EFM32LG940F64G-E-QFN64

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Mfr.Part #
EFM32LG940F64G-E-QFN64
Manufacturer
Silicon Labs
Package / Case
64-VFQFN Exposed Pad
Datasheet
Download
Description
IC MCU 32BIT 64KB FLASH 64QFN
Stock
48,004
In Stock :
48,004

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Manufacturer :
Silicon Labs
Product Category :
Microcontrollers
DMA Channels :
yes
Weight :
206.29948mg
Packaging :
Tray
Terminal Form :
NO LEAD
Factory Lead Time :
6 Weeks
Number of Timers/Counters :
5
Core Size :
32-Bit
Number of Terminations :
64
Number of Programmable I/O :
52
Watchdog Timer :
yes
Operating Supply Voltage :
3V
Interface :
I2C, I2S, IrDA, SPI, UART, USART, USB
Terminal Position :
QUAD
Moisture Sensitivity Level (MSL) :
3 (168 Hours)
Length :
9mm
Has ADC :
yes
Number of Pins :
64
Supply Voltage-Max (Vsup) :
3.8V
Package / Case :
64-VFQFN Exposed Pad
Mounting Type :
Surface Mount
Peripherals :
Brown-out Detect/Reset, DMA, LCD, POR, PWM, WDT
PWM Channels :
yes
Series :
Leopard Gecko
RoHS Status :
RoHS Compliant
Data Bus Width :
32b
Program Memory Type :
Flash
Connectivity :
I2C, IrDA, SmartCard, SPI, UART/USART, USB
Frequency :
48MHz
Operating Temperature :
-40°C~85°C TA
DAC Channels :
yes
RAM Size :
32K x 8
Data Converter :
A/D 8x12b; D/A 2x12b
Oscillator Type :
Internal
Supply Voltage :
3V
Core Processor :
ARM® Cortex®-M3
Program Memory Size :
64KB 64K x 8
Bit Size :
32
Height Seated (Max) :
0.9mm
Memory Size :
64KB
Published :
2014
Number of I/O :
53
ECCN Code :
3A001.A.3
Surface Mount :
yes
uPs/uCs/Peripheral ICs Type :
MICROCONTROLLER, RISC
Core Architecture :
ARM
Voltage - Supply (Vcc/Vdd) :
1.98V~3.8V
Introducing Microcontrollers Silicon Labs EFM32LG940F64G-E-QFN64 from Chip IC,where excellence meets affordability. This product stands out with its Number of Terminations:64, Number of Pins:64, Package / Case:64-VFQFN Exposed Pad, Mounting Type:Surface Mount, Operating Temperature:-40°C~85°C TA, EFM32LG940F64G-E-QFN64 pinout, EFM32LG940F64G-E-QFN64 datasheet PDF, EFM32LG940F64G-E-QFN64 amp .Beyond Microcontrollers Silicon Labs EFM32LG940F64G-E-QFN64 ,we also offer PIC16F506-I/SL, ATTINY44A-SSN, MS51FB9AE, Our vast inventory has you covered. Contact us now for immediate solutions.

Silicon Labs EFM32LG940F64G-E-QFN64


Microcontrollers Silicon Labs EFM32LG940F64G-E-QFN64 Overview

Introducing the robust EFM32LG940F64G-E-QFN64 from Silicon Labs, a cutting-edge microcontroller designed for optimal performance and efficiency. This product from the renowned Microcontrollers Silicon Labs EFM32LG940F64G-E-QFN64 line is engineered to address the complex needs of modern electronic applications. It combines a powerful 32-bit processing core with 64KB of flash memory packed into a compact 64QFN package, ensuring a versatile solution that supports the demands of both power-sensitive and space-constrained applications.

EFM32LG940F64G-E-QFN64 Features

The EFM32LG940F64G-E-QFN64 microcontroller boasts a plethora of features designed to enhance performance and usability. It includes an energy-efficient ARM Cortex-M3 processor which provides the backbone for managing intensive applications while minimizing power consumption. The 64KB flash memory allows for ample program storage, and its small form factor 64QFN package makes it ideal for devices where space is at a premium. Additionally, its robust I/O capabilities enable versatile connectivity options for a variety of peripheral devices.

EFM32LG940F64G-E-QFN64 Applications

  • Smart Home Devices: The microcontroller's low power consumption and robust processing capabilities make it ideal for smart thermostats, security systems, and lighting controls, where efficient energy use is critical.
  • Industrial Automation: Utilized in sensor management, process control, and machine interface units, the EFM32LG940F64G-E-QFN64 supports complex algorithms needed for real-time processing and control tasks.
  • Wearable Technology: With its compact size and energy efficiency, it is perfectly suited for wearables such as fitness trackers and smart watches, providing long battery life and powerful computational ability.
  • Medical Devices: The MCU's reliability and processing features can be applied in medical monitoring systems, ensuring accurate data management and device control crucial for patient care.
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