Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
MAX3637EVKIT+

MAX3637EVKIT+

Microsemi

KIT EVALUATION MAX MAX3637

0

LE71HR8832G

LE71HR8832G

Microsemi

LINE MODULE VE8830 SM2

0

MAX3636EVKIT+

MAX3636EVKIT+

Microsemi

KIT EVALUATION MAX MAX3636

0

MAX24410EVKIT#

MAX24410EVKIT#

Microsemi

KIT EVALUATION MAX24410

0

PD-IM-7648MH

PD-IM-7648MH

Microsemi

POE EVB

0

DRF1200/CLASS-E_27MHZ

DRF1200/CLASS-E_27MHZ

Microsemi

KIT REF DRF1200 27.12MHZ MOSFET

0

ZLR88821L

ZLR88821L

Microsemi

REFERENCE DESIGN ZL88821L

0

MAX3622EVKIT#

MAX3622EVKIT#

Microsemi

KIT EVALUATION MAX3622

0

PM5463-KIT

PM5463-KIT

Microsemi

8-CH FLASH CONTROLLER PCIEX4 4GB

0

DS31407DK

DS31407DK

Microsemi

KIT DEMO DS31407

0

ZLR966121L

ZLR966121L

Microsemi

REFERENCE DESIGN ZLR966121L

0

MAX9451EVKIT+

MAX9451EVKIT+

Microsemi

KIT EVALUATION MAX MAX9451

0

MAX24210EVKIT#

MAX24210EVKIT#

Microsemi

KIT EVALUATION MAX24210

0

ZLR88621L

ZLR88621L

Microsemi

REFERENCE DESIGN ZL88621L

0

LX1677 EVAL KIT

LX1677 EVAL KIT

Microsemi

KIT EVAL FOR SWITCHING REGULATOR

0

OA3SSQL-E

OA3SSQL-E

Microsemi

EVAL KIT FOR OA3SSQL

0

ZLE38465BADA

ZLE38465BADA

Microsemi

BOARD EVAL VOICE PROCESSOR

0

DRF1200/EVALSW

DRF1200/EVALSW

Microsemi

BOARD EVAL MOSFET HYBRID DRF1200

0

DRF1203/EVALSW

DRF1203/EVALSW

Microsemi

BOARD EVAL MOSFET HYBRID DRF1203

0

LX2208 EVAL KIT

LX2208 EVAL KIT

Microsemi

LINEAR LITHIUM ION

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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