| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL BBG NB6N239SMN |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NCP1096 POE-PD |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT NCV74300V3G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
CUSTOMER EVALUATION BRD |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NCN1154MUT USB SWITCH |
2 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT NCV74300V1G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL LOAD SWITCH NCP382 |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NCP380HSN05 LOAD SW |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR NCP348G |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB3N3020 CLOCK MULT |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL 13 MP CO-PROCESSOR 12 |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB6L295MN CLK DELAY |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD LC709203FQH 8VDFN |
8 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR LV8548MC |
10 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD FOR LB1939T |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD PWR BANK CTLR LC70 |
3 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD NCP336FCT2G |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL FOR LB1836M |
1 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL KIT LV8121VG |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NB3N5573 CLOCK GEN |
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)