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Engineers at the University of Maryland have invented an entirely new kind of battery. It is bio-compatible because it produces the same kind of ion-based electrical energy used by humans and other living things.In our bodies, flowing ions (sodium, potassium and other electrolytes) are the electrical signals that power the brain and control the rhythm of the heart, the movement of muscles, and much more. In traditional batteries, the electrical energy, or current, flows in form of moving electrons. This current of electrons out of the battery is generated within the battery by moving positive ions from one end (electrode) of a battery to the other. The new UMD battery does the opposite. It moves electrons around in the device to deliver energy that is a flow of ions. This is the first time that an ionic current-generating battery has been invented. "My intention is for ionic systems to interface with human systems," said Liangbing Hu, the head of the group that developed that battery. Hu is a professor of materials science at the University of Maryland, College Park. He is also a member of the University of Maryland Energy Research Center and a principal investigator of the Nanostructures for Electrical Energy Storage Energy Frontier Research Center, sponsored by the Department of Energy, which funded the study. "So I came up with the reverse design of a battery," Hu said. "In a typical battery, electrons flow through wires to interface electronics, and ions flow through the battery separator. In our reverse design, a traditional battery is electronically shorted (that means electrons are flowing through the metal wires). Then ions have to flow through the outside ionic cables. In this case, the ions in the ionic cable -- here, grass fibers -- can interface with living systems." The work of Hu and his colleagues was published in the July 24 issue of Nature Communications. "Potential applications might include the development of the next generation of devices to micro-manipulate neuronal activities and interactions that can prevent and/or treat such medical problems as Alzheimer's disease and depression," said group member Jianhua Zhang, PhD, a staff scientist at the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), part of the National Institutes of Health in Bethesda, Md. "The battery could be used to develop medical devices for the disabled, or for more efficient drug and gene delivery tools in both research and clinical settings, as a way to more precisely treat cancers and other medical diseases, said Zhang, who performed biological experiments to test that the new battery successfully transmitted current to living cells.. "Looking far ahead on the scientific horizon, one hopes also that this invention may help to establish the possibility of direct machine and human communication," he said. Bio-compatible, bio-material batteries Because living cells work on ionic current and existing batteries provide an electronic current, scientists have previously tried to figure out how to create biocompatibility between these two by patching an electronic current into an ionic current. The problem with this approach is that electronic current needs to reach a certain voltage to jump the gap between electronic systems and ionic systems. However, in living systems ionic currents flow at a very low voltage. Thus, with an electronic-to-ionic patch the induced current would be too high to run, say, a brain or a muscle. This problem could be eliminated by using ionic current batteries, which could be run at any voltage. The new UMD battery also has another unusual feature -- it uses grass to store its energy. To make the battery, the team soaked blades of Kentucky bluegrass in lithium salt solution. The channels that once moved nutrients up and down the grass blade were ideal conduits to hold the solution. The demonstration battery the research team created looks like two glass tubes with a blade of grass inside, each connected by a thin metal wire at the top. The wire is where the electrons flow through to move from one end of the battery to the other as the stored energy slowly discharges. At the other end of each glass tube is a metal tip through which the ionic current flows. The researchers proved that the ionic current is flowing by touching the ends of the battery to either end of a lithium-soaked cotton string, with a dot of blue-dyed copper ions in the middle. Caught up in the ionic current, the copper moved along the string toward the negatively charged pole, just as the researchers predicted. "The microchannels in the grass can hold the salt solution, making them a stable ionic conductor," said Chengwei Wang, first author of the paper and a graduate student in the Materials Science and Engineering department at the University of Maryland in College Park. However, the team plans to diversify the types of ionic current electron batteries they can produce. "We are developing multiple ionic conductors with cellulose, hydrogels and polymers," said Wang. This is not the first time UMD scientists have tested natural materials in new uses. Hu and his team previously have been studying cellulose and plant materials for electronic batteries, creating a battery and a supercapacitor out of wood and a battery from a leaf. They also have created transparent wood as a potentially more energy-efficient replacement for glass windows. Creative Work Ping Liu, an associate professor in nanoengineering at the University of California, San Diego, who was not involved with the study, said: "The work is very creative and its main value is in delivering ionic flow to bio systems without posing other dangers to them. Eventually, the impact of the work really resides in whether smaller and more biocompatible junction materials can be found that then interface with cells and organisms more directly and efficiently." Source:University of Maryland Ref.ML-621S/ZTNMS412FE-FL26E  

