The Kynix Blog - General electronic semiconductor

  Background Nowadays,more and more people need wifi and they can not leave it.More and more family has connected with wifi even in undeveloping country or area.Today,let's make a wifi based home automation project to realize that controlling home devices by using wifi as wireless communication. In this project,we will using esp8266 wifi module and Arduino Uno R3,We have also posted a similar project using pic microcontroller based home automation over wifi. you may also like to check it.    components we needESP8266 Wifi Module: ESP8266 is a wifi chip that provides Transfer Control Protocol (TCP) and Internet Protocol (IP). There are different ESP8266modules available in the market. In this project we are using the first model. It has 6 pins and operates on 3.3v. ESP8266 was initialized via the following commands:ATAT+CWMODE = 3AT+CIFSRAT+CIPMUX = 1ESP8266 was then connected to the mobile hotspot by the following commands:AT+CWLAP (returns the list of the available Wi-Fi networks available)AT+CWJAP = “SSID”, “password”  Example: AT+CWJAP = “PTCL-BB”, “12345467”Arduino Uno: Arduino is development boards build around ATmega 328P. Arduino is perfect for this project as it provides much pins to interface relay module,16×2 LCD and ESP8266 wifi module4 channel Relay Module: Relay is used to switch on and off higher voltages devices by using low dc voltages such as signal from Arduino digital pin. In this project we used 4 channel relay module it is easy to interface with Arduino instead of connecting each relay separately. It can bears up to 250VAC and 10 amps of current.16X2 LCD: 16×2 LCD is used to display 16 characters in two lines. It is easy to interface with Arduino due to its available library. In this project this LCD is used to display the status of the appliances whether it is on or off. Project Circuit Diagram  Connections 16×2 LCD:VSS to ground.VDD to supply voltage.VO to adjust pin of 10k potentiometer.RS to Pin A0.RW to ground.Enable to Pin A1.LCD D4 to Pin A2.LCD D5 to Pin A3.LCD D6 to Pin A4.LCD D7 to Pin A5.Ground one end of potentiometer.5v to other end of potentiometer. 4 Channel Relay modules:External 5 volt to JD VCC.Ground to ground.Ini1 to Pin 3.Ini2 to Pin 4.Ini3 to Pin5.Vcc to Arduino 5v.Connect one terminal of all bulbs to normally open terminal of relays. One end of 220VAC to all common terminals of relay and other end with other terminal of bulbs. ESP8266 wifi module to Arduino:Module Vcc to 3.3v.Module CH_PD to 3.3v.Module Ground to Arduino ground.Module Tx to Arduino Rx.Module Rx to Arduino Tx. Working Download the S Remote application from Google Play Store. Open the application, go to Setting>>Advance>>Layout and select the Button according to your desire. Then select IP and enter the IP address which is get when we initialize ESP8266 wifi module using this command “AT+CIFSR”. IP address is written in third line such as “192.168.10.4”. Then write the port which is “80” in port option. Go to Setting>>Keys and then select key1 and write the label to display on button and then the data which you want to send to Arduino. Click the TCP button. Similarly write the label and data in others keys. If you connect everything correctly then power up the circuit and open serial monitor, it takes few seconds to initialize wifi module. Press the button on application, the data is send by application to Arduino through Wifi and then Arduino performs operations according to instructions and the status on devices are display on LCD.  

