EFM32G842F64G-E-QFP64
- Mfr.Part #
- EFM32G842F64G-E-QFP64
- Manufacturer
- Silicon Labs
- Package / Case
- 64-TQFP
- Datasheet
- Download
- Description
- IC MCU 32BIT 64KB FLASH 64TQFP
- Stock
- 40,689
- In Stock :
- 40,689
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- Manufacturer :
- Silicon Labs
- Product Category :
- Microcontrollers
- PWM Channels :
- yes
- Bit Size :
- 32
- JESD-30 Code :
- S-PQFP-G64
- Has ADC :
- yes
- Speed :
- 32MHz
- Operating Temperature :
- -40°C~85°C TA
- Program Memory Size :
- 64KB 64K x 8
- Terminal Pitch :
- 0.5mm
- Series :
- Gecko
- Connectivity :
- I2C, IrDA, SmartCard, SPI, UART/USART
- Terminal Position :
- QUAD
- Supply Voltage-Max (Vsup) :
- 3.8V
- Factory Lead Time :
- 8 Weeks
- Program Memory Type :
- Flash
- Number of I/O :
- 53
- RAM (bytes) :
- 16384
- On Chip Program ROM Width :
- 8
- Supply Voltage-Min (Vsup) :
- 1.98V
- Number of Terminations :
- 64
- Moisture Sensitivity Level (MSL) :
- 3 (168 Hours)
- Terminal Form :
- Gull wing
- Reach Compliance Code :
- Compliant
- Supply Voltage :
- 3V
- Mounting Type :
- Surface Mount
- Clock Frequency :
- 32MHz
- Oscillator Type :
- Internal
- Address Bus Width :
- 16
- Peripherals :
- Brown-out Detect/Reset, DMA, LCD, POR, PWM, WDT
- Voltage - Supply (Vcc/Vdd) :
- 1.98V~3.8V
- RAM Size :
- 16K x 8
- uPs/uCs/Peripheral ICs Type :
- MICROCONTROLLER, RISC
- External Data Bus Width :
- 16
- DAC Channels :
- yes
- HTS Code :
- 8542.31.00.01
- Data Converter :
- A/D 8x12b; D/A 2x12b
- Core Size :
- 32-Bit
- RoHS Status :
- RoHS Compliant
- Surface Mount :
- yes
- Packaging :
- Tray
- Width :
- 10mm
- Package / Case :
- 64-TQFP
- Length :
- 10mm
- DMA Channels :
- yes
- Height Seated (Max) :
- 1.2mm
- Core Processor :
- ARM® Cortex®-M3
- Datasheets
- EFM32G842F64G-E-QFP64

Microcontrollers Silicon Labs EFM32G842F64G-E-QFP64 Overview
The Microcontrollers Silicon Labs EFM32G842F64G-E-QFP64 represents a cutting-edge solution for versatile applications requiring low power consumption and high performance in a compact form factor. This 32-bit microcontroller unit (MCU) leverages Silicon Labs' proven technology to deliver robust processing capabilities with a 64KB flash memory, all encapsulated in a 64-pin TQFP package. Ideal for design engineers looking to balance power efficiency with advanced computational needs, this MCU is a prime choice for next-generation electronic applications. Its efficient architecture not only reduces power costs but also supports sophisticated features in IoT devices, industrial automation, and more, making it a key component in driving innovative solutions.
EFM32G842F64G-E-QFP64 Features
The EFM32G842F64G-E-QFP64 microcontroller offers a wealth of features that enhance its applicability in a wide range of uses. Key features include a 32-bit ARM Cortex-M3 processor, which provides a balance of efficiency and power for handling complex algorithms and processing tasks. With 64KB of flash memory, it supports substantial code bases and software applications without compromising performance. Additionally, its low-power operation modes ensure optimal power management in battery-driven devices, further augmented by its wide range of I/O options that allow for flexible connectivity solutions.
EFM32G842F64G-E-QFP64 Applications
- Wearable Technology: This MCU can efficiently manage power in wearable devices, such as fitness trackers and smartwatches, ensuring longer battery life while maintaining robust performance for sensor data processing and user interface management.
- Smart Home Devices: In smart home devices like thermostats and lighting systems, the EFM32G842F64G-E-QFP64 offers the necessary control capabilities to handle various sensors and connectivity options, enabling advanced home automation.
- Industrial Automation: This MCU's robust processing power and extensive I/O capabilities make it ideal for industrial automation controllers, where precision and reliability are paramount for monitoring and controlling machinery and production processes.
- Energy Management Systems: In energy management systems, the EFM32G842F64G-E-QFP64's low power consumption and ample memory support complex algorithms for optimizing energy usage and maintaining system stability across various scales.
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