About the amplification factors in organic bioelectronic sensors

A systematic comparison between electrochemical and organic bioelectronic sensors reveals a unified rational description for a transistor amplified detection

On-die CMOS temperature sensors

Temperature changes can have an impact on the reliability and functioning of sensitive integrated circuits. In this thesis an analog DTMOS transistor temperature was designed and laid out in 22 nm CMOS fabrication process using Cadence Virtuoso electrical design automation suite. The design was verifed and validated using Cadence Spectre electrical simulation software and the simulation results were analyzed and compared to previous sensor designs. The new design was found to be less power hungry but slightly less accurate than the original design. The new design also showed a signifcant improvement in operating voltage resilience compared to a previous design used at LG Electronics Finland Lab Oy. Over all the design goals were met and the sensor is ready to be added to be a part of a future integrated circuit

Interfacing of neuromorphic vision, auditory and olfactory sensors with digital neuromorphic circuits

The conventional Von Neumann architecture imposes strict constraints on the development of intelligent adaptive systems. The requirements of substantial computing power to process and analyse complex data make such an approach impractical to be used in implementing smart systems. Neuromorphic engineering has produced promising results in applications such as electronic sensing, networking architectures and complex data processing. This interdisciplinary field takes inspiration from neurobiological architecture and emulates these characteristics using analogue Very Large Scale Integration (VLSI). The unconventional approach of exploiting the non-linear current characteristics of transistors has aided in the development of low-power adaptive systems that can be implemented in intelligent systems. The neuromorphic approach is widely applied in electronic sensing, particularly in vision, auditory, tactile and olfactory sensors. While conventional sensors generate a huge amount of redundant output data, neuromorphic sensors implement the biological concept of spike-based output to generate sparse output data that corresponds to a certain sensing event. The operation principle applied in these sensors supports reduced power consumption with operating efficiency comparable to conventional sensors. Although neuromorphic sensors such as Dynamic Vision Sensor (DVS), Dynamic and Active pixel Vision Sensor (DAVIS) and AEREAR2 are steadily expanding their scope of application in real-world systems, the lack of spike-based data processing algorithms and complex interfacing methods restricts its applications in low-cost standalone autonomous systems. This research addresses the issue of interfacing between neuromorphic sensors and digital neuromorphic circuits. Current interfacing methods of these sensors are dependent on computers for output data processing. This approach restricts the portability of these sensors, limits their application in a standalone system and increases the overall cost of such systems. The proposed methodology simplifies the interfacing of these sensors with digital neuromorphic processors by utilizing AER communication protocols and neuromorphic hardware developed under the Convolution AER Vision Architecture for Real-time (CAVIAR) project. The proposed interface is simulated using a JAVA model that emulates a typical spikebased output of a neuromorphic sensor, in this case an olfactory sensor, and functions that process this data based on supervised learning. The successful implementation of this simulation suggests that the methodology is a practical solution and can be implemented in hardware. The JAVA simulation is compared to a similar model developed in Nengo, a standard large-scale neural simulation tool. The successful completion of this research contributes towards expanding the scope of application of neuromorphic sensors in standalone intelligent systems. The easy interfacing method proposed in this thesis promotes the portability of these sensors by eliminating the dependency on computers for output data processing. The inclusion of neuromorphic Field Programmable Gate Array (FPGA) board allows reconfiguration and deployment of learning algorithms to implement adaptable systems. These low-power systems can be widely applied in biosecurity and environmental monitoring. With this thesis, we suggest directions for future research in neuromorphic standalone systems based on neuromorphic olfaction