（Researchers have developed an algorithm that allows residential customers to share power from the renewable energy sources in their homes during an outage.） If you think you can use the solar panels on your roof to power your home during an outage, think again. During an outage, while your home remains connected to the grid, the devices that manage your solar panels are powered down for safety reasons. In other words, this permanent connection to the grid makes it impossible for homeowners to draw on power generated by their own renewable energy resources. A team of engineers at the University of California San Diego wants to change this. They have developed algorithms that would allow homes to use and share power from their renewable energy sources during outages by strategically disconnecting these devices, called solar inverters, from the grid. The algorithms work with existing technology and would improve systems' reliability by 25 to 35 percent. Researchers detail the algorithms and their applications in a paper they presented at the American Control Conference in Seattle, Wash. "We were inspired to start investigating a way to use renewable power during outages after Hurricane Sandy affected eight million people on the East Coast and left some without power for up to two weeks," said Abdulelah H. Habib, a Ph.D. candidate in mechanical engineering at UC San Diego and the paper's first author. Our Society is Dependent upon ElectricityJust a few hours without power can cause massive losses to both product and revenue.We rely on electricity much more than we realize. Even if you live "off the grid," as I did for years, you are still living in a world and a society that is deeply dependent upon electricity. If the power is out for a few hours, we have all experienced that; of course you'll be fine. Maybe you will be a little bored and inconvenienced, but if the outage is lengthy and widespread, the consequences can be much more severe, even deadly. What would happen if the electricity was out for a week?Every year, 7 million customers experience power outages. Outages that last more than 5 to 10 minutes cost customers more than $80 billion each year. How the Algorithm WorksThe innovation here is the algorithm's capability to prioritize distribution of power from renewable resources during an outage. The equations take into account forecasts for solar and wind power generation as well as how much energy storage is available, including electric vehicles, batteries and so on. The algorithm combines that information with the amount of energy that the residents are projected to use as well as the amount of energy that a cluster of homes can generate.The algorithm could also be programmed to include a priority function, based on different parameters. For example, customers who are willing to pay more could get priority to get power during an outage. Or customers who generate more energy than they produce during normal operations would not lose power during an outage. More importantly, the algorithm could give priority to customers who are in urgent need of power, because they use life support equipment, for example. Ref.KY605-LC-R064R5PKY605-0860-0004

（Metal-semiconductor-metal junction (tunnel barrier) incorporated into a single graphene nanoribbon: The atomic and electronic structure of the nanoribbons can be probed with atomic resolution using advanced microscopic techniques.）   Essential electronic components, such as diodes and tunnel barriers, can be incorporated in single graphene wires (nanoribbons) with atomic precision. The goal is to create graphene-based electronic devices with extremely fast operational speeds. The discovery was made in a collaboration between Aalto University and their colleagues at Utrecht University and TU Delft in the Netherlands. The work is published in Nature Communications. The 'wonder material' graphene has many interesting characteristics, and researchers around the world are looking for new ways to utilise them. Graphene itself does not have the characteristics needed to switch electrical currents on and off and smart solutions must be found for this particular problem. "We can make graphene structures with atomic precision. By selecting certain precursor substances (molecules), we can code the structure of the electrical circuit with extreme accuracy," explains Peter Liljeroth from Aalto University, who conceived the research project together with Ingmar Swart from Utrecht University. Seamless integration The electronic properties of graphene can be controlled by synthesizing it into very narrow strips (graphene nanoribbons). Previous research has shown that the ribbon's electronic characteristics are dependent on its atomic width. A ribbon that is five atoms wide behaves similarly to a metallic wire with extremely good conduction characteristics, but adding two atoms makes the ribbon a semiconductor. "We are now able to seamlessly integrate five atom-wide ribbons with seven atom-wide ribbons. That gives you a metal-semiconductor junction, which is a basic building block of electronic components," according to Ingmar Swart. Chemistry on a surface The researchers produced their electronic graphene structures through a chemical reaction. They evaporated the precursor molecules onto a gold crystal, where they react in a very controlled way to yield new chemical compounds. "This is a different method from that currently used to produce electrical nanostructures, such as those on computer chips. For graphene, it is so important that the structure is precise at the atomic level and it is likely that the chemical route is the only effective method," Ingmar Swart concludes. Electronic characteristics The researchers used advanced microscopic techniques to also determine the electronic and transport characteristics of the resulting structures. It was possible to measure electrical current through a graphene nanoribbon device with an exactly known atomic structure. "This is the first time where we can create e.g. a tunnel barrier and really know its exact atomic structure. Simultaneous measurement of electrical current through the device allows us to compare theory and experiment on a very quantitative level," says Peter Liljeroth.  Source:Aalto University Ref.MN3306STTH2002G-TR 