In recent years Artificial intelligence (AI) has become a technology that global companies are desperately trying to take advantage of, as it is one of the most emerging and competitive technologies. However, a lot of AI technologies focus on the software, with operating speeds low which makes them a poor fit for mobile devices. For this reason big companies are focusing on developing AI with low power and high speeds, hoping to make AI fit for mobile use.   Professor Hoi-Jun Yoo of the Department of Electrical Engineering, along with his research team and collaboration with start-up company, UX Factory Co, has developed a semiconductor chip, CNNP (CNN Processor), which runs AI algorithms with ultra-low power, and K-Eye, a face recognition system using CNNP. Consisting of two different formats, the K-Eye series is available as a wearable type and a dongle type. The wearable type device can be used with a smartphone via Bluetooth, and it can operate for more than 24 hours with its internal battery. By conveniently hanging the K-Eye around their necks users can check information about people by using their smartphone or smart watch, which connects K-Eye and allows users to access a database via their smart devices. A smartphone with K-EyeQ, the dongle type device, can recognise and share information about users at any time.  It works by recognising an authorised user looking at the screen, which then automatically turns the smartphone on, without a fingerprint, passcode or iris authentication. The smartphone cannot be tricked by the user’s photograph, as it can distinguish whether an input face is coming from a saved photograph versus a real person. Other distinct features are carried out by the K-Eye series. Detecting a face at first and then recognising it is one, and it is possible to maintain ‘Always-on’ status with low power consumption of less than 1mW. The research team devised two key technologies to complete this: an image sensor with ‘Always-on’ face detection and the CNNP face recognition chip.  The ‘Always-on’ image sensor, the first key technology, is able to determine if there is a face in its camera range. Then, it can capture frames and set the device to operate only when a face exists, reducing the standby power significantly. Additionally the face detection sensor combines analogue and digital processing to reduce power consumption. Using this approach, the analogue processor, combined with the CMOS Image Sensor array, distinguishes the background area from the area likely to include a face, and the digital processor then detects the face only in the selected area. Therefore, it becomes effective in terms of frame capture, face detection processing, and memory usage.    Following this the second key technology, CNNP, is able to achieve incredibly low power consumption, by optimising a convolutional neural network (CNN) in the areas of circuitry, architecture, and algorithms. Specially designed to enable data to be read in a vertical direction as well as in a horizontal direction, the on-chip memory integrated in CNNP also has immense computational power with 1024 multipliers and accumulators operating in parallel and is capable of directly transferring the temporal results to each other without accessing to the external memory or on-chip communication network. Additionally, convolution calculations with a two-dimensional filter in the CNN algorithm are approximated into two sequential calculations of one-dimensional filters to achieve higher speeds and lower power consumption.  CNNP achieved 97% high accuracy but consumed only 1/5000 power of the GPU thanks to these new technologies. Face recognition can be performed with only 0.62mW of power consumption, and the chip can show higher performance than the GPU by using more power.  Developed by Kyeongryeol Bong, a PhD student under Professor Yoo, these chips were presented at the International Solid-State Circuit Conference (ISSCC) held in San Francisco earlier this year. CNNP, which has the lowest reported power consumption in the world, has achieved a huge amount of attention, which has led to the development of the present K-Eye series for face recognition.  Professor Yoo commented: “AI - processors will lead the era of the Fourth Industrial Revolution. With the development of this AI chip, we expect Korea to take the lead in global AI technology.”  Ref.MT9V022 OV05633

