Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
DS28C36EVKIT#

DS28C36EVKIT#

Maxim Integrated

EVAL KIT DS28C36Q+U

19

MAXREFDES34#

MAXREFDES34#

Maxim Integrated

REFERENCE DESIGN ALCATRAZ

212

MAX98089EVKIT#TQFN

MAX98089EVKIT#TQFN

Maxim Integrated

KIT EVAL FOR MAX98089-TQFN

19

MAXREFDES143#

MAXREFDES143#

Maxim Integrated

DEEPCOVER EMBEDDED SECURITY IOT

156

MAX11300PMB1#

MAX11300PMB1#

Maxim Integrated

EVAL MODULE FOR MAX11300

1224

MAXREFDES38#

MAXREFDES38#

Maxim Integrated

LOW POWER CURRENT FAULT SENSOR

225

MAXM86146EVSYS#

MAXM86146EVSYS#

Maxim Integrated

EVKIT FOR EMBEDDED PPG

10100

DS28S60EVKIT#

DS28S60EVKIT#

Maxim Integrated

DS28S60 EVALUATION SYSTEM

318

MAX22192EVKIT#

MAX22192EVKIT#

Maxim Integrated

EVALUATION KIT FOR OCTAL INDUSTR

118

MAX17262XEVKIT#

MAX17262XEVKIT#

Maxim Integrated

KIT FOR MAX17262

1232

MAX274EVKIT-DIP+

MAX274EVKIT-DIP+

Maxim Integrated

KIT EVALUATION FOR MAX274

270

MAX11300EVKIT#

MAX11300EVKIT#

Maxim Integrated

EVAL KIT FOR MAX11300

69

MAX5487PMB1#

MAX5487PMB1#

Maxim Integrated

MODULE PERIPHERAL FOR MAX5487

9165

MAX20330EVKIT#

MAX20330EVKIT#

Maxim Integrated

KIT MAX20330 OVERVOLTAGE PROT

12

MAX2202XEVKIT#

MAX2202XEVKIT#

Maxim Integrated

EV KIT FOR COMPACT, ISOLATED HAL

314

MAXREFDES39#

MAXREFDES39#

Maxim Integrated

REF DESIGN PA BIASING/MONITORING

10

MAX9276ACOAXEVKIT#

MAX9276ACOAXEVKIT#

Maxim Integrated

EVAL KIT FOR MAX9276

113

DS28C39EVKIT#

DS28C39EVKIT#

Maxim Integrated

DS28C39 EVALUATION SYSTEM

530

MAX1640EVKIT

MAX1640EVKIT

Maxim Integrated

EVAL KIT MAX1640, MAX1641

35

MAXREFDES63#

MAXREFDES63#

Maxim Integrated

REF DES 8CH DGTL-OUT MICRO PLC

129

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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