Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
ISL61861EVAL1Z

ISL61861EVAL1Z

Intersil (Renesas Electronics America)

BOARD EVAL FOR ISL61861

0

EVAL-10MSOPEBZ

EVAL-10MSOPEBZ

Analog Devices, Inc.

EVAL BOARD FOR 10-MSOP

12

BAP-1950A-C24A1-0-H-5CL

BAP-1950A-C24A1-0-H-5CL

APS

SCR (THYRISTOR) 3-PHASE CONTROL

50

ATAK42001-V1

ATAK42001-V1

Atmel (Microchip Technology)

ATA664151 EVAL KIT

0

INA230EVM

INA230EVM

Texas Instruments

EVAL MODULE FOR INA230

4

TPS2421-2EVM-03

TPS2421-2EVM-03

Texas Instruments

EVAL MODULE FOR TPS2421-2-03

1

EPC9059

EPC9059

EPC

BOARD DEV EPC2100 EGAN

5

EPC9509

EPC9509

EPC

EVAL BOARD AMP GAN CLASS D ZVS

22

MAX9286COAXEVKIT#

MAX9286COAXEVKIT#

Maxim Integrated

EVALUATION KIT MAX9286 W/COAX

212

TPS23753AEVM-235

TPS23753AEVM-235

Texas Instruments

EVAL MODULE FOR TPS23753A

0

ADP5092-1-EVALZ

ADP5092-1-EVALZ

Analog Devices, Inc.

ADP5092 EVALUATION BOARD

7

MAX9867EVKIT+

MAX9867EVKIT+

Maxim Integrated

EVAL KIT FOR MAX9867

2016

UCC5320SCEVM-058

UCC5320SCEVM-058

Texas Instruments

EVALUATION MODULE

7

3220DFP-DGLEVM

3220DFP-DGLEVM

Texas Instruments

EVAL BOARD FOR MUX HD3SS3220

3

EVAL-AD5750EBZ

EVAL-AD5750EBZ

Analog Devices, Inc.

BOARD EVAL FOR AD5750

10

AFE5805EVM

AFE5805EVM

Texas Instruments

EVAL MODULE FOR AFE5805

1

APEK4950ELJ-01-T-DK

APEK4950ELJ-01-T-DK

Allegro MicroSystems

BOARD EVAL MOTOR CONTROL A4950

6

TPS22932BEVM

TPS22932BEVM

Texas Instruments

EVAL MODULE FOR TPS22932B

3

MAX4948EVKIT+

MAX4948EVKIT+

Maxim Integrated

KIT EVAL FOR MAX4948

27

ASDAK-MSCSM120AM03CT6LIAG-01

ASDAK-MSCSM120AM03CT6LIAG-01

Roving Networks / Microchip Technology

AUGMENTED SWITCH DEV KIT

2

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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