Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
MAX14676KEVAL#

MAX14676KEVAL#

Maxim Integrated

EVALUATION KIT MAX14676K

0

MAX96943CCOAXEVKIT#

MAX96943CCOAXEVKIT#

Maxim Integrated

EVALUATION KIT COAX MAX96943C

0

DS3106DK

DS3106DK

Maxim Integrated

KIT DEMO FOR DS3106

0

MAX13036EVKIT+

MAX13036EVKIT+

Maxim Integrated

EVAL KIT/SYSTEM MAX13036 (AUTOMO

0

MAX97500EVSYS#

MAX97500EVSYS#

Maxim Integrated

EVAL KIT MAX97500

0

MAX9286S32V234DB#

MAX9286S32V234DB#

Maxim Integrated

MAX9286 DAUGHTER BOARD FOR S23V2

0

MAX16911EVKIT+

MAX16911EVKIT+

Maxim Integrated

KIT EVAL FOR MAX16911

0

MAX14690ADEMBD#

MAX14690ADEMBD#

Maxim Integrated

DEMO BOARD MAX14690A

0

MAX77665AEWQ+T

MAX77665AEWQ+T

Maxim Integrated

INTEGRATED CIRCUIT

0

MAX14931EWEVKIT#

MAX14931EWEVKIT#

Maxim Integrated

EVAL KIT FOR MAX14931

0

MAX1645BEVKIT+

MAX1645BEVKIT+

Maxim Integrated

EVAL KIT MAX1645

0

73S1210F-EB

73S1210F-EB

Maxim Integrated

BOARD EVAL 73S1210F DOC/CD CABLE

0

MAX14936AWEVKIT#

MAX14936AWEVKIT#

Maxim Integrated

EVAL KIT FOR MAX14936

0

MAX14688DEMBD#

MAX14688DEMBD#

Maxim Integrated

HEADSET JACK DETECTION IC WITH A

0

MAX14932ASEVKIT#

MAX14932ASEVKIT#

Maxim Integrated

EVAL KIT FOR MAX14932

0

MAX9406EVKIT+

MAX9406EVKIT+

Maxim Integrated

KIT EVAL FOR MAX9406

0

DS185XK

DS185XK

Maxim Integrated

IC LASER-DRIVER CONTROL 16-CSBGA

0

MAX9225/6EVKIT

MAX9225/6EVKIT

Maxim Integrated

EVALUATION KIT MAX9225/6

0

VT1527SV1EVKIT#

VT1527SV1EVKIT#

Maxim Integrated

EVALUATION KIT VT1527SV1

0

MAX14931BSEVKIT#

MAX14931BSEVKIT#

Maxim Integrated

EVAL KIT FOR MAX14931

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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