Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
MAX5386MEVKIT+

MAX5386MEVKIT+

Maxim Integrated

EVAL KIT MAX5386

10

MAX7322EVCMAXQU+

MAX7322EVCMAXQU+

Maxim Integrated

EVAL KIT/SYSTEM MAX7322 (PORT EX

5

MAX79356CAEVK1#

MAX79356CAEVK1#

Maxim Integrated

EVAL KIT FOR MAX79356

13

MAX20801CEVKIT#

MAX20801CEVKIT#

Maxim Integrated

EVALUATION KIT: MPP TRACKING DC-

11

MAXREFDES211#

MAXREFDES211#

Maxim Integrated

IIOT PLATFORM W/APP PROCESSOR CA

312

MAX5961EVKIT+

MAX5961EVKIT+

Maxim Integrated

KIT EVAL FOR MAX5961

6

MAX14741EVKIT#

MAX14741EVKIT#

Maxim Integrated

EVKIT FOR SMART, COMPACT, 6A, PO

6

MAX8677AEVKIT+

MAX8677AEVKIT+

Maxim Integrated

EVAL KIT MAX8677A (1.5A DUAL-INP

5

MAX1455EVKIT-CS

MAX1455EVKIT-CS

Maxim Integrated

EVAL KIT FOR MAX1455

9

MAX13235EEVKIT+

MAX13235EEVKIT+

Maxim Integrated

EVAL KIT MAX13235 (3MBPS RS-232

42

MAX8904EVKIT+

MAX8904EVKIT+

Maxim Integrated

EVAL KIT MAX8904 (PMIC FOR 2-CEL

8

MAX4899AEEVKIT+

MAX4899AEEVKIT+

Maxim Integrated

EVALUATION KIT FOR THE MAX4899AE

9

MAX17048EVKIT#

MAX17048EVKIT#

Maxim Integrated

EVAL KIT MAX17048 (HOST-SIDE MOD

9

MAX16971EVKIT#

MAX16971EVKIT#

Maxim Integrated

EVALUATION KIT FOR 3A AUTOMOTIVE

20

MAX8814EVKIT+

MAX8814EVKIT+

Maxim Integrated

KIT EVAL FOR MAX8814

14

MAX3535EEVKIT+

MAX3535EEVKIT+

Maxim Integrated

EVAL KIT MAX3535E

45

MAX9293BCOAXEVKIT#

MAX9293BCOAXEVKIT#

Maxim Integrated

EVKIT GMSL SERIALIZER FOR COAX &

22

MAX20332EVKIT#

MAX20332EVKIT#

Maxim Integrated

EVAL MAX20332 USB CHARGE

236

DS2710EVKIT+

DS2710EVKIT+

Maxim Integrated

EVAL KIT DS2710 (SINGLE-CELL NIM

25

MAX9017AEVKIT#

MAX9017AEVKIT#

Maxim Integrated

EVKIT OF DUAL, PRECISION, 1.8V,

10

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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