Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
MAX17610EVKIT#

MAX17610EVKIT#

Maxim Integrated

EVAL KIT OVP/OVC 1A MAX17610

28

MAXNANOPWRBD#

MAXNANOPWRBD#

Maxim Integrated

EVAL NANOPOWER & MEASUREMENT

771

MAX9814EVKIT+

MAX9814EVKIT+

Maxim Integrated

EVALUATION KIT FOR MAX9814

1022

MAX2244XWEVKIT#

MAX2244XWEVKIT#

Maxim Integrated

EVAL MAX2244 DGTL ISO 4CH 10KV

26

MAX1493XSEVKIT#

MAX1493XSEVKIT#

Maxim Integrated

EVAL KIT MAX14930-33 SOIC N

107

DS28E25EVKIT#

DS28E25EVKIT#

Maxim Integrated

EVAL KIT FOR DS28E25

851

MAXREFDES9#

MAXREFDES9#

Maxim Integrated

REFERENCE DESIGN OCEANSIDE

19

MAXREFDES11#

MAXREFDES11#

Maxim Integrated

REFERENCE DESIGN FRESNO

63

DS1086LPMB1#

DS1086LPMB1#

Maxim Integrated

MODULE PERIPHERAL FOR DS1086L

126

MAX38886EVKIT#

MAX38886EVKIT#

Maxim Integrated

A SUPER CAP BACK-UP REGULATOR DE

248

MAX5976BEVKIT+

MAX5976BEVKIT+

Maxim Integrated

EVAL KIT MAX5976B

8

MAX20087EVKIT#

MAX20087EVKIT#

Maxim Integrated

QUAD AUTOMOTIVE CAMERA MODULE PR

213

MAX8601EVKIT

MAX8601EVKIT

Maxim Integrated

EVAL BOARD FOR MAX8601

28

MAX40001EVKIT#

MAX40001EVKIT#

Maxim Integrated

EVAL KIT FOR MAX40001

19

MAX15093EVKIT#

MAX15093EVKIT#

Maxim Integrated

EVAL MAX15093 EFUSE

312

DS28E39EVKIT#

DS28E39EVKIT#

Maxim Integrated

EVAL DS28E39 AUTHENTICATOR

1167

MAX20330AEVKIT#

MAX20330AEVKIT#

Maxim Integrated

EVAL MAX20330

15

MAX14986EVKIT#

MAX14986EVKIT#

Maxim Integrated

KIT EVALUATION FOR MAX14986

18

MAX9258AEVKIT#

MAX9258AEVKIT#

Maxim Integrated

EVAL KIT MAX9257A, MAX9258A

16

MAX22192EVSYS#

MAX22192EVSYS#

Maxim Integrated

EVAL KIT W/MAX22192EVKIT#/USB2PM

19

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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