| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Nuvoton Technology Corporation America |
BOARD DEMO FOR ISD1620 |
35 |
|
 |
EPC |
BOARD DEV EPC2015C 40V EGAN |
8 |
|
 |
Roving Networks / Microchip Technology |
AUTOMOTIVE NETWORKING DEVELOPMEN |
3 |
|
 |
Maxim Integrated |
REFERENCE DESIGN ALCATRAZ |
212 |
|
 |
Analog Devices, Inc. |
ADP5091-2 EVALUATION BOARD |
32 |
|
 |
Texas Instruments |
EVAL MODULE FOR BQ24038 |
1 |
|
 |
IR (Infineon Technologies) |
EVAL-IMM101T-046 IS A STARTER KI |
16 |
|
 |
Maxim Integrated |
KIT EVAL FOR MAX98089-TQFN |
19 |
|
 |
Texas Instruments |
EVAL MODULE FOR BQ24072 |
2 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD ISL6115 |
0 |
|
 |
Sanyo Semiconductor/ON Semiconductor |
EVAL BOARD H-BRIDGE MOTOR DVR |
0 |
|
 |
Roving Networks / Microchip Technology |
ATMXT288UD-I2C-PCB DEV BOARD |
3 |
|
 |
Texas Instruments |
EVAL BOARD FOR BQ76942 |
13 |
|
 |
Analog Devices, Inc. |
LTC4079 DEMO BOARD 2.7V-60VIN, 2 |
15 |
|
 |
PCB FOR TI-BASED REF DES PMP5098 |
50 |
|
|
 |
STMicroelectronics |
45W USB TYPE-C POWER DELIVERY 3 |
0 |
|
 |
CEL (California Eastern Laboratories) |
USB REDRIVER WITH USB-UB RECEPTA |
8 |
|
 |
IR (Infineon Technologies) |
EVAL IGBT 1200V |
0 |
|
 |
Texas Instruments |
EVAIL MOD |
1 |
|
 |
Analog Devices, Inc. |
EVAL BOARD FOR ADM8611 |
1 |
|
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)