Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
CP2101EK

CP2101EK

Silicon Labs

KIT DEVELOPMENT RS232 TO USB

0

USB-MSD-RD

USB-MSD-RD

Silicon Labs

KIT REF DES USB MASS STORAGE

0

ETHERNETDK

ETHERNETDK

Silicon Labs

KIT DEV EMBEDDED ETHERNET

0

CP2400AB

CP2400AB

Silicon Labs

BOARD EVAL SPI LCD DRIVER CP2400

0

DTMFDECODER-RD

DTMFDECODER-RD

Silicon Labs

KIT REF DESIGN DTMF DECODER

0

CP2401AB

CP2401AB

Silicon Labs

BOARD EVAL I2C LCD DRIVER CP2401

0

TS4102DB

TS4102DB

Silicon Labs

EVAL BOARD FOR TS4102

0

TEMPCOMPRTC-RD

TEMPCOMPRTC-RD

Silicon Labs

KIT REF DES TEMP COMPENS RTC

0

SI50122-A6-EVB

SI50122-A6-EVB

Silicon Labs

EVAL BOARD FOR SI50122-A6

0

SI535X-20QFN-EVB

SI535X-20QFN-EVB

Silicon Labs

EVALUATION BOARD FOR SI535X

0

SI5XX-PROG-EVB

SI5XX-PROG-EVB

Silicon Labs

KIT EVALUATION FOR SI5XX

0

VOICE-RECORD-RD

VOICE-RECORD-RD

Silicon Labs

KIT REF DESIGN VOICE RECORD F41X

0

SI5382E-E-EVB

SI5382E-E-EVB

Silicon Labs

EVALUATION BOARD KIT

0

SI3216MDCQ1-EVB

SI3216MDCQ1-EVB

Silicon Labs

DAUGHTER CARD W/SI3201 INTERFACE

0

SI3220DC0-EVB

SI3220DC0-EVB

Silicon Labs

DAUGHTER CARD W/SI3200 INTERFACE

0

SI3056PPT-EVB

SI3056PPT-EVB

Silicon Labs

BOARD EVAL FOR DAA SI3056/SI3018

0

SI3056DC1-EVB

SI3056DC1-EVB

Silicon Labs

DAUGHTERCARD DAA SI3056/SI3019

0

SMARTPSE24-KIT

SMARTPSE24-KIT

Silicon Labs

KIT EVAL REF 24PORT SPI/UART

0

SI3245MB5-EVB

SI3245MB5-EVB

Silicon Labs

BOARD EVAL W/SI3205 INTERFACE

0

SI3217XCFB21IK0EVB

SI3217XCFB21IK0EVB

Silicon Labs

BOARD EVAL 2FXS1FXO PCM

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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