| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Intersil (Renesas Electronics America) |
ISL91211A ZYNQ-7000 REF BRD |
5 |
|
 |
Intersil (Renesas Electronics America) |
DEMO BOARD FOR HIP4081A |
11 |
|
 |
Intersil (Renesas Electronics America) |
BOARD EVAL FOR ISL61861 |
0 |
|
 |
Intersil (Renesas Electronics America) |
BOARD EVAL FOR ISL6146 |
1 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD ISL6115 |
0 |
|
 |
Intersil (Renesas Electronics America) |
STARTER KIT EVAL F/U/W ISL28025 |
0 |
|
 |
Intersil (Renesas Electronics America) |
ISL94216 EVAL KIT |
13 |
|
 |
Intersil (Renesas Electronics America) |
HIP2211 8 LD SOIC EVAL BOARD |
4 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD 1 FOR ISL88001/2/3 |
0 |
|
 |
Intersil (Renesas Electronics America) |
EVALUATION BOARD FOR ISL54220 |
0 |
|
 |
Intersil (Renesas Electronics America) |
MOTHRBRD FOR KAD27,KAD55,KAD56 |
1 |
|
 |
Intersil (Renesas Electronics America) |
KIT EVALUATION ISL94203 |
0 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL12020MIRZ |
5 |
|
 |
Intersil (Renesas Electronics America) |
ISL94202 EVAL KIT |
11 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BRD ISL9237 |
0 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD FOR TW9900-NA1-GR |
0 |
|
 |
Intersil (Renesas Electronics America) |
BOARD EVAL FOR ISL6146 |
3 |
|
 |
Intersil (Renesas Electronics America) |
EVAL BOARD FOR ISL61851 |
0 |
|
 |
Intersil (Renesas Electronics America) |
BOARD EVAL HIP2103_4 |
0 |
|
 |
Intersil (Renesas Electronics America) |
BOARD EVAL ACTIVE BALUN ISL55210 |
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)