Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
VT505EVKIT#

VT505EVKIT#

Maxim Integrated

EVAL KIT FOR VT505EV

0

MAX14745EVKIT#

MAX14745EVKIT#

Maxim Integrated

EVAL KIT MAX14745 BATTERY CHRG

1313

MAX9286ATHENA10DB#

MAX9286ATHENA10DB#

Maxim Integrated

MAX9286 DAUGHTER BOARD THAT PAIR

0

MAX14578AEVKIT#

MAX14578AEVKIT#

Maxim Integrated

EVAL KIT MAX14578A (USB BATTERY

12

MAX40027EVKIT#

MAX40027EVKIT#

Maxim Integrated

EVAL KIT MAX40027

312

MAX5387EVKIT+

MAX5387EVKIT+

Maxim Integrated

EVAL KIT MAX5387 (DUAL, 256-TAP,

15

MAX1538EVKIT

MAX1538EVKIT

Maxim Integrated

EVAL KIT MAX1538 (POWER-SOURCE S

8

MAX9277COAXEVKIT#

MAX9277COAXEVKIT#

Maxim Integrated

EVKIT OF SERIALIZER WITH SERIAL

10

MAXREFDES177#

MAXREFDES177#

Maxim Integrated

IO-LINK CONFIGURABLE ANALOG IO

410

DS2488EVKIT#

DS2488EVKIT#

Maxim Integrated

DS2488 EVALUATION SYSTEM

221

MAX77962EVKIT-06#

MAX77962EVKIT-06#

Maxim Integrated

EVALUATION KIT FOR 23VIN, 3.2AOU

236

MAX1758EVKIT+

MAX1758EVKIT+

Maxim Integrated

MAX1758 EVAL KIT+

15

MAX15093AEVKIT#

MAX15093AEVKIT#

Maxim Integrated

EVAL MAX15093A EFUSE

342

MAX9647EVKIT#

MAX9647EVKIT#

Maxim Integrated

KIT EVAL FOR MAX9647

25

MAX2982EVSYS

MAX2982EVSYS

Maxim Integrated

EVALUATION SYSTEM FOR INDUSTRIAL

32

MAX5977AEVKIT#

MAX5977AEVKIT#

Maxim Integrated

EVAL KIT MAX5977A

9

MAX7311EVKIT+

MAX7311EVKIT+

Maxim Integrated

EVAL KIT MAX7311 (2-WIRE-INTERFA

7

MAX9275COAXEVKIT#

MAX9275COAXEVKIT#

Maxim Integrated

EVKIT FOR SERIALIZER WITH PARALL

12

MAX1455EVKIT-NS

MAX1455EVKIT-NS

Maxim Integrated

EVAL KIT FOR MAX1455

48

MAX31328SHLD#

MAX31328SHLD#

Maxim Integrated

EVKIT FOR INTEGRATED DS3231SN W/

334

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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