Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
127900-HMC807LP6CE

127900-HMC807LP6CE

Analog Devices, Inc.

KIT EVAL HMC807LP6CE

0

EVAL-RS485FDEBZ

EVAL-RS485FDEBZ

Analog Devices, Inc.

BOARD EVALUATION RS485

2

EVAL-ADUCM350EBZ

EVAL-ADUCM350EBZ

Analog Devices, Inc.

EVAL KIT ADUCM350

3

AD9670EBZ

AD9670EBZ

Analog Devices, Inc.

BOARD EVAL FOR AD9670

0

EVAL-AD5116EBZ

EVAL-AD5116EBZ

Analog Devices, Inc.

BOARD EVAL FOR AD5116

0

127832-HMC836LP6CE

127832-HMC836LP6CE

Analog Devices, Inc.

EVAL BOARD HMC836LP6CE

0

DC2180A

DC2180A

Analog Devices, Inc.

EVAL BOARD FOR LTC437

1

DC1068A

DC1068A

Analog Devices, Inc.

BOARD EVAL FOR LTC3550EDHC

2

EVAL-ADM1170EBZ

EVAL-ADM1170EBZ

Analog Devices, Inc.

BOARD EVALUATION FOR ADM1170

3

DC590B

DC590B

Analog Devices, Inc.

BOARD DEMO USB SERIAL CONTROLLER

233

DC740A-C

DC740A-C

Analog Devices, Inc.

EVAL BOARD FOR LTC2922IF

3

EVAL-AD5941BATZ

EVAL-AD5941BATZ

Analog Devices, Inc.

EVAL KIT - BATTERY IMPEDENCE

25

EKIT01-HMC987LP5E

EKIT01-HMC987LP5E

Analog Devices, Inc.

KIT EVAL FOR HMC987

1

EV-AD74412RSDZ

EV-AD74412RSDZ

Analog Devices, Inc.

EVALUATION BOARD

16

DC510A

DC510A

Analog Devices, Inc.

BOARD EVAL FOR LTC1697EMS

1

128157-HMC820LP6CE

128157-HMC820LP6CE

Analog Devices, Inc.

EVAL BOARD HMC820LP6CE

1

EVAL-ADN2850SDZ

EVAL-ADN2850SDZ

Analog Devices, Inc.

BOARD EVAL FOR ADN2850SDZ

0

DC1959A-C

DC1959A-C

Analog Devices, Inc.

DEMO BOARD FRAC-N SYNT LN

1

DC1789A

DC1789A

Analog Devices, Inc.

DEMO BOARD ISO USB TX W/PWR

54

DC2046A-B

DC2046A-B

Analog Devices, Inc.

DEV BOARD FOR LT4276B/LT4321

1

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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