High-throughput screening of encapsulated islets using wide-field lens-free on-chip imaging

Islet microencapsulation is a promising solution to diabetes treatment, but its quality control based on manual microscopic inspection is extremely low-throughput, highly variable and laborious. This study presents a high-throughput islet-encapsulation quality screening system based on lens-free on-chip imaging with a wide field-of-view of 18.15 cm^2, which is more than 100 times larger than that of a lens-based optical microscope, enabling it to image and analyze ~8,000 microcapsules in a single frame. Custom-written image reconstruction and processing software provides the user with clinically important information, such as microcapsule count, size, intactness, and information on whether each capsule contains an islet. This high-throughput and cost-effective platform can be useful for researchers to develop better encapsulation protocols as well as perform quality control prior to transplantation

Experimental study of visual corona under aeronautic pressure conditions using low-cost imaging sensors

Visual corona tests have been broadly applied for identifying the critical corona points of diverse high-voltage devices, although other approaches based on partial discharge or radio interference voltage measurements are also widely applied to detect corona activity. Nevertheless, these two techniques must be applied in screened laboratories, which are scarce and expensive, require sophisticated instrumentation, and typically do not allow location of the discharge points. This paper describes the detection of the visual corona and location of the critical corona points of a sphere-plane gap configurations under different pressure conditions ranging from 100 to 20 kPa, covering the pressures typically found in aeronautic environments. The corona detection is made with a low-cost CMOS imaging sensor from both the visible and ultraviolet (UV) spectrum, which allows detection of the discharge points and their locations, thus significantly reducing the complexity and costs of the instrumentation required while preserving the sensitivity and accuracy of the measurements. The approach proposed in this paper can be applied in aerospace applications to prevent the arc tracking phenomenon, which can lead to catastrophic consequences since there is not a clear protection solution, due to the low levels of leakage current involved in the pre-arc phenomenon.Peer ReviewedPostprint (published version

DESIGN AND MICROFABRICATION OF A CMOS-MEMS PIEZORESISTIVE ACCELEROMETER AND A NANO-NEWTON FORCE SENSOR

DESIGN AND MICROFABRICATION OF A CMOS-MEMS PIEZORESISTIVE ACCELEROMETER AND A NANO-NEWTON FORCE SENSOR by Mohd Haris Md Khir Adviser: Hongwei Qu, Ph.D. This thesis work consists of three aspects of research efforts: I. Design, fabrication, and characterization of a CMOS-MEMS piezoresistive accelerometer 2. Design, fabrication, and characterization of a CMOS-MEMS nano-Newton force sensor 3. Observer-based controller design of a nano-Newton force sensor actuator system A low-cost, high-sensitivity CMOS-MEMS piezoresistive accelerometer with large proof mass has been fabricated. Inherent CMOS polysilicon thin film was utilized as piezoresistive material and full Wheatstone bridge was constructed through easy wiring allowed by three metal layers in CMOS thin films. The device fabrication process consists of a standard CMOS process for sensor configuration and a deep reactive ion etching (DRIE) based post-CMOS microfabrication for MEMS structure release. Bulk single-crystal silicon (SCS) substrate was included in the proof mass to increase sensor sensitivity. Using a low operating power of 1.67 m W, the sensitivity was measured as 30.7 mV/g after amplification and 0.077 mV/g prior to amplification. With a total noise floor of 1.03 mg!-!Hz, the minimum detectable acceleration is found to be 32.0 mg for a bandwidth of I kHz which is sufficient for many applications. The second device investigated in this thesis work is a CMOS-MEMS capacitive force sensor capable ofnano-Newton out-of-plane force measurement. Sidewall and fringe capacitance formed by the multiple CMOS metal layers were utilized and fully differential sensing was enabled by common-centroid wiring of the sensing capacitors. Single-crystal silicon (SCS) is incorporated in the entire sensing element for robust structures and reliable sensor deployment in force measurement. A sensitivity of 8 m V /g prior to amplification was observed. With a total noise floor of 0.63 mg!-IHz, the minimum detection acceleration is found to be 19.8 mg, which is equivalent to a sensing force of 449 nN. This work also addresses the design and simulation of an observer-based nonlinear controller employed in a CMOS-MEMS nano-Newton force sensor actuator system. Measurement errors occur when there are in-plane movements of the probe tip; these errors can be controlled by the actuators incorporated within the sensor. Observerbased controller is necessitated in real-world control applications where not all the state variables are accessible for on-line measurements. V

