Bruno V

Bruno V

Engineering Student | Aerospace Enthusiast | AI Developer | Java Certified | Honors Class

AI-Driven Automated Titration System

Published:

Introduction

Titration is a cornerstone of quantitative chemical analysis, used to determine the concentration of an unknown solution. This guide focuses on automating hydrochloric acid (HCl) and sodium hydroxide (NaOH) titration using AI to enhance precision, reduce human error, and streamline data collection.

Materials and Reagents

Chemical Reagents

  1. Analyte: Hydrochloric acid (HCl) solution (unknown concentration).
  2. Titrant: Sodium hydroxide (NaOH) solution (standardized, e.g., 0.1 M).
  3. Indicator: Phenolphthalein (1% w/v in ethanol) for visual endpoint detection.
  4. Calibration Standards:
    • pH buffer solutions (pH 4.0, 7.0, and 10.0).
    • Conductivity standard solution (if applicable).
  5. Distilled water for rinsing and dilution.

System Components and Integration

1. Robotic Liquid Handler

  • Function: Precisely dispenses NaOH titrant into HCl analyte.
  • Specifications: Programmable dispensing rates.

2. Sensors and Computer Vision

  • pH/Conductivity Sensors: Real-time monitoring at 10 Hz.
  • Camera System: OpenCV / TensorFlow for colorimetric analysis.

3. AI Control Software

  • Endpoint Prediction: Linear regression or neural networks.
  • Adaptive Dispensing: Adjusts flow rate based on real-time pH slope.
  • Live Dashboard: pH curve, titrant volume, and camera feed.

Data Analysis

Calculations

Using the formula for neutralization:

\[M_{HCl} = \frac{M_{NaOH} \times V_{NaOH}}{V_{HCl}}\]

Advantages of Automation

  • Error Reduction: AI minimizes overshooting by predicting endpoint trends.
  • Throughput: Process 20+ samples/hour vs. 4-5 manually.
  • Data Integrity: Automated logs eliminate transcription errors.

Conclusion

This AI-driven system revolutionizes traditional titration by merging robotics, sensor networks, and machine learning for pharmaceutical-grade accuracy.