To help detect and prevent possible incidents at critical facilities and public venues, Intel technology is powering a face recognition engine that can rapidly and accurately identify people, even when they are moving and in a crowd. NEC relied on Intel Arria 10 field programmable gate arrays (FPGAs) operating on Intel Xeon processor–based servers to increase the performance of its NEC NeoFace facial recognition engine to a level where an individual can be identified smoothly from a high-resolution image with dozens of faces.  “Facial recognition in a moving crowd requires highly advanced techniques when compared to still images because these cameras are affected by many factors: camera location, image quality and lighting, along with the subject’s size, walking speed and face direction,” said Tadashige Kadoi, general manager of IoT Platform Development Division, NEC. “Intel FPGAs and their parallel processing capability help NEC to enable fast and accurate collection and processing of images from even 4K high-resolution remote cameras.” Intel FPGA acceleration technology played a role in a recent achievement for NEC. In March, NEC NeoFace was ranked Number 1 in almost all tests by the US National Institute of Standards and Technology (NIST) specifically for face-in-video evaluation. The NIST tests evaluated the accuracy of the technology in two real-life test scenarios including a test for entry-exit management at an airport passenger gate. It determined whether and how well the engine could recognise people as they walked through an area one at a time without stopping or looking at the camera. NEC's face recognition technology won first place with a matching accuracy of 99.2%. The error rate of 0.8% is less than one-fourth of the second place error rate. In the second test, the technology was asked to detect suspicious individuals at an indoor stadium. This test was conducted with an individual situated far from the camera, with their face direction changing frequently. NEC's face recognition technology won first place with an error rate half that of the second place error rate. To create the NeoFace Accelerator, NEC’s NeoFace facial recognition engine software IP is integrated into an Intel Arria 10 FPGA, keeping the same accuracy level while achieving higher performance in facial recognition than the previous solution. Intel teams also worked with NEC to enhance the performance of NeoFace data centre server technology. NEC NeoFace Accelerator includes not only the Intel Arria 10 FPGA, but also an Intel MAX 10 low-cost FPGA and Intel Enpirion power devices. Ref.KY32-EP1S60B956C6KY32-EP4CGX150DF27I7 

Diodes Incorporated introduced the BCR401U, BCR402U and BCR405U. Appealing to lighting designers, these constant-current regulators enable simple driving of low- current LED strips and panels in the commercial and industrial lighting sectors. Targeted at 12 V and 24 V linear LED strips, these regulators increase light output efficiency as they only require a 1.4 V supply, allowing more LEDs in the string. By achieving regulation within ±10% and providing preset options of 10 mA (BCR401U), 20 mA (BCR402U), and 50 mA (BCR405U) that can be adjusted up to 100 mA, these regulators simplify the design, minimize component count, and overall enhance system reliability by integrating the driver. Combined with the improved efficiency and longer life offered by LEDs, many lighting applications including advertising, emergency, refrigeration, decorative, architectural and other general forms are being superseded with this emerging light source.  Delivering a regulated current over a wide 1.4 V to 40 V supply, the BCR40xU will tolerates voltage spikes and LED short failures in strings, whilst preserving LED brightness and longevity. This, along with a negative temperature coefficient that reduces the LED current with rising temperature, helps to increase the LED lifespan by reducing dissipation and additionally enables parallel device operation for increased current in applications requiring more than 100 mA. The BCR40xU operates as a linear LED driver, minimizing the likelihood of EMI, which is particularly important in medical lighting and other sensitive applications, while LED brightness can be PWM controlled with <1% duty cycle at 25 kHz allowing accurate dimming to low light levels. The BCR401U, BCR402U and BCR405U LED drivers are offered in the industry-standard SOT-26 (SC74R) package. Ref.KY32-BCR401U E6327KY32-BCR402UKY32-BCR405UE6327  

Texas Instruments (TI) introduced the industry's first differential inductive switch, with a dual-coil architecture that automatically compensates for variations in temperature and component aging. The LDC0851 detects the presence or absence of conductive material by using a simple coil drawn on a printed circuit board (PCB). This unique approach enables low-cost, highly reliable switching implementations for a variety of uses including buttons, knobs, door open/close detection, and speed and directional sensing in personal electronics, appliances, industrial equipment and communications applications. The LDC0851 provides a temperature-stable switching accuracy of better than 1 percent of the sensor coil diameter, removing the need for production calibration and minimizing part-to-part variation. Unlike alternative sensing technologies, the LDC0851's contactless and magnet-free design is immune to dirt, dust or other environmental factors, providing designers a reliable, low-cost solution. The device joins TI's distinctive portfolio of inductive-sensing integrated circuits (ICs) including the LDC1614 family of multichannel inductance-to-digital converters.  Key features and benefits of the LDC0851: ·Stable switching threshold:The differential architecture maintains the switching threshold across variations in temperature, humidity and other environmental factors, as well as providing immunity to component aging for stable, long-term performance. ·High accuracy:The device can deliver better than 1 percent switching accuracy, which is up to 10 times more accurate than magnetic sensor-based designs, reducing the need for production calibration. ·High reliability:The device's immunity to nonconductive contaminants such as oil, dirt and dust can help extend product lifetimes and reduce replacement costs. The solution is also unaffected by direct current (DC) magnetic fields, ensuring robust operation and reliability in a wide range of environments. ·Low power:Duty cycling of the LDC0851 allows for less than 20-µA average current consumption at 10 samples per second, which is up to five times lower than competitive solutions. Tools and support to jump-start design The LDC0851EVM evaluation module helps designers easily configure the LDC0851 and start designing it into a system without programming.（The LDC0851EVM evaluation module.）An incremental rotary encoder reference design (TIDA-00828) demonstrates the LDC0851 in a simple 32-position rotary-knob design. Using only two LDC0851 inductive switches, the system can track rotation position and direction, and designers can easily scale the number of encoder positions up or down.（TIDA-00828 Inductive Sensing 32-Position Encoder Knob ReferenceDesign using the LDC0851.） System designers can start their inductive-sensing design in minutes with TI's WEBENCH Coil Designer. This online tool simplifies sensor-coil design based on application and system requirements. The optimized design is exportable to a variety of computer-aided design (CAD) programs to quickly incorporate the sensor coil into an overall system layout. Ref.KY362-LDC0851EVMKY362-LDC1614EVM     

A simple and efficient PWM lamp dimmer using timer IC NE555 is discussed in this article. Yesterdays linear regulator based dimmers can only attain a maximum efficiency  of 50% and are far inferior when compared to the PWM based dimmers which can hit well over 90% efficiency. Since less amount of power is wasted as heat, the switching elements of PWM dimmers require a smaller heat sink and this saves a lot of size and weight. In simple words, the most outstanding features of the PWM based lamp dimmers are high efficiency and low physical size. The circuit diagram of a 12V PWM lamp dimmer is shown below. As you can see, NE555 timer IC which is wired as an astable multivibrator operating at 2.8KHz forms the heart of this circuit. Resistors R1,R2, POT R3 and capacitor C1 are the timing components. Duty cycle of the IC’s output can be adjusted using the POT R3. higher the duty cycle means higher the lamp brightness and lower the duty cycle means lower the lamp brightness. Diode D1 by-passes the lower half of the POT R3 during the charging cycle of the astable multivibrator. This is done in order to keep the output frequency constant irrespective of the duty cycle. Transistors Q1 and Q2 forms a darlington driver stage for the 12V lamp. Resistor R4 limits the base current of transistor Q1.Understanding the variable duty cycle astable multivibrator.As I have said earlier, the variable duty cycle astable multi vibrator based on NE555 forms the foundation of this circuit and a good knowledge on it is essential for designing projects like this. For the ease of explanation the timing side of the astable multivibrator is redrawn in the figure below.Upper and lower halves of the POT R3 are denoted as Rx and Ry respectively. Consider the output of the astable multivibrator to be high at the starting instant. Now the capacitor C1 charges through the path R1, Rx, and R2. The lower half of POT R3 ie; Ry is out of the scene because the diode D1 by-passes it. When the voltage across the capacitor reaches 2/3 Vcc, the internal upper comparator flips its output which makes the internal flip flop to toggle its output. As a result the output of the astable multivibrator goes low. In simple words, the output of the astable multivibrator remains high until the charge across C1 becomes equal to 2/3 Vcc and here it is according to the equation Ton =0.67(R1+Rx+R2)C1.Since the internal flip flop is set now, the capacitor starts discharging through the path R2,Ry into the discharge pin. When the voltage across the capacitor C1 becomes 1/3 Vcc, the lower comparator flips its output and this in turn makes the internal flip flop to toggle its output again. This makes the output of the astable multivibrator high. To be simple, the output of the astable multivibrator remains low until the voltage across the capacitor C1 becomes 1/3 Vcc and it is according to the equation Toff = 0.67(R2+Ry)C1. Have a look at the internal block diagram of NE555 timer shown below for better understanding.How does the frequency remain constant irrespective of the position of POT3 knob?.What ever may be the position of  POT3 knob, the total resistance across it remains the same (50K here). If anything decreases in the upper side (Rx) the same amount will be increased in the lower (Ry) and the same thing gets applied to the higher(Ton) and lower(Toff) time periods. The derivation shown below will help you to grasp the matter easily.With reference to Fig 2, we have:Ton = 0.67(R1+Rx+R2)C1Toff= 0.67(R2+Ry)C1Total time period of the output waveform “T” is according to the equation :T = Ton + ToffThere fore, T = 0.67(R1+Rx+R2+R2+Ry)C1                        T= 0.67(R1+2R2+Rx+Ry)C1We know that Rx+Ry = R3There fore T = 0.67(R1+2R2+R3)C1Therefore frequency F = 1/(0.67(R1+2R2+R3)C1) From the above equation its is clear that the frequency depends only on the value of the components C1, R1, R2  and the over all value of R3 and it has nothing to do with the position of R3 knob.  Ref:KY32-NE555KY32-NE555.NE555DR.NE555P