Manufacturer Part Number
LM4132DMF-2.5/NOPB
Manufacturer
Texas Instruments
Introduction
The LM4132DMF-2.5/NOPB is a high-precision, low-noise, and low-power voltage reference from Texas Instruments. It provides a stable and accurate reference voltage of 2.5V, making it suitable for a wide range of applications, including analog-to-digital converters (ADCs), digital-to-analog converters (DACs), and precision measurement circuits.
Product Features and Performance
Fixed output voltage of 2.5V
High accuracy with ±0.4% tolerance
Low temperature coefficient of 20ppm/°C
Low noise performance with 240μVp-p (0.1Hz to 10Hz)
Wide input voltage range of 2.9V to 5.5V
Low quiescent current of 100μA
Wide operating temperature range of -40°C to 125°C
Product Advantages
Excellent stability and accuracy
Low noise and power consumption
Compact and space-saving SOT-23-5 package
Suitable for a wide range of analog and mixed-signal applications
Key Reasons to Choose This Product
Reliable and consistent performance
Optimized for power-sensitive designs
Easy to integrate with other circuit components
Cost-effective solution for precision voltage reference needs
Quality and Safety Features
Compliant with RoHS and lead-free requirements
Robust and reliable design for long-term use
Extensive testing and quality control measures
Compatibility
The LM4132DMF-2.5/NOPB is a drop-in replacement for other precision voltage reference ICs with similar specifications, making it easy to integrate into existing designs.
Application Areas
Analog-to-digital converters (ADCs)
Digital-to-analog converters (DACs)
Precision measurement and control circuits
Sensor conditioning and signal processing
Battery-powered and portable electronics
Product Lifecycle
The LM4132DMF-2.5/NOPB is an active product, and our website's sales team continues to manufacture and support it. There are no immediate plans for discontinuation. However, as technology evolves, customers are advised to check with our website's sales team for the latest information on product availability and potential alternative models.