Electrochemical Sensors and On-chip Optical Sensors

abstract: The microelectronics technology has seen a tremendous growth over the past sixty years. The advancements in microelectronics, which shows the capability of yielding highly reliable and reproducible structures, have made the mass production of integrated electronic components feasible. Miniaturized, low-cost, and accurate sensors became available due to the rise of the microelectronics industry. A variety of sensors are being used extensively in many portable applications. These sensors are promising not only in research area but also in daily routine applications. However, many sensing systems are relatively bulky, complicated, and expensive and main advantages of new sensors do not play an important role in practical applications. Many challenges arise due to intricacies for sensor packaging, especially operation in a solution environment. Additional problems emerge when interfacing sensors with external off-chip components. A large amount of research in the field of sensors has been focused on how to improve the system integration. This work presents new methods for the design, fabrication, and integration of sensor systems. This thesis addresses these challenges, for example, interfacing microelectronic system to a liquid environment and developing a new technique for impedimetric measurement. This work also shows a new design for on-chip optical sensor without any other extra components or post-processing.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

On-chip optical sensors

Adding more functionality to chips is an important trend in the advancement of technology. During the past couple of decades, integrated circuit developments have focused on keeping Moore\u27s Law alive More of Moore . Moore\u27s law predicts the doubling of the number of transistors on an integrated circuit every year. My research objectives revolve around More than Moore , where different functionalities are sought to be integrated on chip. Sensing in particular is becoming of paramount importance in a variety of applications. Booming healthcare costs can be reduced with early diagnosis, which requires improved sensitivity and lower cost. To halt global warming, environmental monitoring requires miniature gas sensors that are cheap enough to be deployed at mass scale. First, we explore a novel silicon waveguide platform that is expected to perform well as a sensor in comparison to the conventional 220 nm thick waveguide. 50 and 70 nm shallow silicon waveguides have the advantage of easier lithography than conventional 220 nm thick waveguides due to the large minimum feature size required of 1 µm. 1 µm wide waveguides in these shallow platforms are single mode. A multi-mode interference device is designed in this platform to function as the smallest MMI sensor, giving sensitivity of 427 nm / refractive index unit (RIU) at a length of 4 mm. The silicon photonic MMI sensor is based on detecting refractive index changes. Refractometric techniques such as the MMI sensor require surface functionalization to achieve selectivity or specificity. Spectroscopic methods, usually reserved for material characterization in a research setting, can be adapted for highly specific label-free sensing. Chapter 4 explores the use of a highly doped III-V semiconductor for on chip infrared spectroscopy. Finite element method and finite different time domain were both used to design a plasmonic slot waveguide for gas sensing. On chip lasers and detectors have been designed using InAs. While InAs is still considered more expensive than silicon, the electronics industry expects to start incorporating more materials in standard fabrication processes, including III-V semiconductors for their superior properties including mobility. Thus, experimental realization of this sensor is feasible. A drawback with infrared spectroscopy is that it is difficult to use with biological fluids. Chapter 5 explores the use of Raman spectroscopy as a sensing method. To adapt Raman spectroscopy for sensing, the most important task is to enhance the Raman signal. The way the Raman signal is generated means that the number of photons is generally very low and usually bulk material or concentrated fluids are used as samples. To measure low concentrations of a probe molecule, the probe molecule is placed on a surface enhanced Raman spectroscopy (SERS) substrate. A typical SERS substrate is composed of metal nanostructures for their surface plasmon resonance property, which causes a large amplification in the electric field in particular hot spots. By decorated silicon nanowires with silver nanoparticles, an enhancement factor of 1011 was realized and picomolar concentrations of pyridine were detected using Raman spectroscopy. In conclusion, this thesis provides new concepts and foundations in three directions that are all important for on chip optical sensing. First, silicon photonics is the technology of choice that is nearest to the market and a multi-mode interference sensor based on shallow silicon waveguides was designed. Further work can explore how to cascade such MMIs to increase sensitivity without sacrificing the free spectral range. Second, infrared plasmonics is a promising technology. Before semiconductor plasmonics, on chip devices operated in the visible or near IR and then microwave region of the electromagnetic spectrum. By using highly doped semiconductors, it is possible to bridge the gap and operate with mid-infrared wavelengths. The implications are highlighted by designing a waveguide platform that can be used for next generation on chip infrared spectroscopy. Third, Raman spectroscopy was exploited as a sensing technique by experimental realization of a SERS substrate using equipment-free fabrication methods

