights the potential of quantum dot-sensitized FET gas sensors as a practical solution for integrated gas sensor chip applications using CQDs.

In this paper we show Magnetic Field Imaging (MFI) is the best method for Electric Fault Isolation (EFI) of short failures in 2.5/3D Through Silicon Via (TSV) devices in a true non-destructive way by imaging the current path. To confirm the failing locations and to do Physical Failure Analysis (PFA), a Dual Beam-Plasma FIB (DB-PFIB) system was used for cross sectioning and volume analysis of the TSV structures and high resolution imaging of the identified defects. Magnetic Current Imaging (MCI) is a sub technique of MFI which has been used by the semiconductor industry for more than a decade to find electrical shorts and leakage paths and which has the capability to “look through” all materials typically used in the semiconductor industry, allowing global imaging without the need for physical de-processing [1, 2, 3]. MCI utilizes two types of sensors: a Superconducting Quantum Interference Device (SQUID) sensor for low current and large working distances and a Giant Magneto Resistance (GMR) sensor for sub micron resolution current imaging at wafer/die level [3]. The sample investigated in this work is a triple-layer stack, in which 2 layers of 50 μm thick test chip (Chip 1 and Chip 2 in Figure 1) were assembled on a 200 μm thick bottom chip (Chip 0 in Figure 1). The test chips were manufactured by imec's standard 65 nm CMOS Back End of Line (BEOL) process, 5×50 μm via-middle TSV technology [4], and fine pitch micro bumping process [6]. Further details of the test vehicle and assembly process can be found elsewhere [5]. The sample had a short between daisy chain a1 and a2, which were supposed to be electrically separated. The probe tests that was used for this experiment is shown in Table 1. The signal was injected into the respective daisy chains by probing V+ to V− on the bottom chip. To send a signal between daisy chain a1 and a2 one could probe V− to V− and V+ to V+. The MCI scans were done using the GMR sensor only. The sample was attached to a vacuum chuck and raster scanned. From Fig. 2 one can see that the current enters the top layer (Chip 2) at TSV 18 and goes back down again to Chip 1 at TSV 28. Since the sample clearly has multiple shorts, the short located at TSV pair 23 was chosen for PFA using the PFIB. A short is found between the 2 BEOL layers of Chip 1, causing the current to leak into Chip 2 (Fig. 3).

Cell motility is the brilliant result of cell status and its interaction with close environments. Its detection is now possible, thanks to the synergy of high-resolution camera sensors, time-lapse microscopy devices, and dedicated software tools for video and data analysis. In this scenario, we formulated a novel paradigm in which we considered the individual cells as a sort of sensitive element of a sensor, which exploits the camera as a transducer returning the movement of the cell as an output signal. In this way, cell movement allows us to retrieve information about the chemical composition of the close environment. To optimally exploit this information, in this work, we introduce a new setting, in which a cell trajectory is divided into sub-tracks, each one characterized by a specific motion kind. Hence, we considered all the sub-tracks of the single-cell trajectory as the signals of a virtual array of cell motility-based sensors. The kinematics of each sub-track is quantified and used for a classification task. To investigate the potential of the proposed approach, we have compared the achieved performances with those obtained by using a single-trajectory paradigm with the scope to evaluate the chemotherapy treatment effects on prostate cancer cells. Novel pattern recognition algorithms have been applied to the descriptors extracted at a sub-track level by implementing features, as well as samples selection (a good teacher learning approach) for model construction. The experimental results have put in evidence that the performances are higher when a further cluster majority role has been considered, by emulating a sort of sensor fusion procedure. All of these results highlighted the high strength of the proposed approach, and straightforwardly prefigure its use in lab-on-chip or organ-on-chip applications, where the cell motility analysis can be massively applied using time-lapse microscopy images.

Accurate traceable measurement systems often use laser interferometers for position measurements in one or more dimensions. Since interferometers provide only incremental information, they are often combined with index sensors to provide a stable reference starting point. Straightness measurements are important for machine axis correction and for systems having several degrees of freedom. In this paper, we investigate the accuracy of an optical two-dimensional (2D) index sensor, which can also be used in a straightness measurement system, based on a fiber-coupled, collimated laser beam pointing onto an image sensor. Additionally, the sensor can directly determine a 2D position over a range of a few millimeters. The device is based on a simple and low-cost complementary metal–oxide–semiconductor (CMOS) image sensor chip and provides sub-micrometer accuracy. The system is an interesting alternative to standard techniques and can even be implemented on machines for real-time corrections. This paper presents the developed sensor properties for various applications and introduces a novel error separation method for straightness measurements.

To explore the possibility of achieving rapid and in situ detection of aflatoxin B₁ (AFB₁), a portable biosensing instrument consisting of an impedance detector and a 3D-printed USB-compatible sensor chip was developed.

