Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
BAP-1950A-C12A1-0-1-6OL

BAP-1950A-C12A1-0-1-6OL

APS

SCR (THYRISTOR) 3-PHASE CONTROL

50

MAX5487PMB1#

MAX5487PMB1#

Maxim Integrated

MODULE PERIPHERAL FOR MAX5487

9165

TMC2300-BOB

TMC2300-BOB

TRINAMIC Motion Control GmbH

BREAKOUTBOARD WITH TMC2300

15

EVAL-ADV7280MEBZ

EVAL-ADV7280MEBZ

Analog Devices, Inc.

EVAL BOARD VID DECODER ADV7280-M

1

TPS386000EVM-736

TPS386000EVM-736

Texas Instruments

EVAL MODULE FOR TPS386000-736

3

S5U13513P00C100

S5U13513P00C100

Epson

BOARD EVAL/SOFTWARE FOR S1D13513

0

BAP-1950A-C12A2-0-1-6OL

BAP-1950A-C12A2-0-1-6OL

APS

SCR (THYRISTOR) 3-PHASE CONTROL

50

TPS65217CEVM

TPS65217CEVM

Texas Instruments

EVAL MODULE FOR TPS65217C

2

EV-ADF41513SD1Z

EV-ADF41513SD1Z

Analog Devices, Inc.

EVB FOR 26.5GHZ PLL WITH ULTRA L

3

STEVAL-IDP003V1

STEVAL-IDP003V1

STMicroelectronics

BOARD & REF DESIGN

6

XR20M1280L40-0A-EB

XR20M1280L40-0A-EB

MaxLinear

EVAL BOARD FOR XR20M1280L40

1

DC1819A

DC1819A

Analog Devices, Inc.

BOARD DEMO FOR LTC4415EMSE

17

DPHY440SSRHREVM

DPHY440SSRHREVM

Texas Instruments

EVAL BOARD FOR SN65DPHY440

4

2054030002

2054030002

Woodhead - Molex

USB 2.0 500MA HUB MODULE KIT

37

BAP-1950A-C24A2-0-P-4CL

BAP-1950A-C24A2-0-P-4CL

APS

SCR (THYRISTOR) 3-PHASE CONTROL

50

125932-HMC675LP3E

125932-HMC675LP3E

Analog Devices, Inc.

EVAL BOARD HMC675LP3E

0

EVAL-CN0218-SDPZ

EVAL-CN0218-SDPZ

Analog Devices, Inc.

BOARD CFTL AD8212

0

MCSXTE2BK142

MCSXTE2BK142

NXP Semiconductors

EVAL BOARD FOR GD3000 S32K142

5

BQ40Z50EVM-561

BQ40Z50EVM-561

Texas Instruments

EVAL BOARD FOR BQ40Z50

12

EV1HMC882ALP5

EV1HMC882ALP5

Analog Devices, Inc.

HMC882 EVAL BOARD

8

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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