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

The CC2640R2F SimpleLink ultra-low-power wireless microcontroller from Texas Instruments (TI) is in stock at Mouser Electronics. Part of TI’s CC26xx SimpleLink family of 2.4GHz devices, the CC2640R2F microcontroller features a small, single-chip system that integrates a flash-based microcontroller and Bluetooth Smart radio to target Bluetooth 4.2 and Bluetooth 5 low-energy applications. The microcontroller combines a 61μA/MHz ARM Cortex-M3 microcontroller and a rich peripheral set that includes an 8.2μA/MHz sensor controller. The 48MHz ARM microcontroller offers 128 kBytes of flash and 28 kBytes of SRAM and supports over-the-air (OTA) updates. The sensor controller is ideal for interfacing external sensors and for collecting analog and digital data autonomously while the rest of the system is in sleep mode. The device includes a 12-bit analogue-to-digital converter, up to 31 general-purpose inputs and outputs (GPIOs), and built-in robust security on chip with one of the simplest radio frequency (RF) and antenna designs available. Minimal RF expertise is required to implement the device, which helps make development and layout extremely easy. The wireless microcontroller is available in 2.7×2.7 mm WCSP and 4×4, 5×5 and 7×7 mm QFN packages, and is designed for a board array of wireless Internet of Things (IoT) applications, including health and fitness, industrial, and home and building automation. With ready-to-use protocol stacks (including the SIMPLELINK-CC2640R2-SDK software development kit for Bluetooth 5), the SimpleLink portfolio of wireless connectivity solutions not only offers designers maximum flexibility and support but also delivers multi-standard capabilities with code- and pin-compatibility across Bluetooth Smart, 6LoWPAN, ZigBee and ZigBee RF4CE.   Ref: KY32-MB91F376GPMCR-GS KY32-MB90F548GSPFV-G KY32-HD6417604SVF20

Two microcontroller lines from STMicroelectronics increase energy efficiency, flexibility, and feature integration at the high end of the STM32F4 Access Line for high-performance embedded designs. Qualified up to 125°C, these STM32 devices target always-on sensor acquisition and general-purpose industrial applications and present a robust and cost-effective upgrade from STM32F1 MCUs. The STM32F413 and crypto-enhanced STM32F423 integrate up to 1.5MB Flash and dense SRAM of 320KB. These are the most highly featured of the STM32F4 Access Lines, with rich audio capabilities including a Serial Audio Interface (SAI) and an enhanced voice-acquisition interface with multi-channel Digital Filter for Sigma-Delta Modulators (DFSDM) that enables low-power sound localisation and beam forming. The devices also provide peripheral integration, with two 12-bit Digital-Analogue Converters (DACs), up to 10 UARTs, and three CAN 2.0B active interfaces. The crypto-enhanced STM32F423 also has a True Random-Number Generator (TRNG) and AES-256 cryptographic hardware accelerator.Sitting at the top of the STM32F4 Access Lines, the MCUs introduce a 100MHz dual-mode Quad SPI for connecting serial off-chip memory, 16-bit Flexible Memory Controller (FMC) for external SRAM, PSRAM or NOR Flash, up to 16-bit QVGA or 8-bit WQVGA LCD interface, and USB OTG with Link Power Management (LPM) and dual power rails that save external level shifting.In addition, both lines feature a RAM-access scheme that uses the Instruction and Data (I/D) buses and the System BUS (SBUS) to connect to separate RAM1 (256KB) and RAM2 (64KB) areas thereby minimising contentions. An enhanced DMA Batch Acquisition Mode (BAM+) takes advantage of these separate RAM1 and RAM2 areas to process code and data extremely efficiently in sensor-hub applications.Delivering high performance, the STM32 microcontrollers combine the 100MHz 125DMIPS/339 EEMBC CoreMark ARM Cortex-M4 core with ST’s power-saving Dynamic Efficiency technologies that cut RUN mode current up to 112µA/MHz. These Dynamic Efficiency technologies include the ST ART Accelerator for zero-wait execution from Flash, and the supply-voltage extending down to 1.7V, to maximise the battery life of always-connected devices.Designers can immediately start their projects using the NUCLEO-F413ZH development board. This STM32 Nucleo-144 board comes with the ST-LINK/V2-1 debugger/programmer, software libraries and examples, and can be used directly with ARM mbed online resources. Ref:KY32-STM32F401CBU6KY32-STM32F401CCU6KY362-STM32F401C-DISCO