| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC5160 |
38 |
|
 |
EPC |
BOARD DEV FOR EPC8010 100V EGAN |
16 |
|
 |
Texas Instruments |
EVAL BOARD FOR ADS54J60 |
8 |
|
 |
Würth Elektronik Midcom |
ENERGY HARVESTING SOLUTION TO GO |
0 |
|
 |
Epson |
EVAL BOARD S1D13517 |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
BOARD EVAL NCP380HMU05 LOAD SW |
4 |
|
 |
Maxim Integrated |
EVAL KIT MAX77950 WRLS PWR RCR |
2941 |
|
 |
Bellnix Co., LTD. |
CONTACTLESS POWER SUPPLY SET/50W |
3 |
|
 |
Silicon Labs |
SAMPLE PACK SI87XX |
1 |
|
 |
APS |
SCR (THYRISTOR) 3-PHASE CONTROL |
50 |
|
 |
Texas Instruments |
EVAL MODULE FOR TX0202SEA |
0 |
|
 |
Texas Instruments |
EVAL MODULE FOR BQ24018 |
1 |
|
 |
Analog Devices, Inc. |
BOARD EVALUATION FOR ADM1062LF |
3 |
|
 |
STMicroelectronics |
EVAL BOARD FOR L6206N DIP |
1 |
|
 |
Texas Instruments |
EVALUATION MODULE FOR ADS1293 |
8 |
|
 |
STMicroelectronics |
EVALUATION KIT |
0 |
|
 |
TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC2100 |
9 |
|
 |
Roving Networks / Microchip Technology |
BREAKOUT MODULE MCP2210 |
174 |
|
 |
Texas Instruments |
COMPLETE CHARGER EVALUATION MODU |
2 |
|
 |
Wickmann / Littelfuse |
EVALUATION BOARD FOR IX4351 |
1218 |
|
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)