This design implements a USB security token powered by an STM32 microcontroller. The device is engineered for compactness and efficient PCB integration while ensuring robust security features. Key elements of the design include: - **Microcontroller Core:** A STM32F103T8U6 serves as the primary processing unit, handling USB communication and security protocols. - **USB Interface:** A USB-A plug provides connectivity to the host. Dedicated net portals ensure proper routing of the VBUS, D+, D–, and ground signals. - **Power Regulation:** A low-dropout regulator supplies a stable 3.3V operating voltage, ensuring low noise and proper current supply to the microcontroller and peripherals. - **Signal Conditioning and EMI Filtering:** An EMI filter is used to maintain signal integrity and reduce interference while preserving the security token’s functionality. - **Synchronous Elements:** A ceramic resonator is incorporated to provide a precise clock source for USB data transfer and microcontroller operations. - **Additional Components:** Surface-mount resistors, capacitors, and LED indicators are deployed to ensure proper conditioning, decoupling, and status feedback. Their compact 0402 packages facilitate a highly integrated design. - **Connectivity and Net Portals:** Custom net portals are used throughout the schematic to streamline connectivity and PCB layout, keeping the design modular and easy to modify. This USB security token is designed with industry-standard components and robust connectivity to ensure secure, reliable operation in portable security applications. #USBToken #STM32 #PCBDesign #SecurityTechnology #PortableSecurity #Microcontrollers #USBInterface #PowerRegulation #EMIProtection #CompactDesign

This device will be connected to computer through type-C and recognize as MIDI device. User can change two effects(A and B) from lists, effect speed(Tempo) and volume. #audioDevices

A 3-bit counter showcasing digital logic simulation. Input is a sequence of pulses which pass through a logic block to determine the segments.

Lipo Charger Shield. Directly plugs into Arduino Uno R3. Charge rate set with solder jumpers. Use with any MCU through tapping the VIN pin for power. VIN pin takes either

Project Overview: This project is an enhanced LED blinking circuit that goes beyond a simple 555 timer-based design. It incorporates additional features such as random blinking patterns, speed control, and a start/stop function. The project utilizes a microcontroller, such as an Arduino or Raspberry Pi, to control the blinking patterns, speed, and start/stop functionality. LED Blinking: The board features a total of 8 LEDs that blink in various random patterns. When the board is powered on, even before user interaction, the LEDs start blinking randomly, creating an eye-catching display. Each LED has its own current-limiting resistor to ensure proper current flow and prevent damage. The microcontroller is programmed to generate random blinking patterns for the LEDs, ensuring that the LEDs do not blink in a predictable or sequential order. This random blinking adds an element of unpredictability and visual interest to the project. Speed Control: The board includes two speed control buttons that allow the user to adjust the blinking speed of the LEDs. Button 1 is designated as the "fast" button, increasing the blinking speed when pressed, while Button 2 is designated as the "slow" button, decreasing the blinking speed when pressed. The speed control provides a range of blinking speeds, from a slow, gradual blink to a rapid, strobe-like effect. The microcontroller monitors the state of the speed control buttons and adjusts the blinking speed accordingly. Start/Stop Functionality: A third button serves as a start/stop control. When pressed, it toggles the blinking of the LEDs on or off. This allows the user to freeze the blinking pattern at any desired moment or resume the blinking when desired. The microcontroller handles the start/stop functionality by turning the LEDs on or off based on the state of the start/stop button. Manual Speed Adjustment: In addition to the speed control buttons, the board includes a potentiometer or variable resistor. This component allows the user to manually adjust the blinking speed of the LEDs by turning the knob or sliding the control. The manual speed adjustment provides more precise and customizable control over the blinking speed compared to the preset speeds of the buttons. The microcontroller reads the analog value from the potentiometer and adjusts the blinking speed accordingly. Power and Connectivity: The board is powered through a USB-C or USB-micro B connector, allowing it to be easily connected to a power source such as a computer or wall adapter. A voltage regulator may be included to ensure a stable and appropriate voltage supply to the components. A power switch is incorporated to conveniently turn the board on or off.

sEMG-DAQ is a wearable 6 channel data acquisition unit for capturing surface electromyographic (sEMG) signals from human arm muscles using SJ2-3593D jack connectors while conditioning, digitizing, processing and transmitting them as sEMG data to an external AI accelerated board through an SM12B-SRSS IDC connector where AI models are run for various applications including robotic control, muscle signals medical assessment and gesture recognition. The board leverages an INA125P instrumentation amplifier together with filter stages utilizing LM324QT op-amps for conditioning and an STM32G4A1VET6 microcontroller for the digitization, processing and data transmission of the signals. Since AI models can only be as good as the data, the design of such a DAQ is necessary to ensure clean, reliable and real-time data for AI applications requiring sEMG data. The board also has USB-FS and JTAG to cater for debugging. The power (5V) is fed through a screw terminal and is regulated by two LDK320AM LDO regulators to offer 5V, 3.3V and 1.8V to meet the requirements of various components on the board.

