Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
LMK03806BEVAL/NOPB

LMK03806BEVAL/NOPB

Texas Instruments

BOARD EVAL FOR LMK03806

2

WIG-09555

WIG-09555

SparkFun

SPARKFUN OBD-II UART

6

INA200EVM

INA200EVM

Texas Instruments

EVAL BOARD FOR INA200

5

EV-ADF4356SD1Z

EV-ADF4356SD1Z

Analog Devices, Inc.

EVAL BOARD FOR ADF4356

11

EVAL-CN0225-SDPZ

EVAL-CN0225-SDPZ

Analog Devices, Inc.

EVAL BOARD FOR CN0225

1

NB7V32MMNGEVB

NB7V32MMNGEVB

Sanyo Semiconductor/ON Semiconductor

BOARD EVAL NB7V32M

0

GA03IDDJT30-FR4

GA03IDDJT30-FR4

GeneSiC Semiconductor

BOARD GATE DRIVER

0

BQ24090EVM

BQ24090EVM

Texas Instruments

EVAL MODULE FOR BQ24090

1

DRV2624EVM-MINI

DRV2624EVM-MINI

Texas Instruments

EVAL BOARD FOR DRV2624

7

SP337EBET-0A-EB

SP337EBET-0A-EB

MaxLinear

BOARD EVALUATION FOR SP337EBET

2

SN65LVDS387EVM

SN65LVDS387EVM

Texas Instruments

EVALUATION MOD FOR SN65LVDS387

19

KITDRIVER2EDN7524RTOBO1

KITDRIVER2EDN7524RTOBO1

IR (Infineon Technologies)

2EDN7524R DUAL LOW SIDE

0

INA226EVM

INA226EVM

Texas Instruments

EVAL MODULE FOR INA226

6

TCA9802EVM

TCA9802EVM

Texas Instruments

EVAL MODULE

6

PD-IM-7608M

PD-IM-7608M

Roving Networks / Microchip Technology

COMPACT EVB 8 PORTS EVBBASED PD6

1

CDCEL925PERF-EVM

CDCEL925PERF-EVM

Texas Instruments

EVAL MOD PERFORMANCE FOR CDCE925

2

BAP-1950A-C02K2-0-P-6CL

BAP-1950A-C02K2-0-P-6CL

APS

SCR (THYRISTOR) 3-PHASE CONTROL

50

EVAL-ADM3050EEBZ

EVAL-ADM3050EEBZ

Analog Devices, Inc.

ADM3050E EVALUATION BOARD

16

TMC6200-EVAL

TMC6200-EVAL

TRINAMIC Motion Control GmbH

EVAL BOARD FOR TMC6200

2

EVAL2ED020I12F2TOBO1

EVAL2ED020I12F2TOBO1

IR (Infineon Technologies)

EVAL-2ED020I12-F2 TO SHOW THE FU

3

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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