Concept: Electrical engineering
Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers.
Driven by advances in materials and computer science, researchers are attempting to design systems where the computer and material are one and the same entity. Using theoretical and computational modeling, we design a hybrid material system that can autonomously transduce chemical, mechanical, and electrical energy to perform a computational task in a self-organized manner, without the need for external electrical power sources. Each unit in this system integrates a self-oscillating gel, which undergoes the Belousov-Zhabotinsky (BZ) reaction, with an overlaying piezoelectric (PZ) cantilever. The chemomechanical oscillations of the BZ gels deflect the PZ layer, which consequently generates a voltage across the material. When these BZ-PZ units are connected in series by electrical wires, the oscillations of these units become synchronized across the network, where the mode of synchronization depends on the polarity of the PZ. We show that the network of coupled, synchronizing BZ-PZ oscillators can perform pattern recognition. The “stored” patterns are set of polarities of the individual BZ-PZ units, and the “input” patterns are coded through the initial phase of the oscillations imposed on these units. The results of the modeling show that the input pattern closest to the stored pattern exhibits the fastest convergence time to stable synchronization behavior. In this way, networks of coupled BZ-PZ oscillators achieve pattern recognition. Further, we show that the convergence time to stable synchronization provides a robust measure of the degree of match between the input and stored patterns. Through these studies, we establish experimentally realizable design rules for creating “materials that compute.”
Conventional ways of making bio-electrodes are generally complicated, expensive and unconformable. Here we describe for the first time the method of applying Ga-based liquid metal ink as drawable electrocardiogram (ECG) electrodes. Such material owns unique merits in both liquid phase conformability and high electrical conductivity, which provides flexible ways for making electrical circuits on skin surface and a prospective substitution of conventional rigid printed circuit boards (PCBs).
Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.
We have proposed and successfully demonstrated a novel approach to direct conversion of mechanical energy into electrical energy using microfluidics. The method combines previously demonstrated reverse electrowetting on dielectric (REWOD) phenomenon with the fast self-oscillating process of bubble growth and collapse. Fast bubble dynamics, used in conjunction with REWOD, provides a possibility to increase the generated power density by over an order of magnitude, as compared to the REWOD alone. This energy conversion approach is particularly well suited for energy harvesting applications and can enable effective coupling to a broad array of mechanical systems including such ubiquitous but difficult to utilize low-frequency energy sources as human and machine motion. The method can be scaled from a single micro cell with 10(-6) W output to power cell arrays with a total power output in excess of 10 W. This makes the fabrication of small light-weight energy harvesting devices capable of producing a wide range of power outputs feasible.
The control of charges in a circuit due to an external electric field is ubiquitous to the exchange, storage and manipulation of information in a wide range of applications. Conversely, the ability to grow clean interfaces between materials has been a stepping stone for engineering built-in electric fields largely exploited in modern photovoltaics and opto-electronics. The emergence of atomically thin semiconductors is now enabling new ways to attain electric fields and unveil novel charge transport mechanisms. Here, we report the first direct electrical observation of the inverse charge-funnel effect enabled by deterministic and spatially resolved strain-induced electric fields in a thin sheet of HfS2. We demonstrate that charges driven by these spatially varying electric fields in the channel of a phototransistor lead to a 350% enhancement in the responsivity. These findings could enable the informed design of highly efficient photovoltaic cells.
Rapid advancements in stretchable and multifunctional electronics impose the challenge on corresponding power devices that they should have comparable stretchability and functionality. We report a soft skin-like triboelectric nanogenerator (STENG) that enables both biomechanical energy harvesting and tactile sensing by hybridizing elastomer and ionic hydrogel as the electrification layer and electrode, respectively. For the first time, ultrahigh stretchability (uniaxial strain, 1160%) and transparency (average transmittance, 96.2% for visible light) are achieved simultaneously for an energy-harvesting device. The soft TENG is capable of outputting alternative electricity with an instantaneous peak power density of 35 mW m(-2) and driving wearable electronics (for example, an electronic watch) with energy converted from human motions, whereas the STENG is pressure-sensitive, enabling its application as artificial electronic skin for touch/pressure perception. Our work provides new opportunities for multifunctional power sources and potential applications in soft/wearable electronics.
The use of electric fields for signalling and control in liquids is widespread, spanning bioelectric activity in cells to electrical manipulation of microstructures in lab-on-a-chip devices. However, an appropriate tool to resolve the spatio-temporal distribution of electric fields over a large dynamic range has yet to be developed. Here we present a label-free method to image local electric fields in real time and under ambient conditions. Our technique combines the unique gate-variable optical transitions of graphene with a critically coupled planar waveguide platform that enables highly sensitive detection of local electric fields with a voltage sensitivity of a few microvolts, a spatial resolution of tens of micrometres and a frequency response over tens of kilohertz. Our imaging platform enables parallel detection of electric fields over a large field of view and can be tailored to broad applications spanning lab-on-a-chip device engineering to analysis of bioelectric phenomena.
Our world is increasingly powered by electricity, which is largely converted to or from mechanical energy using electric motors. Several applications have driven the miniaturization of these machines, resulting in high rotational speeds. Although speeds of several hundred thousand revolutions per minute have been used industrially, we report the realization of an electrical motor reaching 40 million rpm to explore the underlying physical boundaries. Millimeter-scale steel spheres, which are levitated and accelerated by magnetic fields inside a vacuum, are used as a rotor. Circumferential speeds exceeding 1000 m/s and centrifugal accelerations of more than 4 × 108 times gravity were reached. The results open up new research possibilities, such as the testing of materials under extreme centrifugal load, and provide insights into the development of future electric drive systems.
The cheapest and thus widespread way to add new generators to a high-voltage power grid is by a simple tree-like connection scheme. However, it is not entirely clear how such locally cost-minimizing connection schemes affect overall system performance, in particular the stability against blackouts. Here we investigate how local patterns in the network topology influence a power grid’s ability to withstand blackout-prone large perturbations. Employing basin stability, a nonlinear concept, we find in numerical simulations of artificially generated power grids that tree-like connection schemes-so-called dead ends and dead trees-strongly diminish stability. A case study of the Northern European power system confirms this result and demonstrates that the inverse is also true: repairing dead ends by addition of a few transmission lines substantially enhances stability. This may indicate a topological design principle for future power grids: avoid dead ends.