A review and perspective on optical phased array for automotive LiDAR

This paper aims to review the state of the art of Light Detection and Ranging (LiDAR) sensors for automotive applications, and particularly for automated vehicles, focusing on recent advances in the field of integrated LiDAR, and one of its key components: the Optical Phased Array (OPA). LiDAR is still a sensor that divides the automotive community, with several automotive companies investing in it, and some companies stating that LiDAR is a ‘useless appendix’. However, currently there is not a single sensor technology able to robustly and completely support automated navigation. Therefore, LiDAR, with its capability to map in 3 dimensions (3D) the vehicle surroundings, is a strong candidate to support Automated Vehicles (AVs). This manuscript highlights current AV sensor challenges, and it analyses the strengths and weaknesses of the perception sensor currently deployed. Then, the manuscript discusses the main LiDAR technologies emerging in automotive, and focuses on integrated LiDAR, challenges associated with light beam steering on a chip, the use of Optical Phased Arrays, finally discussing current factors hindering the affirmation of silicon photonics OPAs and their future research directions

Making sense of light: the use of optical spectroscopy techniques in plant sciences and agriculture

As a result of the development of non-invasive optical spectroscopy, the number of prospective technologies of plant monitoring is growing. Being implemented in devices with different functions and hardware, these technologies are increasingly using the most advanced data processing algorithms, including machine learning and more available computing power each time. Optical spectroscopy is widely used to evaluate plant tissues, diagnose crops, and study the response of plants to biotic and abiotic stress. Spectral methods can also assist in remote and non-invasive assessment of the physiology of photosynthetic biofilms and the impact of plant species on biodiversity and ecosystem stability. The emergence of high-throughput technologies for plant phenotyping and the accompanying need for methods for rapid and non-contact assessment of plant productivity has generated renewed interest in the application of optical spectroscopy in fundamental plant sciences and agriculture. In this perspective paper, starting with a brief overview of the scientific and technological backgrounds of optical spectroscopy and current mainstream techniques and applications, we foresee the future development of this family of optical spectroscopic methodologies.info:eu-repo/semantics/publishedVersio

Magnetic biosensors: modelling and simulation

In the past few years, magnetoelectronics has emerged as a promising new platform technology in various biosensors for detection, identification, localisation and manipulation of a wide spectrum of biological, physical and chemical agents. The methods are based on the exposure of the magnetic field of a magnetically labelled biomolecule interacting with a complementary biomolecule bound to a magnetic field sensor. This Review presents various schemes of magnetic biosensor techniques from both simulation and modelling as well as analytical and numerical analysis points of view, and the performance variations under magnetic fields at steady and nonstationary states. This is followed by magnetic sensors modelling and simulations using advanced Multiphysics modelling software (e.g. Finite Element Method (FEM) etc.) and home-made developed tools. Furthermore, outlook and future directions of modelling and simulations of magnetic biosensors in different technologies and materials are critically discussed

Deep Learning-Based Multiple Object Visual Tracking on Embedded System for IoT and Mobile Edge Computing Applications

Compute and memory demands of state-of-the-art deep learning methods are still a shortcoming that must be addressed to make them useful at IoT end-nodes. In particular, recent results depict a hopeful prospect for image processing using Convolutional Neural Netwoks, CNNs, but the gap between software and hardware implementations is already considerable for IoT and mobile edge computing applications due to their high power consumption. This proposal performs low-power and real time deep learning-based multiple object visual tracking implemented on an NVIDIA Jetson TX2 development kit. It includes a camera and wireless connection capability and it is battery powered for mobile and outdoor applications. A collection of representative sequences captured with the on-board camera, dETRUSC video dataset, is used to exemplify the performance of the proposed algorithm and to facilitate benchmarking. The results in terms of power consumption and frame rate demonstrate the feasibility of deep learning algorithms on embedded platforms although more effort to joint algorithm and hardware design of CNNs is needed.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl