Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
XR20M1280L24-0A-EB

XR20M1280L24-0A-EB

MaxLinear

EVAL BOARD FOR XR20M1280

0

XRP2528EVB

XRP2528EVB

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BOARD EVAL POWER SWITCH XRP2528

3

XR22414CV48EVB

XR22414CV48EVB

MaxLinear

XR22414 LQFP EVAL BRD

2

XR33156IDEVB

XR33156IDEVB

MaxLinear

EVAL BOARD FOR XR33156

1

XR21V1410IL-0B-EB

XR21V1410IL-0B-EB

MaxLinear

EVAL BOARD FOR XR21V1410IL

0

XRP2525EVB

XRP2525EVB

MaxLinear

BOARD EVAL POWER SWITCH XRP2525

1

XR20M1280L32-0B-EB

XR20M1280L32-0B-EB

MaxLinear

EVAL BOARD FOR XR20M1280L32

0

XR33052IDEVB

XR33052IDEVB

MaxLinear

EVAL BOARD FOR XR33052I

3

XR31235EDEVB

XR31235EDEVB

MaxLinear

EVAL BOARD FOR XR31235ED

2

XR33181ESBEVB

XR33181ESBEVB

MaxLinear

EVAL BRD FOR XR33181

4

XR20M1170G24-0A-EB

XR20M1170G24-0A-EB

MaxLinear

EVAL BOARD FOR XR20M1170 24TSSOP

2

SP330EEY-0A-EB

SP330EEY-0A-EB

MaxLinear

EVAL BOARD TXRX RS232/485

5

XR33152EVB

XR33152EVB

MaxLinear

EVAL BOARD FOR XR33152

2

XR20M1280L32-0A-EB

XR20M1280L32-0A-EB

MaxLinear

EVAL BOARD FOR XR20M1280L32

0

SP337EUET-0A-EB

SP337EUET-0A-EB

MaxLinear

EVALUATION BOARD FOR SP337EUET

1

XR20M1172G28-0B-EB

XR20M1172G28-0B-EB

MaxLinear

EVAL BOARD FOR XR20M1172 28TSSOP

5

XR16M890IL32-0C-EB

XR16M890IL32-0C-EB

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BOARD EVAL XR16M890IL32

4

XR21B1411IL-0A-EB

XR21B1411IL-0A-EB

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EVAL BOARD UART SR21B1411

0

XRA1403IG24-0B-EB

XRA1403IG24-0B-EB

MaxLinear

GPIO EXPANDER EVAL BOARD

0

XR21B1420IL28-0A-EVB

XR21B1420IL28-0A-EVB

MaxLinear

EVAL BOARD FOR XR21B1420IL28

3

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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