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SummaryA metamaterial developed by researchers at King's College London uses quantum effects to turn electrons flowing through a circuit into "hot electrons" and light in a highly controlled manner.According to the team,this has potential application in optoelectronics and sensing. BodyThe nanomaterial takes advantage of electron tunnelling to produce streams of particles which can have important applications, when properly controlled.   Accodring to the researcher Dr Pan Wang,this one tiny device offers several amazing applications: plasmon excitation, light generation and chemical reaction activation. And all this is achieved by a small, easy to produce material which only requires a small voltage to function. A voltage applied across the device causes electrons to flow from one material (eutectic gallium indium) to another (gold nanorods). These are separated by an air gap, which would usually stop the electron flow, but because the air gap is less than 1nm, the electrons can ‘tunnel’ through.Most of the tunnelling electrons arrive at the gold nanorod tips in the form of ‘hot electrons’, but a small proportion excite plasmons in the metamaterial to emit light whose wavelength is directly related to the applied voltage. According to the team, this conversion is usually inefficient, but the use of array gold nanorods provides 100billion tunnel junctions, improving electron-to-plasmon conversion and making the emitted light visible. While there are applications in sensing, the researchers point to a benefit in small scale electronics. Since light is generated by applying a voltage along a 10nm thick nanorod, it can be used to transmit information optically between or within chips. The metamaterial allows optical signals to be produced within a much smaller device, holding the potential of faster electronics. "We expected to generate some weak light which we thought should be enough for various nanophotonic applications when we began these studies," added King’s College Professor Anatoly Zayats ,"but But as sometimes happens in the research, the applications are much richer.” 

SummaryThe process that makes gold-plated jewelry or chrome car accents is now making powerful lithium-ion batteries. It's reported in the Joural Science Advances that research at the University of Illinois, Xerion Advanced Battery Corporation and Nanjing University in China developed a method for electroplating lithium-ion battery cathodes, yielding high-quality, high-performance battery materials that could also open the door to flexible and solid-state batteries in May,2017. Paul V. Braun, a professor of materials science and engineering and director of the Frederick Seitz Materials Research Lab at Illinois said that it's an entirely new approach to manufacturing battery cathodes, which resulted in batteries with previously unobtainable forms and functionalities. Traditional Lithium-ion BatteryTraditional lithium-ion battery cathodes use lithium-containing powders formed at high temperatures. The powder is mixed with gluelike binders and other additives into a slurry, which is spread on a thin sheet of aluminum foil and dried. The slurry layer needs to be thin, so the batteries are limited in how much energy they can store. The glue also limits performance. "The glue is not active. It doesn't contribute anything to the battery, and it gets in the way of electricity flowing in the battery," said co-author Hailong Ning, the director of research and development at Xerion Advanced Battery Corporation in Champaign, a startup company co-founded by Braun. The researchers bypassed the powder and glue process altogether by directly electroplating the lithium materials onto the aluminum foil claimed "You have all this inactive material taking up space inside the battery, while the whole world is trying to get more energy and power from the battery". The Electroplated CathodeSince the electroplated cathode doesn't have any glue taking up space, it packs in 30% more energy than a conventional cathode, according to the paper. It can charge and discharge faster as well, since the current can pass directly through it and not have to navigate around the inactive glue or through the slurry's porous structure. It also has the advantage of being more stable. What's more, the electroplating process creates pure cathode materials, even from impure starting ingredients. This means that manufacturers can use materials lower in cost and quality and the end product will still be high in performance, eliminating the need to start with expensive materials already brought up to battery grade, Braun said.  "This method opens the door to flexible and three-dimensional battery cathodes, since electroplating involves dipping the substrate in a liquid bath to coat it," said co-author Huigang Zhang, a former senior scientist at Xerion who is now a professor at Nanjing University. The researchers demonstrated the technique on carbon foam, a lightweight, inexpensive material, making cathodes that were much thicker than conventional slurries. They also demonstrated it on foils and surfaces with different textures, shapes and flexibility.These designs are impossible to achieve by conventional processes,however,what's really important is that it's a high-performance material and that it's nearly solid. By using a solid electrode rather than a porous one, more energy can be stored in a given volume. One of the day, people want batteries to store a lot of energy and peple will make this thought come true. 

SummaryIt has been successfully demonstrated that a nanocrystal of of perovskite can serve as a quantum emitter of light, and, when coupled with a nanophotonic cavity, can dramatically improve the efficiency of the light emission by an international research team from the University of Maryland and ETH Zurich in Switzerland.  A new device features perovskite nanocrystals and a series of nanophotonic cavities. The arrows indicate the way that the UV laser used to excite the crystals, and the light  the crystals produce, move in and out of the device. Described in the Journal Applied Physics Letters ,the resulting device and method could be used to build nanolasers and optical devices that exhibit much faster response times than currently possible. Previously, there have been other quantum emitting materials that have been coupled to nanophotonic cavities. In this area, epitaxial materials such as quantum dots have garnered the most research interest. Distinct advantage to using PerovskiteHowever, the researchers believe there are some distinct advantages to using perovskite nanocrystals instead of epitaxial materials, which involve the fairly complex deposition of a crystalline layer on a crystalline substrate.Instead of the epitaxial techniques, the perovskite nanocrystals are synthesized using inexpensive colloidal chemistry techniques. This also makes it possible for these crystals to be placed on a broad range of substrates using simpler solution-deposition techniques when they are coupled to various photonic structures. The other main set of advantages for perovskites in light-emitting applications relates back to why they have become such a darling in photovoltaics: their optical and electrical properties. Perovskites exhibit a slow non-radiative decay rate and low densities of carrier-trapping defects, which contributes to their high photoluminescence efficiency at room temperature.In addition, the emission spectrum could cover the whole visible range by controlling the size and material composition, especially for the blue-green wavelengths that are otherwise difficult to access. The device operates by exciting the coupled system using a UV laser. This excites the perovskites to a higher energy level. Within a nanosecond, the exciton (an excited electron-hole pair) will decay to its ground state while transforming its energy in the form of an emitting photon. The cavity introduces more decay channels to the emitting materials, so a majority of the photons are coupled into the cavity and form the standing mode of the cavity. Finally, the researchers are able to detect the photons leaking away from the cavity, which is the emission signal. Difficult metThe problem that previous attempts have encountered in working with nanocrystal perovskites has been the material quality. “We need emitters with good photostability, so it can hold the performance when coupling to the cavities, said Yang. “Our collaborators from ETH provided perovskites that make this coupling possible.” In addition to nanolasers and faster optoelectronics, Yang believes the device they have made could increase the efficiency of existing perovskite emitting devices, such as LEDs, which could open up real-world applications in efficient illumination and displays. Before these aspirations can be realized, Yang concedes that they will need to further improve the performance and stability of the material itself. Second, it would be better to excite the material electrically rather than optically for practical use.Yang will try to realize similar devices spanning the whole visible range and the next step it to find ways to further improve and stabilize the performance and also utilizing electrical gates to excite the material in devices. Article source: Applied Physics LettersArticle edited by kynix 

DescriptionIt's not weird to discover that applications are becoming more complex,with connectivity just one of the drivers. And,as it become more complex.the number of sensors grows,as does the need for more capable user interfaces. At the same time,algoriths need more processing power,wireless stacks mandate larger memories and power budgets are shrinking.In order to coping with the growing list of demands, a great number of leading MCU manufacturers have recently launched Micro Controller Unit built around the ARM Cortex-M4 core. BodyThe M3 is general purpse and the M0+is low cost but the M4 is a more capable core in general if look at the Cortex range. Oivind Loe,a senior strategic marketing manager with Sillicon Laboratories said. Microchip's product marketing manager--Anand Rangara commented:“Something that sat around without the need to communicate now needs connectivity. When that happens, you need more flash and RAM, as well as graphics capability and perhaps the ability to support a touch interface. All this has to be offered at good power/performance and an attractive price.”  'Industrial Strength' MCUsSilicon Labs has expanded its EFM32 Gecko portfolio with what it calls ‘industrial strength’ MCUs. It says the EFM32GG11 Giant Gecko MCU family offers the ‘most advanced’ feature set available in the low-power MCU market.Loe noted that MCU development isn’t just about power. “It’s also about executing tasks efficiently. A simple program with a few clocks will run efficiently on an M0+ core. But if the workload is larger, the M4 core has some special instructions that can allow it to use less energy than the M0+ and more efficiently than some larger cores – and that's crucial for a range of application.” GG11 Geckos offer up to 2Mbyte of flash and 512kbyte of RAM to accommodate more code and comms stacks, such as a 10/100 Ethernet MAC and a dual CAN interface. Looking to meet power budgets, the parts boast an active power consumption of 77μA/MHz, while drawing 1.6μA in deep sleep mode. FPU to Increase System EffiencyMicrochip’s SAM D5x/E5x MCUs also take advantage of the Cortex-M4’s floating point unit (FPU) to increase system efficiency. Running at up to 120MHz, the D5x and E5x MCUs come with up to 1Mbyte of dual-panel flash and up to 256kbyte of SRAM. Rangarajan noted: “We’ve listened to our customers, so we’ve included more connectivity in these MCUs. But it's not just about adding memory , it’s also about more performance and the ability to provide more flexible peripherals, interfaces and connectivity options.” Meanwhile,he  pointed out that the original SAM D MCUs – developed by Atmel prior to its acquisition by Microchip – were based on the Cortex-M0+. “But we’ve always wanted to take the product line to the next level of performance. This allows Microchip to address a broader range of consumer and industrial automation applications.” Limited the Clock RateBucking the trend to a certain extent, both Silicon Labs and Microchip have limited the clock rate in their latest MCUs. Giant Geckos, for example, have a maximum clock of 72MHz. “These products are focused on energy efficiency,” Loe claimed. “If you build an MCU to run at 200MHz, for example, then each clock cycle will consume more energy than in an MCU running at 72MHz. A lot of MCUs will be used in battery powered apps, so we need to be energy efficient and to enable the CPU to sleep a lot.” Rangarajan agreed that clock rate is not always the primary factor when it comes to developing MCU portfolios. “We hear our customers saying don’t give me faster clock rates, make sure the MCUs meet my requirements. An app that runs from a battery requires a power efficient MCU. If you want a fast MCU, then you have to make trade offs.” In Loe’s views, MCU selection is all about the ability to perform certain tasks at a particular power efficiency. “That is always going to involve trade offs, but an M4 based MCU will generally be good for embedded applications with challenging energy consumption requirements.” Adopt the Concept of Smart PeripheralsBoth companies have adopted the concept of smart peripherals in their recent products. Loe explained: “Twenty years ago, most MCUs saw the CPU doing everything. That took a lot of CPU cycles, which meant you couldn’t do as much as you might have liked.“Today, most apps will take advantage of DMA, which offloads the CPU. In turn, this allows the CPU to do more.” Rangarajan said Microchip provides what he called ‘sleepwalking’ peripherals. “If there’s a requirement for them to do small numbers of transactions, this can be done without waking the CPU.” On the other hand,Sillicon Loe Noted that It’s all about when you have to wake up the M4 core. We’re trying to allow it to sleep for as much as possible. More than half of the peripherals in a Giant Gecko can run autonomously in deep sleep mode. Both Companies are Keen to Highlight Their Provision Silicon Labs has launched a starter kit to support Giant Gecko based application development(following picture) With this approach, a Giant Gecko’s A/D converter can operate while the CPU is in deep sleep mode. “It can sample and use DMA to pull the data into RAM,” Loe continued.Loe highlighted a couple of aspects. “We have included a cyrotimer that runs in shut off; the lowest energy mode. It’s a simple timer that’s useful when you need the CPU to be asleep for minutes. there’s the Peripheral Reflex System, which allows peripherals to talk. For example, the real time clock could tell the A/D converter to take a sample. It gives a level of determinism which you don’t get from a CPU.  Microchip's Product brings better power efficiency How does an MCU developer differentiate their products from similar devices with an M4 core? Rangarajan pointed to the integration of a buck regulator. “This brings better power efficiency,” he claimed, “which means lower active power consumption; as little as 65µA/MHz. The parts also support flexible pin options.”“We’re offering the best integrated security features,” Rangarajan contended. “SAM Dx/Ex MCUs have crypto hardware acceleration – symmetrical and asymmetrical – and public key encryption, amongst other features. It’s something Microchip has taken to heart and has made sure it’s all in the MCU.“We’re offering the best integrated security features,” Rangarajan contended. “SAM Dx/Ex MCUs have crypto hardware acceleration – symmetrical and asymmetrical – and public key encryption, amongst other features. It’s something Microchip has taken to heart and has made sure it’s all in the MCU.  EndLoe pointed to the security management unit (SMU) as an ‘upgrade’ to the memory protection unit (MPU) associated with the M4’s core. “While the MPU allows you to segment memory into eight regions, the SMU takes that further. The MPU is restricted to eight regions, so there is limited granularity. The SMU allows you to selectively say which pieces of code can access each peripheral.” “All of this is important,” Rangarajan concluded, “as security will become standard in the next few years.” 

TroublesAs the deployment of Industrial IoT systems continues to proliferate,the streams of data transferred to the cloud skyrockets, drastically increasing the cost for cloud computing.  SolutionIn order to meet this trouble, many systems designers are adopting edge computing,in which data processing is done close to the source like sensors in a bid to reduce data transfer,storage and processing costs,plus address a few other concerns over Cloud Computing,in particular security. What is Big DataBig Data is a broad label for the growing amount of data generated by IoT devices and smart systems. For instance, some aircraft engines have more than 5,000 elements that are monitored at relatively high sample rates. Most of the data is transferred to a ground station for the real-time monitoring of the engine and for future R&D work. But this is only part of a growing trend. Most ‘smart’ systems produce vast amounts of data which needs to be processed immediately or be stored for subsequent processing. Huge datacentres are required if you want to store Big Data.Big Data is a broad label for the growing amount of data generated by IoT devices and smart systems. For instance, some aircraft engines have more than 5,000 elements that are monitored at relatively high sample rates. Most of the data is transferred to a ground station for the real-time monitoring of the engine and for future R&D work. But this is only part of a growing trend. Most ‘smart’ systems produce vast amounts of data which needs to be processed immediately or be stored for subsequent processing. Cloud Computing's advantages and disadvantagesCloud Computing has a lot of advantages including cost efficiency (i.e. no need to invest in and maintain your own hardware), scalability, resource availability (for all your users irrespective of their geographic locations), lower latency (as you can specify servers that are closest to the relevant users/customers) and peace of mind in terms of back-ups. There are,however,some disadvantages also. The biggest of which is that no provider can guarantee 100% availability. Data security and privacy are also causes for concern, both on the cloud and for data in transit. Latency can be an issue for Big Data, and doing computationally intensive tasks on the cloud will increase the cost. Of these concerns the last two, in particular, can be negated through edge processing; i.e. performing much of the computationally intensive work near the source data. Benefits here include real-time or near-real-time data processing and reduced network traffic, as you need only transfer the product of the edge processing, thus resulting in lower Cloud Computing costs. Security and privacy can be improved by keeping the sensitive data (a.k.a. Hot Data) within the edge processing environment and only sending less sensitive (Cold) data to the cloud. FPGAs have the edgeThere are technologies that can be used for edge processing applications. These include the use of traditional CPUs (scoring high in terms of flexibility), application-specific processors (e.g. GPUs) and ASICs/SoCs (scoring high on performance). However, it is FPGAs that are slotting into most edge processing applications. Why is this so? Well, let’s consider the requirements. Edge processing needs to be high-performance and in this respect an FPGA can perform several different tasks in parallel. For example, consider executing many non-dependent computations (such as A=B+C, D=E+F and G=H+I). On a CPU, these would have to be performed sequentially, with each sum requiring a few clock cycles. In an FPGA, an array of adders could do the computations in parallel, possibly requiring only a single clock cycle. Power efficiency is essential too, as the end product may well be battery-powered. With an FPGA the function (design) need be the only circuit present, whereas the architecture of a CPU or GPU may not be fully utilized. Also, with an FPGA comes the benefit of reprogrammability. Higher security is afforded too because the edge processing functions are hard wired into the FPGA. It is also possible to encrypt the transaction bus and to even go as far as designing your own processor. ConnectingA prime example of where edge processing is extremely useful, and in which FPGAs can play a significant role, is within an embedded system in which data derived from images needs to be transferred. For example, in the automotive sector Advanced Driver Assistance Systems (ADAS) are under development to make driving safer, easier and more comfortable, and ADAS is regarded as a significant step towards fully autonomous cars. The data processed by an ADAS can be used to notify the driver of problems or to automatically trigger responses such as deceleration, braking and/or the execution of a manoeuvre. The data can also be useful outside the vehicle. Let's discuss the embedded vision system first though by considering an ADAS demo unit that was built for this year's Embedded Vision show in Santa Clara, California. The demo comprised a TySOM-2-7Z100 prototyping board (see figure 1) which includes a Xilinx Zynq XC7Z100 device and a TySOM-FMC-ADAS daughter board to interface with four 960 x 540 pixel cameras. The processing was shared between a dual-core ARM Cortex-A9 processor and FPGA logic (both of which reside within the Zynq device) and began with frame grabbing images from the cameras and applying an edge detection algorithm (‘edge’ here in the sense of physical edges, such as objects, lane markings etc.). This is a computational-intensive task because of the pixel-level computations being applied (i.e. more than 2 million pixels). To perform this task on the ARM CPU a frame rate of only 3 per second could have been realised, whereas in the FPGA 27.5 fps was achieved.This picture is a TySOM-2-7Z100 prototyping board. Mixed technology (like CPU and FPGA) boards are proving very popular for edge processing applications and for connecting with the cloud.  The ARM CPU was mainly used for superimposing detected edges over the initial camera images, colour-space conversions, the formation of a composite image (see main image) and outputting it to an HD buffer. The FPGA and CPU could also work together to recognise and distinguish between obstacles and pedestrians close to the car and to provide lane departure warnings. What goes upSending the processed data to the cloud for further processing and/or storage is then a relatively simple task. Firstly, an AWS account would be created along with an AWS IoT environment. Next, we would configure a Thing (seeing as it is the IoT) and download the public and private keys needed for secure communications with the cloud.The embedded C MQTT standard would be the ideal Software Development Kit (SDK), because it is secure and requires minimal bandwidth. An application would then be prepared to run on the ARM CPU to publish the data onto the cloud. Imagine a scenario,howevber,under which we have data from thousands of vehicles going to the cloud.Analysis of the data could be performed on the cloud and made available for traffic systems or highway maintenance organisations, for example. There may also be instances where data from the cloud feeds into an edge-processing application, in which case applications are also available from AWS. All in all,there are both advantages and disadvantages associated with cloud computing. And many of the disadvantages will be overcome though edge-processing that FPGAs are a particularly suitable activity.  Article provided by Farhad Fallah,an Application Engineer with EDA company AldecArticle edited by Kynix 

SummaryThe robot comes perfectly if they can walk more naturally for humans.However,it's not an easy job for robots and their designers. Walking on two legs is actually a complicated task,requiring several muscles to perform delicate balancing acts.That's why in spite of years of major technological advancements in the field,humanoid robots are still far from being able to get around easily and reliably. Engineers at EPFL's Biorobotics Laboratory are testing new walking algoritms on a plateform called COMAN, short for COmpliant HuMANoid. This 95-cm-tall humanoid is designed specifically for studying walking – which is why it has no head. COMAN was developed under the EU AMARSi project and is being used by several research teams. The EPFL team is looking specifically at the "brains" of the machine. "We developed algorithms that can improve the robot's balance while it's walking," says Hamed Razavi, a researcher scientist at the Biorobotics Lab.  Body One:Climbing Stairs and Opening Doors The algorithms are geared towards three types of realworld applications. The first is carrying out rescue missions in disastrous scenarios. "In environments designed by humans - like a nuclear power plant where there are stairs to climb and doors to open – humanoid robots can get around more easily than robots with wheels," says Razavi. The second is helping with tasks like carrying heavy boxes or moving objects (see box). And the third is creating exoskeletons for the disabled. "Making the robots more stable is just the tip of the iceberg," says Razavi. The next step is refining the algorithms so that the humanoids have a wider range of movement and can overcome obstacles and walk on irregular or sloped surfaces. Two:In Harmony with Symmetries One of COMAN's distinguishing features is its joints,which are integrated with elastic elements that give it greater flexibility when performing different tasks.The EPFL team came up with a novel control algorithm for the robot, based on the existing symmetries in the structure and dynamics of the robot' as well as the mathematical equations representing the robot dynamics. "You could say we're working in harmony with these symmetries rather than against them. As a result, we obtain a more natural and robust walking gait," says Razavi. The control algorithm uses sophisticated computer programs to carefully analyze the date received from the robot – including its position, velocity, joint angles, etc. – and sends appropriate commands to the motors, telling them what to do in order to maintain the robot's balance. "For example, if someone pushes COMAN, for example, our algorithms will calculate exactly where its foot should land in order to counteract the perturbation," says Razavi. Three: Humanoids Helping Humans As part of this project,Jessica Lanini and Hamed Razavi studied how two people carrying an object together are able to walk,turn and speed up in a coordinated manner - without communicating with each other.Their findings,recently published in PLOS ONE,indicate that the two people automatically synchronize their steps, like a quadruped. Now the researchers plan to apply their results to humanoid robots. Lanini explained:"Whether for manufacturing or natural disasters, we need robots that can interact with humans and help us carry heavy objects,but such robots don't exist. That's because, in order to operate safely and effectively, the robots would need to be able to make decisions and respond to unexpected circumstances." But such robots don't exist. The reason is that in order to operate safely and effectively, the robots would need to be able to make decisions and respond to unexpected circumstances." Article provided by  Ecole Polytechnique Federale de Lausanne.