Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
XR21B1422IL40-0A-EVB

XR21B1422IL40-0A-EVB

MaxLinear

EVAL BOARD FOR XR21B1422IL40

4

XRA1404IG16-0B-EB

XRA1404IG16-0B-EB

MaxLinear

GPIO EXPANDER EVAL BOARD

4

SP337EBET-0A-EB

SP337EBET-0A-EB

MaxLinear

BOARD EVALUATION FOR SP337EBET

2

XR33053IDEVB

XR33053IDEVB

MaxLinear

EVAL BOARD FOR XR33053

4

XR21V1410IL-0A-EB

XR21V1410IL-0A-EB

MaxLinear

EVAL BOARD FOR XR21V1410IL

0

XRA1402IG16-0B-EB

XRA1402IG16-0B-EB

MaxLinear

GPIO EXPANDER EVAL BOARD

0

XRP2527EVB

XRP2527EVB

MaxLinear

BOARD EVAL POWER SWITCH XRP2527

3

XRA1403IL24-0B-EB

XRA1403IL24-0B-EB

MaxLinear

GPIO EXPANDER EVAL BOARD

0

SP337EBEY-0A-EB

SP337EBEY-0A-EB

MaxLinear

BOARD EVALUATION FOR SP337EBEY

1

XR20M1280L40-0A-EB

XR20M1280L40-0A-EB

MaxLinear

EVAL BOARD FOR XR20M1280L40

1

XR21V1410IL-0C-EB

XR21V1410IL-0C-EB

MaxLinear

EVAL BOARD FOR XR21V1410IL

33

XR33183ESBEVB

XR33183ESBEVB

MaxLinear

EVAL BRD FOR XR33183

4

XR22417CV64EVB

XR22417CV64EVB

MaxLinear

EVAL BOARD FOR ZR22417 64-LQFP

3

XR33058IDEVB

XR33058IDEVB

MaxLinear

EVAL BOARD FOR XR33058I

0

XR21V1412IL-0B-EB

XR21V1412IL-0B-EB

MaxLinear

EVAL BOARD FOR XR21V1412IL

0

XR10910IL40EVB

XR10910IL40EVB

MaxLinear

EVALUATION BOARD FOR XR10910

2

XR21V1414IM-0B-EB

XR21V1414IM-0B-EB

MaxLinear

EVAL BOARD FOR XR21V1414

2

RD-HNPH2DCP962KIT-01

RD-HNPH2DCP962KIT-01

MaxLinear

DCP962P PHONE LINE/TP EVAL KIT

2

XR34350ILEVB

XR34350ILEVB

MaxLinear

EVAL BOARD FOR XR34350

1

XRA1405IL24-0B-EB

XRA1405IL24-0B-EB

MaxLinear

GPIO EXPANDER EVAL BOARD

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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