This project is a LoRa data logger implementing the i.MX RT1010 microcontroller. It collects and logs data through the LoRa-E5 module and stores the data via a TF card. Capacitors and resistors are used to construct the necessary circuits, ensuring proper functionality. This system is ideal for long-distance, low-power IoT applications. #project #LoRa #RT1010 #SDCARD

This device will be connected to computer through type-C and recognize as MIDI device. User can change two effects(A and B) from lists, effect speed(Tempo) and volume.

This is a recreation of the [EV5920-5048-V-00A](https://www.monolithicpower.com/en/ev5920-5048-v-00a.html) from MPS which demonstrates a MP5920 Hot-Swap controller commanding 5 MP5048 e-fuses in parallel. WIP Items: -Routing In flux, this project demonstrates hierarchal design through the use of modules. Additionally, parametric symbols are used extensively to improve schematic cleanliness. Components in the canvas are locked because their positions correspond to the same positions as the original layout. Changelog from Original MPS Design: - Not including GPIO2 or GPIO3 as included in the original board due to NC pin name on the IC. - PC1 and PC2 footprints are 5mm in pitch and 12.5mm in diameter rather than the 16mm diameter in the original layout. This change corresponds with the selected part more accurately. -Renamed Designators to be More Verbose

This is a LoRa-based door and window sensor incorporating a microcontroller unit (MCU). It features a reed sensor, LED indicators, a AAA non-rechargeable battery, and a booster IC for constant voltage. The MCU is linked to peripherals through nets, ensuring optimal performance #LoRa #MCU #ReferenceDesign #project #referenceDesign #simple-embedded #seeed #seeed-studio #template #reference-design

The Ariel AI chip prototype is an advanced electronic component designed to enhance the capabilities of Flux AI systems through a sophisticated arrangement of transistors, resistors, capacitors, and a cutting-edge CPU. Key components include two NPN transistors (part numbers NPN-TRANS-001 and NPN-TRANS-002), which are essential for signal amplification, alongside precision resistors (RES-1K and RES-1K-002) each with a resistance of 1kΩ, and a capacitor (CAP-10UF) with a capacitance of 10μF, crucial for filtering and stabilizing the voltage supply. At the heart of the design is a revolutionary CPU (part number CPU-RT-4C-2G) featuring a quad-core setup with a clock speed of 2GHz, based on a radical transistor architecture, designed to deliver unparalleled computational performance for AI tasks. This component set is powered by a 5V DC power supply (DCPS-5V), ensuring a stable and efficient operation. The Ariel AI chip is engineered for high-speed, reliable performance in demanding AI applications, representing a significant advancement in electronic component design for artificial intelligence systems.

This design is three parts, one a bandpass filter to allow only a certain frequency to come through the device, and the other two to filter and jam out different frequencies that would be coming near the device. The bandpass is set at 450MHz as is the common frequency for phones, the top jammer is set up for blocking out typical radio frequencies while the bottom is set to block frequencies above that of a phone signal. Vin=20 volts

Guitar pedal starter template based on project by Mark Wu. Includes schematic and PCB layout for basic DIY pedal hardware. This includes two 1/4" jacks (one for input and one for output), a 9V power supply (including LED), a 3PDT true bypass wiring setup, and an example potentiometer that can be copy/pasted throughout the circuit. The headers are meant to be unpopulated so that wires can be soldered to the pads. PCB design rules imported from the JLCPCB 2-layer stackup template. #template

A 3-bit counter showcasing digital logic simulation. Input is a sequence of pulses which pass through a logic block to determine the segments.

"This is what makes time travel possible." —Doc Brown In order to travel through time, the vehicle integrated with the flux capacitor needed to be traveling at 88 mph (140.8 km/h), and required 1.21 gigawatts of power (1,210,000,000 watts)

The semgdaq board is a wearable 6 channel data acquisition unit for capturing surface electromyographic (sEMG) signals from human arm muscles using SJ2-3593D jack connectors while conditioning, digitizing, processing and feature extracting them then transmitting the feature data as vectors to an external AI accelerated board through an SM12B-SRSS IDC connector using 12C and UART communication protocals where AI models are run for various applications including robotic control, muscle signals medical assessment and gesture recognition. The feature vectors are comprised of onset detection, slope sign changes, autoregression coefficients and Short Time Fourier Transform magnitude spectrum data for each segment or window of the signals in real time. This vectors can be used as the basis for further feature extraction on more computationally resourceful hardware where machine learning algorthms can be employed for descision making in the applications mentioned earlier. The board leverages INA125P instrumentation amplifiers together with filter stages utilizing LM324QT op-amps for conditioning and an STM32G4A1VET6 microcontroller for the digitization, processing, feature extraction and data transmission. Since AI models can only be as good as the data, the design of such a DAQ is necessary to ensure clean, reliable and real-time data for AI applications requiring sEMG feature data. The board also has USB-FS and JTAG to cater for debugging and external flash memory to extend its data storage and processing capability. The power (5V) is fed through a screw terminal and is regulated by two LDK320AM LDO regulators to offer 5V, 3.3V and 1.8V to meet the requirements of various components on the board.

