Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
ISO722XEVM

ISO722XEVM

Texas Instruments

EVAL MODULE FOR ISO7220M

1

TUSB212EVM

TUSB212EVM

Texas Instruments

TUSB212EVM

4

DP141RLJEVM

DP141RLJEVM

Texas Instruments

EVALUATION MODULE

3

TSW1400EVM

TSW1400EVM

Texas Instruments

KIT EVAL DAT69933A ACQ 16B

13

LP8758EVM

LP8758EVM

Texas Instruments

EVAL MODULE LP8758

3

TMDSDCDCLEDKIT

TMDSDCDCLEDKIT

Texas Instruments

KIT LED DVR C2000 PICCOLO

1

TPS382-Q1EVM

TPS382-Q1EVM

Texas Instruments

EVALUATION MODULE

5

TLV320AIC3111EVM-K

TLV320AIC3111EVM-K

Texas Instruments

EVAL MODULE FOR TLV320AIC3111

2

TPS2066CDGNEVM-015

TPS2066CDGNEVM-015

Texas Instruments

EVAL MODULE FOR TPS2066C-015

2

TPS22925EVM

TPS22925EVM

Texas Instruments

EVALUATION MODULE

2

BQ24091EVM

BQ24091EVM

Texas Instruments

EVAL MODULE FOR BQ24091

2

ADS1292RECG-FE

ADS1292RECG-FE

Texas Instruments

KIT DEMO FOR ADS1292R

4

LMX2592EVM

LMX2592EVM

Texas Instruments

EVAL BOARD FOR LMX2592

10

BQ24125EVM-003

BQ24125EVM-003

Texas Instruments

EVAL MODULE FOR BQ24125-003

2

DK-LM4F-DRV8312

DK-LM4F-DRV8312

Texas Instruments

KIT MOTOR CONTROL LM4F

3

BQ24297EVM-021

BQ24297EVM-021

Texas Instruments

EVAL MOD LI-ION BATTERY CHARGER

3

TPS22908EVM-025

TPS22908EVM-025

Texas Instruments

MODULE EVAL FOR TPS22908-025

3

SN65LVDS822RGZEVM

SN65LVDS822RGZEVM

Texas Instruments

EVAL MODULE FOR SN65LVDS822RGZ

1

DRV8844EVM

DRV8844EVM

Texas Instruments

EVAL MODUOLE FOR DRV8844

4

LMH1218EVM

LMH1218EVM

Texas Instruments

EVAL MODULE FOR LMH1218

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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