| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB6L295MMN CLK DELAY |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD MOTOR MOD I2C STP DVR NQFP |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FIELDBUS ACCESS UNIT |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NCP370G |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8417CS |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCS36000G |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD H-BRIDGE MOTOR DVR |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LV8746V |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NLAS7222CMUG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCP382HMN10AG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR ECLTSSOP20 |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NCP380LMU15 LOAD SW |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LB11685AVG |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL BBG NB6L239MND |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
THE STR-NIS5020-GEVB PROV |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR NB4N11MD |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT LV8714TAG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NB7L216MN |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVALUATION HART MODEM QFN |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
FUSB302 AND NCV81599 USB- |
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)