AD7366BRUZ-RL7 - Analog Devices

Manufacturer Part Number

AD7366BRUZ-RL7

Manufacturer

analog-devices

Introduction

The AD7366BRUZ-RL7 is a high-performance, 12-bit, 1 MSPS, 4-channel, simultaneous sampling, analog-to-digital converter (ADC) with a flexible, serial interface. It features a low-power, high-speed successive-approximation register (SAR) ADC, a sample-and-hold amplifier, and a multiplexer. The device operates from a single +2.7 V to +5.25 V digital supply and a dual analog supply of ±11.5 V to ±16.5 V.

Product Features and Performance

12-bit resolution

1 MSPS sampling rate

4 single-ended analog input channels

Simultaneous sampling

SPI/DSP serial interface

Selectable address

True bipolar operation

External or internal reference

-40°C to +85°C operating temperature range

Product Advantages

High-speed, low-power SAR ADC

Flexible, serial interface

Simultaneous sampling

True bipolar operation

Wide operating temperature range

Key Reasons to Choose This Product

Reliable and high-performance data acquisition solution

Versatile interface and configuration options

Efficient power consumption for low-power applications

Robust operation in a wide range of environmental conditions

Quality and Safety Features

Qualified for automotive and industrial applications

Stringent quality control and testing procedures

Complies with relevant safety and environmental regulations

Compatibility

The AD7366BRUZ-RL7 is compatible with a variety of microcontrollers and digital signal processors with SPI or DSP-compatible serial interfaces.

Application Areas

Industrial automation and control

Instrumentation and test equipment

Medical imaging and diagnostic equipment

Power monitoring and management systems

Automotive electronics

Product Lifecycle

The AD7366BRUZ-RL7 is an active product in our website's sales team's portfolio. There are no announced plans for discontinuation at this time. Customers are advised to contact our website's sales team for information on any available equivalent or alternative models.