Waveguides with sub-100 nm thickness offer a promising platform for sensors. We designed and analyzed multimode interference (MMI) devices using these ultrathin platforms for use as biosensors. To verify our design methodology, we compared the measured and simulated spectra of fabricated 220-nm-thick MMI devices. Designs of the MMI biosensors based on the sub-100 nm platforms have been optimized using finite difference time domain simulations. At a length of 4 mm, the 50-nm-thick MMI sensor provides a sensitivity of roughly 420 nm/RIU and with a figure of merit (FOM) definition of sensitivity/full-width-at-half-maximum, the FOM is 133. On the other hand, using a thickness of 70 nm results in a more compact design—only 2.4 mm length was required to achieve a similar FOM, 134, with a sensitivity of 330 nm/RIU. The limits of detection (LOD) were calculated to be 7.1 × 10−6 RIU and 8.6 × 10−6 RIU for the 50 nm and the 70-nm-thick sensor, respectively. The LOD for glucose sensing was calculated to be less than 10 mg dL−1 making it useful for detecting glucose in the diabetic range. The biosensor is also predicted to be able to detect layers of protein, such as biotin-streptavidin as thin as 1 nm. The ultrathin SOI waveguide platform is promising in biosensing applications using this simple MMI structure.

Carbon nanomaterials are increasingly attractive as potential candidates to make new generation of sensors due to their unique nanostructures that grant their promising electrical, chemical, and physical properties. Among the group of carbon materials, carbon nanotube (CNT) is one of the most encouraging materials because of its features of high surface-to-volume ratio and unique electronic structure. These features enable CNTs the potential to become a highly sensitive sensing material. Since our project aims on detecting bio-marks from human breath, of which the concentrations are extremely low, the nature of our sensor R&D becomes extremely challenging. Consequently, using CNTs as the sensing materials ought to be our obvious choice at this stage. This choice of carbonous materials as sensing media is also on the hope to simplify the sensor’s instability problems in our R&D effort because carbon itself is very chemically inert toward many chemicals. This presentation will serve as a report of the preliminary results from a lab experiment setting to detect several human breath related bio-marks. Sensors were chemiresistive typed and constructed through drop casting on interdigitated sensor circuit. Each sensor chip contains 8 sensor pixels, and the test bed can host maximum of 16 sensor chips simultaneously. In other words, our sensor testing chamber can embed up to 128 sensors at the same time. We then performed the sensor testing against several gases. As expected, the application of nanotechnology in using CNTs enabled us to approach high sensitivity towards to several gaseous analytes, ranging from sub-ppb to sub-ppm. Noticed that, the previous study from our lab revealed that the sensitivity of sensors could be promoted by illuminations of UV light.1 It was approved that the detection limit of nitric oxides is about 27 ppm, providing reliable and stable sensitivity. To simplify the sensor fabrication and miniaturization as well as to reduce power consumption of final sensor units, in this work, we employed an external thermal power to improve the reversibility of the sensors. Two external 375W IR bulbs were used as the heating source in this setting. A dimmer and temperature control circuitry were integrated to maintain the intended operating temperatures. Moreover, we employed our test protocols and methods by functionalizing the CNTs with carboxylic group, besides utilizing the pristine CNTs. It was resulted that this sensor array was able to detect various gaseous species, including NH3, Isoprene, acetone, etc., with relatively high sensitivity. The existence of surfactants in the CNT sensing layer lowered the conductivity of sensor pixels by a great magnitude and resulted in much reduced sensors’ sensitivities. Therefore, removing surfactants in the CNT solution was made, which dramatically improved the sensors’ electric conductivities and boosted sensors’ sensitivities. However, CNT solutions with diluted surfactants destabilize the CNTs’ aqueous suspension, and lead to the non-uniform CNTs layers. The sensor pixels fabricated by using this surfactant deficient CNTs resulted in the formation of CNT bundles or clusters. The gathering of CNTs in a non-uniform fashion could dramatically reduce the sensor’s sensitivity because the bundles would short the interdigitated circuit and disable the CNTs’ sensing capability in most other area of the sensor film. We, therefore, increased the amount of surfactant in the CNT solutions. The sensors fabricated with excess amount of surfactant exhibited highly electric resistance or even non-conductance with very low or no sensitivity. A simple washing process was then developed to wash out the surfactant, which partially resolved the non-uniformity problem. The method to completely prevent the CNT bundles from formation in sensor film is in progress. In conclusion, we developed a gas sensor array that can detect various VOCs and certain nitrogen containing gas molecules with an extremely high or reasonably high sensitivities. Through applying pristine, modified CNTs or mixtures of both into sensor fabrication, the sensing properties were enhanced under an external heating source in comparison with illumination of UV light. The best sensitivity of the sensors is achieved by removing the surfactants in the sensing films. The application of external thermal energy to help on sensors’ performance gets approved. The benefit of using thermal energy vs. UV light is also discussed. G. Chen, T. M. Paronyan, E. M. Pigos, and A. R. Harutyunyan, Scientific Reports 2, 343 (2012).