EFM32G840F128G-E-QFN64R Allicdata Electronics
Allicdata Part #:

EFM32G840F128G-E-QFN64R-ND

Manufacturer Part#:

EFM32G840F128G-E-QFN64R

Price: $ 1.75
Product Category:

Integrated Circuits (ICs)

Manufacturer: Silicon Labs
Short Description: 128K FLASH, 16K RAM, 4X24 LCD, A
More Detail: ARM® Cortex®-M3 Gecko Microcontroller IC 32-Bit 32...
DataSheet: EFM32G840F128G-E-QFN64R datasheetEFM32G840F128G-E-QFN64R Datasheet/PDF
Quantity: 1000
1000 +: $ 1.59466
Stock 1000Can Ship Immediately
$ 1.75
Specifications
Series: Gecko
Part Status: Active
Core Processor: ARM® Cortex®-M3
Core Size: 32-Bit
Speed: 32MHz
Connectivity: I²C, IrDA, SmartCard, SPI, UART/USART
Peripherals: Brown-out Detect/Reset, DMA, LCD, POR, PWM, WDT
Number of I/O: 56
Program Memory Size: 128KB (128K x 8)
Program Memory Type: FLASH
EEPROM Size: --
RAM Size: 16K x 8
Voltage - Supply (Vcc/Vdd): 1.98 V ~ 3.8 V
Data Converters: A/D 8x12b, D/A 2x12b
Oscillator Type: Internal
Operating Temperature: -40°C ~ 85°C (TA)
Description

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The EFM32G840F128G-E-QFN64R is a 32-bit microcontroller specially designed for use in a range of embedded applications. It is part of the EFM32 Gecko family of microcontrollers from Silicon Labs. This model offers a range of features that makes it suitable for a wide variety of embedded projects.

The EFM32G840F128G-E-QFN64R is based on an ARM Cortex-M4 core and contains an integrated floating point and DSP unit, making it ideal for signal processing, motor control and control loop applications. It runs at up to 48MHz and includes up to 512kB flash and 96kB RAM. There are also a range of digital and analogue peripherals, including USB, UART, SPI, I2C, PWM, GPIO as well as digital sensors, allowing the microcontroller to be used in a range of different applications.

The EFM32G840F128G-E-QFN64R is suitable for a wide range of embedded applications, including motor control and control loop applications. It can be used to control the speed and position of motors, to monitor temperature and other parameters, or to monitor and control other processes in a system. It can also be used as the basis for a home automation system, controlling lighting and other systems within a home.

The EFM32G840F128G-E-QFN64R is well suited for use in Internet of Things (IoT) applications. It can be used to gather data from sensors, to process the data and to communicate the data to the cloud. This could be used for monitoring systems, such as monitoring energy usage in a building, or for more complicated applications such as controlling an industrial process.

The EFM32G840F128G-E-QFN64R also has a range of features that make it suitable for use in wearable technology. It can be used to monitor physical activity, heart rate, temperature or other parameters and can be used to drive displays or to communicate data to the cloud. It can be used in combination with other sensors, such as GPS, to provide accurate location tracking.

The working principle of the EFM32G840F128G-E-QFN64R is based on the ARM Cortex-M4 core, which is a 32-bit processor with a wide range of features. It can execute multiple instructions in parallel, making it an ideal for applications that require high performance processing. The ARM Cortex-M4 also has built-in memory protection and error checking, making it well suited for use in safety critical applications.

The EFM32G840F128G-E-QFN64R can be programmed using the Silicon Labs Simplicity Studio development environment. The environment includes a range of development tools, including an integrated debugger and a C++ compiler, and can be used for rapid prototyping and applications development.

The EFM32G840F128G-E-QFN64R is a versatile microcontroller that is suitable for a wide range of embedded applications. It offers a range of features that makes it well suited for motor control, signal processing and IoT applications and can be used to provide the core functionality for a variety of applications. It is programmed using the Silicon Labs Simplicity Studio development environment and is ideal for rapid prototyping and application development.

The specific data is subject to PDF, and the above content is for reference

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