Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
TMC5062-EVAL

TMC5062-EVAL

TRINAMIC Motion Control GmbH

EVAL BOARD FOR TMC5062

1

EVAL-ADG5243FEBZ

EVAL-ADG5243FEBZ

Analog Devices, Inc.

EVAL BOARD FOR ADG5243

0

BQ24012EVM

BQ24012EVM

Texas Instruments

EVAL MOD FOR BQ24012

2

INA3221EVM

INA3221EVM

Texas Instruments

EVAL MODULE FOR INA3221

3

DC788B

DC788B

Analog Devices, Inc.

BOARD EVAL FOR LTC4061EDD

4

WIZ100SR-EVB

WIZ100SR-EVB

WIZnet

EVALUATION MODULE

0

UMFT220XA-02

UMFT220XA-02

Future Technology Devices International, Ltd.

USB TO 4-BIT SPI/FT1248 DEVELOPM

0

TSW1266EVM

TSW1266EVM

Texas Instruments

TSW1266EVM EVALUATION MODULE

1

WIZ550WEB-EVB

WIZ550WEB-EVB

WIZnet

EVALUATION BOARD FOR WIZ550WEB

0

BAP-1950A-C24A1-0-1-4OL

BAP-1950A-C24A1-0-1-4OL

APS

SCR (THYRISTOR) 3-PHASE CONTROL

50

EVAL100WDRIVECFD2TOBO1

EVAL100WDRIVECFD2TOBO1

IR (Infineon Technologies)

100W MOTOR DRIVER EVAL

2

DC1746A-B

DC1746A-B

Analog Devices, Inc.

EVALUATION KIT LOW EMI LTM2881-5

2

EV_INMP522-FX

EV_INMP522-FX

TDK InvenSense

EVAL BOARD MEMS MIC INMP522

4

EPC9054

EPC9054

EPC

BOARD DEV EPC2010C EGAN FET

13

BQ3050EVM-001

BQ3050EVM-001

Texas Instruments

EVAL MODULE FOR BQ3050-001

3

DC1594A-A

DC1594A-A

Analog Devices, Inc.

BOARD DEMO FOR 5V LTC4219-12

1

P-NUCLEO-USB002

P-NUCLEO-USB002

STMicroelectronics

GENERAL PURPOSE ANALOG & RF

3

TPS22967EVM-023

TPS22967EVM-023

Texas Instruments

EVAL BOARD FOR TPS22967

1

EPC9086

EPC9086

EPC

EVAL BOARD FOR EPC2111

56

NB4N11MDTEVB

NB4N11MDTEVB

Sanyo Semiconductor/ON Semiconductor

BOARD EVAL FOR NB4N11MD

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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