| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
APS |
SCR (THYRISTOR) 3-PHASE CONTROL |
50 |
|
 |
Maxim Integrated |
EVAL MAX22501 RS485/RS422 |
86 |
|
 |
STMicroelectronics |
BOARD EVAL 1-PH BASED ON STPM33 |
3 |
|
 |
Maxim Integrated |
KIT EVALUATION FOR MAX14970 |
19 |
|
 |
APS |
SCR (THYRISTOR) 1-PHASE CONTROL |
50 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR ADE7880 |
6 |
|
 |
Seeed |
HEELIGHT CORE |
0 |
|
 |
STMicroelectronics |
EVAL BRD FLIGHT CONTROLLER DRONE |
0 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPS2491-002 |
5 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR LTC4257-1 |
1 |
|
 |
ams |
EVAL KIT SQUIGGLE MOTOR + SENSOR |
7 |
|
 |
SparkFun |
SPARKFUN PRODRIVER - STEPPER MOT |
57 |
|
 |
Texas Instruments |
EVAL BOARD FOR LDC2114 |
31 |
|
 |
STMicroelectronics |
VNH7100BAS EVALUATION BOARD |
0 |
|
 |
Maxim Integrated |
REFERENCE DESIGN CORONA |
173 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR AD7195 |
6 |
|
 |
STMicroelectronics |
VN7000AY EVALUATION BOARD |
10 |
|
 |
GLF Integrated Power |
GLF71303 EVB |
5 |
|
 |
STMicroelectronics |
MOTOR CONTROL SOLUTION EVAL BOAR |
11 |
|
 |
Analog Devices, Inc. |
BOARD EVAL FOR LTC4098EPDC |
2 |
|
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)