| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Wolfspeed - a Cree company |
EVAL MODULE 1200V SIC MOSFET |
14 |
|
 |
Wolfspeed - a Cree company |
EVAL FXTR G2 1.2KV 45MM SIX-PK P |
12 |
|
 |
Wolfspeed - a Cree company |
EVAL BOARD 1200V SIC BRIDGE GATE |
0 |
|
 |
Wolfspeed - a Cree company |
SIC MOSFET ISOLATED GATE DRIVER |
5 |
|
 |
Wolfspeed - a Cree company |
GATE DRIVER, FOR 1.2KV, HM3 HIGH |
0 |
|
 |
Wolfspeed - a Cree company |
GATE DRIVER 1.2KV, 325A |
0 |
|
 |
Wolfspeed - a Cree company |
EVAL BOARD FOR C3M0120090J |
0 |
|
 |
Wolfspeed - a Cree company |
EVAL BOARD 1700V SIC BRIDGE GATE |
0 |
|
 |
Wolfspeed - a Cree company |
300 KW INVERTER KIT FOR XM3 CPM3 |
7 |
|
 |
Wolfspeed - a Cree company |
650V SIC FET BUCK-BOOST EVAL KIT |
2 |
|
 |
Wolfspeed - a Cree company |
DOUBLE PULSE DYNAMIC EVAL BOARD |
0 |
|
 |
Wolfspeed - a Cree company |
EVAL KIT PCB 2-MOSFET 2-SIC DRVR |
0 |
|
 |
Wolfspeed - a Cree company |
GATE DRVR 150C FOR 1.2KV 325A HI |
139 |
|
 |
Wolfspeed - a Cree company |
DOUBLE PULSE DYNAMIC EVAL BOARD |
0 |
|
 |
Wolfspeed - a Cree company |
EVAL MODULE 1200V SIC MOSFET |
12 |
|
|
Wolfspeed - a Cree company |
EVAL KIT FOR SIC MOSFET |
2 |
|
|
Wolfspeed - a Cree company |
250KW XM3 3PHASE INVERTER |
0 |
|
|
Wolfspeed - a Cree company |
CAB400M12XM3 SIC MODULE DEV KIT |
0 |
|
 |
Wolfspeed - a Cree company |
EVAL BOARD 1200V SIC MOSFET MOD |
0 |
|
 |
Wolfspeed - a Cree company |
BOARD EVAL ISOL SIC GATE DRIVER |
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)