Manufacturer Part Number
TM4C123GH6PMI7R
Manufacturer
Texas Instruments
Introduction
The TM4C123GH6PMI7R is a high-performance, low-power 32-bit ARM Cortex-M4F-based microcontroller from Texas Instruments. It offers a comprehensive set of integrated peripherals, making it well-suited for a wide range of embedded applications.
Product Features and Performance
ARM Cortex-M4F core running at 80MHz
256KB FLASH program memory
32KB RAM
Integrated CAN, I2C, IrDA, Microwire, QEI, SPI, SSI, UART, and USB OTG interfaces
Extensive peripheral set including DMA, motion PWM, brown-out detection, and watchdog timer
12-bit ADC with 12 channels
Product Advantages
High-performance 32-bit ARM Cortex-M4F core
Generous on-chip memory for complex applications
Extensive peripheral set for versatile interfacing
Low-power operation for battery-powered designs
Robust set of development tools and ecosystem support
Key Reasons to Choose
Powerful 32-bit ARM Cortex-M4F processor for demanding applications
Comprehensive peripheral integration for reduced system complexity
Flexibility to handle a wide range of embedded control and monitoring tasks
Long-term product availability and support from a trusted industry leader
Quality and Safety Features
Supported by a robust development ecosystem
Designed and manufactured to high quality and reliability standards
Integrated safety features like brown-out detection and watchdog timer
Compatibility
The TM4C123GH6PMI7R is pin-compatible with other TM4C123 series microcontrollers, enabling easy migration and design reuse.
Application Areas
The TM4C123GH6PMI7R is well-suited for a variety of embedded applications, including industrial automation, motor control, medical devices, and consumer electronics.
Product Lifecycle
The TM4C123GH6PMI7R is an active product in the Tiva™ C series. Our website's sales team continues to provide long-term support and availability for this microcontroller family. Customers are advised to contact our website's sales team for information on any potential equivalent or alternative models.