Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
MAX31790EVKIT#

MAX31790EVKIT#

Maxim Integrated

KIT EVAL FOR MAX31790

312

MAX77655EVKIT#

MAX77655EVKIT#

Maxim Integrated

MAX77655 EVALUATION KIT

3

DS3231MEVKIT#

DS3231MEVKIT#

Maxim Integrated

EVAL KIT FOR DS3231M

123

MAX148X2EVKIT#

MAX148X2EVKIT#

Maxim Integrated

EVAL KIT RS-485/RS-422 TXRX

110

MAXFILTERBRD+

MAXFILTERBRD+

Maxim Integrated

BOARD EVAL MAX7408/7415/418-7425

116

MAX4886EVKIT+

MAX4886EVKIT+

Maxim Integrated

KIT EVAL FOR MAX4886

5

MAX14589EEVKIT#

MAX14589EEVKIT#

Maxim Integrated

EVAL KIT MAX14589 (HIGH-DENSITY

49

MAXREFDES7#

MAXREFDES7#

Maxim Integrated

REFERENCE DESIGN LAKEWOOD

17

MAXSANTAFEEVSYS#

MAXSANTAFEEVSYS#

Maxim Integrated

EVAL SYSTEM SANTA FE

4

MAX9892EVKIT+

MAX9892EVKIT+

Maxim Integrated

EVAL BOARD FOR MAX9892

17

MAX17260XEVKIT#

MAX17260XEVKIT#

Maxim Integrated

EVKIT MODEL GAUGE M5 MAX17260

1343

MAXREFDES64#

MAXREFDES64#

Maxim Integrated

REF DES 8CH DGTL-IN MICRO PLC

124

MAX77958EVKIT-2S6#

MAX77958EVKIT-2S6#

Maxim Integrated

MAX77958EVALUATION KIT WITH 6AOU

332

MAX96705COAXEVKIT#

MAX96705COAXEVKIT#

Maxim Integrated

EVAL BOARD FOR MAX96705

312

MAX14913EVKIT#

MAX14913EVKIT#

Maxim Integrated

EV KIT FOR MAX14913

19

MAX25221EVSYS#

MAX25221EVSYS#

Maxim Integrated

EVAL KIT FOR MAX25221

311

MAX40000EVKIT#

MAX40000EVKIT#

Maxim Integrated

EVKIT FOR 600NA COMPARATOR IN UL

41

MAX17301XEVKIT#

MAX17301XEVKIT#

Maxim Integrated

EVAL MAX17301 MODELGAUGE

737

MAX3232PMB1#

MAX3232PMB1#

Maxim Integrated

MODULE PERIPHERAL FOR MAX3232

197219

MAX14880EVKIT#

MAX14880EVKIT#

Maxim Integrated

EVAL MAX14880 TXRX CAN

215

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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