Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
SI5395E-A-EVB

SI5395E-A-EVB

Silicon Labs

BOARD EVALUATION SI5395

4

CP2130EK

CP2130EK

Silicon Labs

KIT EVALUATION CP2130

33

SI5XXUC-EVB

SI5XXUC-EVB

Silicon Labs

XO & VCXO UNIVERSAL EVAL BOARD

43

SI5395J-A-EVB

SI5395J-A-EVB

Silicon Labs

BOARD EVALUATION SI5395

8

CP2105EK

CP2105EK

Silicon Labs

KIT EVAL FOR CP2105

17

SI5391A-A-EVB

SI5391A-A-EVB

Silicon Labs

SI5391 EVALUATION KIT

0

SI5392J-A-EVB

SI5392J-A-EVB

Silicon Labs

BOARD EVALUATION SI5392

1

SI3050E1EG01SL1KIT

SI3050E1EG01SL1KIT

Silicon Labs

SI3050/SI3019 QFN GLOBAL VOICE D

0

SI32261CFB20SL0EVB

SI32261CFB20SL0EVB

Silicon Labs

BOARD EVAL 2FXS PCM SI32261-C

0

SI5346-EVB

SI5346-EVB

Silicon Labs

EVAL BOARD SI5346 CLOCK GEN

0

SI2418FT18-EVB

SI2418FT18-EVB

Silicon Labs

BOARD EVAL SI2418+SI3018 24PIN

0

SI3210MPPQX-EVB

SI3210MPPQX-EVB

Silicon Labs

BOARD EVAL W/DISCRETE INTERFACE

0

SI5381A-E-EVB

SI5381A-E-EVB

Silicon Labs

EVALUATION BOARD KIT SI5381A

0

SI32260CQS20SL0EVB

SI32260CQS20SL0EVB

Silicon Labs

BOARD EVAL 2FXS PCM SI32260-C

0

SI5332-6IX-EVB

SI5332-6IX-EVB

Silicon Labs

6-OUTPUT SI5332 CUSTOMER EVAL KI

2

SI5332-8IX-EVB

SI5332-8IX-EVB

Silicon Labs

8-OUTPUT SI5332 CUSTOMER EVAL KI

3

SI32266CQC20SL0EVB

SI32266CQC20SL0EVB

Silicon Labs

BOARD EVAL 2FXS ISI SI32266-C

0

SI32172CQC10SL0EVB

SI32172CQC10SL0EVB

Silicon Labs

BOARD EVAL 1FXS ISI SI32172-C

0

SI32261CUB20SL0KIT

SI32261CUB20SL0KIT

Silicon Labs

2FXS PCM EVALUATION KIT FOR SI32

0

SI2493-D-FS18-EVB

SI2493-D-FS18-EVB

Silicon Labs

BOARD EVAL ISOMODEM 16PIN

0

Evaluation and Demonstration Boards and Kits

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.

TypeFunctional FeaturesApplication Examples
Microcontroller Development BoardsEmbedded CPUs, GPIOs, integrated peripheralsIoT devices, robotics
FPGA Evaluation BoardsReconfigurable logic, high-speed interfacesCommunication systems, AI accelerators
Sensor Expansion KitsMulti-sensor integration (temperature, motion, etc.)Smart agriculture, environmental monitoring
Wireless Communication ModulesBluetooth/Wi-Fi/LoRa protocols, antenna interfacesConnected 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.

ParameterDescription
Processor Performance (MHz/GHz)Determines computational capability
Memory Capacity (RAM/Flash)Affects program complexity and data storage
Interface TypesDictates 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

ManufacturerRepresentative Products
STMicroelectronicsSTM32 Nucleo Series, SensorTile Kit
IntelIntel Edison, Movidius Neural Compute Stick
XilinxZynq UltraScale+ MPSoC Evaluation Kit
ArduinoArduino 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)

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