NodeMCU V3 ESP8266 ESP-12E is WiFi development board that helps you to prototype your IoT product with few Lua script lines, or through Arduino IDE. The board is based on ESP8266 ESP-12E variant, unlike other ESP-12E, you won’t need to buy a separate breakout board, usb to serial adapter, or even solder it to a PCB to get started, you will only need a usb cable (Micro USB).

The Ariel AI Chip, a pioneering component in the realm of artificial intelligence hardware, integrates a suite of electronic elements tailored for high-performance computing applications. At the heart of this assembly lies a CPU with a Radical Transistor architecture, featuring a quad-core setup clocked at 2GHz, identified by the part number CPU-RT-4C-2G. Power management is facilitated through a DC Power Supply, marked DCPS-5V, ensuring a stable 5V supply to the intricate circuitry. The chip's switching capabilities are bolstered by two NPN transistors, NPN-TRANS-001 and NPN-TRANS-002, which play a crucial role in signal modulation. Essential to the chip's operation are the passive components: two 1kΩ resistors (RES-1K and RES-1K-002) and a 10µF capacitor (CAP-10UF), which together with the transistors, form a robust network ensuring reliable performance under varying load conditions. Designed for integration into advanced AI systems, this chip stands out for its innovative use of standard components in a configuration that emphasizes efficiency, reliability, and high-speed data processing capabilities.

The Ariel AI chip prototype, designed for integration with Flux AI for advanced simulation and testing, incorporates a suite of electronic components optimized for high-performance computing applications. At the heart of this system lies a CPU with a radical transistor architecture, featuring a 4-core configuration and a clock speed of 2GHz, identified by part number CPU-RT-4C-2G. Power management is facilitated through a DC Power Supply, specified as DCPS-5V, ensuring a stable 5V supply to the system. The circuit's dynamic performance is modulated by two NPN transistors, NPN-TRANS-001 and NPN-TRANS-002, which, along with precision resistors RES-1K and RES-1K-002 (both 1kΩ), and a 10μF capacitor (CAP-10UF), form the critical signal processing path leading to the CPU. This configuration is designed to provide an efficient, reliable processing environment for AI computations, with an emphasis on minimizing latency and maximizing throughput. The Ariel AI chip's architecture, combining traditional components with an innovative CPU design, offers a versatile platform for developing advanced AI applications, reflecting a significant step forward in computational technology.

A 3-bit counter showcasing digital logic simulation. Input is a sequence of pulses which pass through a logic block to determine the segments.

The Ariel AI Chip, an innovative component designed for high-performance computing applications, integrates a sophisticated array of electronic parts to deliver unparalleled processing capabilities. At the heart of this system is a CPU with a radical transistor architecture, featuring a core count of 4 and a clock speed of 2GHz, identified by its part number CPU-RT-4C-2G. Power management within the chip is efficiently handled by a DC Power Supply, rated at 5V, with the part number DCPS-5V, ensuring stable and reliable operation. The chip's signal processing and amplification needs are addressed through the inclusion of two NPN transistors, with part numbers NPN-TRANS-001 and a similar variant, providing the necessary gain and switching capabilities for complex computational tasks. Signal conditioning is further enhanced by a pair of 1kΩ resistors, RES-1K and RES-1K-002, and a 10µF capacitor, CAP-10UF, which work together to filter and stabilize the power supply and signal pathways, ensuring clean and noise-free operation. This integration of components within the Ariel AI Chip offers electrical engineers a robust platform for developing advanced AI systems, combining high processing power with efficient power management and signal integrity, suitable for a wide range of applications in the field of artificial intelligence.

NodeMCU V3 ESP8266 ESP-12E is WiFi development board that helps you to prototype your IoT product with few Lua script lines, or through Arduino IDE. The board is based on ESP8266 ESP-12E variant, unlike other ESP-12E, you won’t need to buy a separate breakout board, usb to serial adapter, or even solder it to a PCB to get started, you will only need a usb cable (Micro USB).

NodeMCU V3 ESP8266 ESP-12E is WiFi development board that helps you to prototype your IoT product with few Lua script lines, or through Arduino IDE. The board is based on ESP8266 ESP-12E variant, unlike other ESP-12E, you won’t need to buy a separate breakout board, usb to serial adapter, or even solder it to a PCB to get started, you will only need a usb cable (Micro USB).

NodeMCU V3 ESP8266 ESP-12E is WiFi development board that helps you to prototype your IoT product with few Lua script lines, or through Arduino IDE. The board is based on ESP8266 ESP-12E variant, unlike other ESP-12E, you won’t need to buy a separate breakout board, usb to serial adapter, or even solder it to a PCB to get started, you will only need a usb cable (Micro USB).

Power Barrel Connector Jack 2.10mm ID (0.083"), 5.50mm OD (0.217") Through Hole, Right Angle #Barrel_Jack_MountingPin