Printing of wirelessly rechargeable solid-state supercapacitors for soft, smart contact lenses with continuous operations

Recent advances in smart contact lenses are essential to the realization of medical applications and vision imaging for augmented reality through wireless communication systems. However, previous research on smart contact lenses has been driven by a wired system or wireless power transfer with temporal and spatial restrictions, which can limit their continuous use and require energy storage devices. Also, the rigidity, heat, and large sizes of conventional batteries are not suitable for the soft, smart contact lens. Here, we describe a human pilot trial of a soft, smart contact lens with a wirelessly rechargeable, solid-state supercapacitor for continuous operation. After printing the supercapacitor, all device components (antenna, rectifier, and light-emitting diode) are fully integrated with stretchable structures for this soft lens without obstructing vision. The good reliability against thermal and electromagnetic radiations and the results of the in vivo tests provide the substantial promise of future smart contact lenses

A review of advances in pixel detectors for experiments with high rate and radiation

The Large Hadron Collider (LHC) experiments ATLAS and CMS have established hybrid pixel detectors as the instrument of choice for particle tracking and vertexing in high rate and radiation environments, as they operate close to the LHC interaction points. With the High Luminosity-LHC upgrade now in sight, for which the tracking detectors will be completely replaced, new generations of pixel detectors are being devised. They have to address enormous challenges in terms of data throughput and radiation levels, ionizing and non-ionizing, that harm the sensing and readout parts of pixel detectors alike. Advances in microelectronics and microprocessing technologies now enable large scale detector designs with unprecedented performance in measurement precision (space and time), radiation hard sensors and readout chips, hybridization techniques, lightweight supports, and fully monolithic approaches to meet these challenges. This paper reviews the world-wide effort on these developments.Comment: 84 pages with 46 figures. Review article.For submission to Rep. Prog. Phy

A handheld high-sensitivity micro-NMR CMOS platform with B-field stabilization for multi-type biological/chemical assays

We report a micro-nuclear magnetic resonance (NMR) system compatible with multi-type biological/chemical lab-on-a-chip assays. Unified in a handheld scale (dimension: 14 x 6 x 11 cm³, weight: 1.4 kg), the system is capable to detect<100 pM of Enterococcus faecalis derived DNA from a 2.5 μL sample. The key components are a portable magnet (0.46 T, 1.25 kg) for nucleus magnetization, a system PCB for I/O interface, an FPGA for system control, a current driver for trimming the magnetic (B) field, and a silicon chip fabricated in 0.18 μm CMOS. The latter, integrated with a current-mode vertical Hall sensor and a low-noise readout circuit, facilitates closed-loop B-field stabilization (2 mT → 0.15 mT), which otherwise fluctuates with temperature or sample displacement. Together with a dynamic-B-field transceiver with a planar coil for micro-NMR assay and thermal control, the system demonstrates: 1) selective biological target pinpointing; 2) protein state analysis; and 3) solvent-polymer dynamics, suitable for healthcare, food and colloidal applications, respectively. Compared to a commercial NMR-assay product (Bruker mq-20), this platform greatly reduces the sample consumption (120x), hardware volume (175x), and weight (96x)

Doctor of Philosophy

dissertationSince the late 1950s, scientists have been working toward realizing implantable devices that would directly monitor or even control the human body's internal activities. Sophisticated microsystems are used to improve our understanding of internal biological processes in animals and humans. The diversity of biomedical research dictates that microsystems must be developed and customized specifically for each new application. For advanced long-term experiments, a custom designed system-on-chip (SoC) is usually necessary to meet desired specifications. Custom SoCs, however, are often prohibitively expensive, preventing many new ideas from being explored. In this work, we have identified a set of sensors that are frequently used in biomedical research and developed a single-chip integrated microsystem that offers the most commonly used sensor interfaces, high computational power, and which requires minimum external components to operate. Included peripherals can also drive chemical reactions by setting the appropriate voltages or currents across electrodes. The SoC is highly modular and well suited for prototyping in and ex vivo experimental devices. The system runs from a primary or secondary battery that can be recharged via two inductively coupled coils. The SoC includes a 16-bit microprocessor with 32 kB of on chip SRAM. The digital core consumes 350 μW at 10 MHz and is capable of running at frequencies up to 200 MHz. The integrated microsystem has been fabricated in a 65 nm CMOS technology and the silicon has been fully tested. Integrated peripherals include two sigma-delta analog-to-digital converters, two 10-bit digital-to-analog converters, and a sleep mode timer. The system also includes a wireless ultra-wideband (UWB) transmitter. The fullydigital transmitter implementation occupies 68 x 68 μm2 of silicon area, consumes 0.72 μW static power, and achieves an energy efficiency of 19 pJ/pulse at 200 MHz pulse repetition frequency. An investigation of the suitability of the UWB technology for neural recording systems is also presented. Experimental data capturing the UWB signal transmission through an animal head are presented and a statistical model for large-scale signal fading is developed

Neuro-memristive Circuits for Edge Computing: A review

The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks and open problems in the field of neuro-memristive circuits for edge computing