Organic bioelectronic devices to control cell signalling

The nervous system consists of a network of specialized cells that coordinate the actions of the body by transmitting information to and from the brain. The communication between the nerve cells is dependent on the interplay of both electrical and chemical signals. As our understanding of nerve cell signalling increases there is a growing need to develop techniques capable of interfacing with the nervous system. One of the major challenges is to translate between the signal carriers of the nervous system (ions and neurotransmitters) and those of conventional electronics (electrons). Organic conjugated polymers represent a unique class of materials that can utilize both electrons and ions as charge carriers. Taking advantage of this combined feature, we have established a novel communication interface between electronic components and biological systems. The organic bioelectronic devices presented in this thesis are based on the organic electronic ion pump (OEIP) made of the conducting organic polymer poly(3,4-ethylenedioxythiophene) doped with poly(styrenesulfonate) (PEDOT:PSS). When electronically addressed, electrochemical redox reactions in the polymer translate electronic signals into electrophoretic migration of ions. We show that the device can transport a range of substances involved in nerve cell signaling. These include positively charged ions, neurotransmitters and cholinergic substances. Since the devices are designed to be easily incorporated in conventional microscopy set-ups, we use Ca2+ imaging as readout to monitor cell responses. We demonstrate how electrophoretic delivery of ions and neurotransmitters with precise, spatiotemporal control can be used to modulate intracellular Ca2+ signaling in neuronal cells in the absence of convective disturbances. The electronic control of delivery enables strict control of dynamic parameters, such as amplitude and frequency of Ca2+ responses, and can be used to generate temporal patterns mimicking naturally occurring Ca2+ oscillations. To enable further control and fine-tuning of the ionic signals we developed the electrophoretic chemical transistor, an analogue of the traditional transistor used to amplify and/or switch electronic signals. We thereby take the first step towards integrated chemical circuits. Finally, we demonstrate the use of the OEIP in a new “machine-to-brain” interface. By encapsulating the OEIP we were able to use it in vivo to modulate brainstem responses in guinea pigs. This was the first successful realization of an organic bioelectronic device capable of modulating mammalian sensory function by precise delivery of neurotransmitters. Our findings highlight the potential of communication interfaces based on conjugated polymers in generating complex, high-resolution, signal patterns to control cell physiology. Such devices will have widespread applications across basic research as well as future applicability in medical devices in multiple therapeutic areas

Passive micromixers and organic electrochemical transistors for biosensor applications

Fluid handling at the microscale has greatly affected different fields such as biomedical, pharmaceutical, biochemical engineering and environmental monitoring due to its reduced reagent consumption, portability, high throughput, lower hardware cost and shorter analysis time compared to large devices. The challenges associated with mixing of fluids in microscale enabled us in designing, simulating, fabricating and characterizing various micromixers on silicon and flexible polyester substrates. The mixing efficiency was evaluated by injecting the fluids through the two inlets and collecting the sample at outlet. The images collected from the microscope were analyzed, and the absorbance of the color product at the outlet was measured to quantify the mixing efficacy. A mixing efficiency of 96% was achieved using a flexible disposable micromixer. The potential for low-cost processing and the device response tuning using chemical doping or synthesis opened doorways to use organic semiconductor devices as transducers in chemical and biological sensor applications. A simple, inexpensive organic electrochemical transistor (OECT) based on conducting polymer poly(3,4- ethyelenedioxythiphene) poly(styrene sulfonate) (PEDOT:PSS) was fabricated using a novel one step fabrication method. The developed transistor was used as a biosensor to detect glucose and glutamate. The developed glucose sensor showed a linear response for the glucose levels ranging from 1 μM-10 mM and showed a decent response for the glucose levels similar to those found in human saliva and to detect glutamate released from brain tumor cells. The developed glutamate sensor was used to detect the glutamate released from astrocytes and glioma cells after stimulation, and the results are compared with fluorescent spectrophotometer. The developed sensors employ simple fabrication, operate at low potentials, utilize lower enzyme concentrations, do not employ enzyme immobilization techniques, require only 5 μL of both enzyme and sample to be tested and show a stable response for a wide pH ranging from 4 to 9

A walk on the frontier of energy electronics with power ultra-wide bandgap oxides and ultra-thin neuromorphic 2D materials

Altres ajuts: the ICN2 is funded also by the CERCA programme / Generalitat de CatalunyaUltra-wide bandgap (UWBG) semiconductors and ultra-thin two-dimensional materials (2D) are at the very frontier of the electronics for energy management or energy electronics. A new generation of UWBG semiconductors will open new territories for higher power rated power electronics and deeper ultraviolet optoelectronics. Gallium oxide - GaO(4.5-4.9 eV), has recently emerged as a suitable platform for extending the limits which are set by conventional (-3 eV) WBG e.g. SiC and GaN and transparent conductive oxides (TCO) e.g. In2O3, ZnO, SnO2. Besides, GaO, the first efficient oxide semiconductor for energy electronics, is opening the door to many more semiconductor oxides (indeed, the largest family of UWBGs) to be investigated. Among these new power electronic materials, ZnGa2O4 (-5 eV) enables bipolar energy electronics, based on a spinel chemistry, for the first time. In the lower power rating end, power consumption also is also a main issue for modern computers and supercomputers. With the predicted end of the Moores law, the memory wall and the heat wall, new electronics materials and new computing paradigms are required to balance the big data (information) and energy requirements, just as the human brain does. Atomically thin 2D-materials, and the rich associated material systems (e.g. graphene (metal), MoS2 (semiconductor) and h-BN (insulator)), have also attracted a lot of attention recently for beyond-silicon neuromorphic computing with record ultra-low power consumption. Thus, energy nanoelectronics based on UWBG and 2D materials are simultaneously extending the current frontiers of electronics and addressing the issue of electricity consumption, a central theme in the actions against climate chang