| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Sanyo Semiconductor/ON Semiconductor |
KIT EVAL FOR BR262CPP01G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT 3 PHASE HYBRID INVERTER |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD LV56801PG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD STK5Q4U352JG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV3319PM |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT 3 PHASE HYBRID INVERTER |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT LV8726TAG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCP338FCCT2G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NCV7708AG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD BIDIR MOTOR DRIVER |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL LV8075LP MOTOR DRIVER |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCN5192G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR XOCLCC6 |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCV73830V1G |
0 |
|
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Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR NCN5120 |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD DEMO NCP1631 INTERLEAV PFC |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD DAUGHTER I2C STEP DVR NQFP |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD STK673-011G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
DEMO BOARD FOR 2.2 V USB |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD |
0 |
|
Evaluation and Demonstration Boards and Kits are hardware platforms designed to facilitate the development, testing, and demonstration of electronic systems. They serve as critical tools for engineers and developers to prototype applications, validate designs, and accelerate time-to-market. These boards integrate processors, sensors, communication interfaces, and software ecosystems, enabling rapid experimentation across diverse industries such as IoT, automotive, and industrial automation.
| Type | Functional Features | Application Examples |
|---|---|---|
| Microcontroller Development Boards | Embedded CPUs, GPIOs, integrated peripherals | IoT devices, robotics |
| FPGA Evaluation Boards | Reconfigurable logic, high-speed interfaces | Communication systems, AI accelerators |
| Sensor Expansion Kits | Multi-sensor integration (temperature, motion, etc.) | Smart agriculture, environmental monitoring |
| Wireless Communication Modules | Bluetooth/Wi-Fi/LoRa protocols, antenna interfaces | Connected healthcare, smart cities |
Typical architecture includes: - Processing Units: Microcontrollers, FPGAs, or SoCs - Memory: RAM, Flash, EEPROM - Interfaces: USB, UART, SPI, I2C, Ethernet - Power Management: Regulators, battery connectors - Software Stack: SDKs, device drivers, IDEs Physical designs often feature standardized form factors (e.g., Arduino Uno, Raspberry Pi HATs) for modular expansion.
| Parameter | Description |
|---|---|
| Processor Performance (MHz/GHz) | Determines computational capability |
| Memory Capacity (RAM/Flash) | Affects program complexity and data storage |
| Interface Types | Dictates peripheral compatibility |
| Power Consumption (mW/MHz) | Critical for battery-operated devices |
| Operating Temperature (-40 C to +85 C) | Defines environmental durability |
- Internet of Things (IoT): Smart home controllers, edge AI nodes - Automotive: ADAS sensor fusion platforms - Industrial Automation: PLC controllers, predictive maintenance systems - Consumer Electronics: Wearables, AR/VR prototypes
| Manufacturer | Representative Products |
|---|---|
| STMicroelectronics | STM32 Nucleo Series, SensorTile Kit |
| Intel | Intel Edison, Movidius Neural Compute Stick |
| Xilinx | Zynq UltraScale+ MPSoC Evaluation Kit |
| Arduino | Arduino MKR Series, Nano 33 IoT |
Key considerations: 1. Match processor capabilities to application complexity 2. Verify interface compatibility with target peripherals 3. Assess software ecosystem maturity (e.g., ROS support) 4. Evaluate power budget requirements 5. Consider long-term availability and community support
- Growing adoption of RISC-V-based evaluation platforms - Integration of AI/ML accelerators in edge computing boards - Expansion of open-source hardware ecosystems - Increased focus on energy-efficient architectures for IoT - Standardization of form factors (e.g., SparkFun's Qwiic system)