Automated photometric determination of manganese using the Optrode
Applications | | MetrohmInstrumentation
The accurate quantification of manganese in aqueous matrices is essential for environmental monitoring, industrial quality control and compliance with regulatory standards. Manganese levels influence water quality and can affect human health, while reliable analysis supports process optimization in chemical, pharmaceutical and food industries.
This application note presents an automated photometric titration procedure for determining Mn(II) in water using Eriochrome Black T as the indicator and an Optrode photometric sensor at 610 nm. The method ensures complete reduction to Mn(II), prevents precipitation and achieves reproducible, high-throughput determinations.
Seven replicate analyses yielded a mean manganese concentration of 2.170 g/L with a relative standard deviation of 0.29 %. These results demonstrate the method’s precision and the Optrode’s reliable endpoint detection in automated titration workflows.
The automated photometric titration method using the Optrode sensor offers a reliable, precise and efficient solution for manganese analysis in aqueous samples. Its automation, simplicity and reproducibility make it a valuable asset for laboratories requiring robust trace metal determinations.
Titration
IndustriesEnergy & Chemicals
ManufacturerMetrohm
Summary
Significance of the topic
The accurate quantification of manganese in aqueous matrices is essential for environmental monitoring, industrial quality control and compliance with regulatory standards. Manganese levels influence water quality and can affect human health, while reliable analysis supports process optimization in chemical, pharmaceutical and food industries.
Objectives and overview of the method
This application note presents an automated photometric titration procedure for determining Mn(II) in water using Eriochrome Black T as the indicator and an Optrode photometric sensor at 610 nm. The method ensures complete reduction to Mn(II), prevents precipitation and achieves reproducible, high-throughput determinations.
Methodology and instrumentation
- Sample preparation:
- 5–15 mL of 0.05 mol/L manganese standard in a 200 mL beaker
- Tip of ascorbic acid to reduce Mn to the divalent state
- 10 mL of 16 % triethanolamine to complex Mn and inhibit hydroxide precipitation
- 0.5 mL Eriochrome Black T indicator solution
- 10 mL pH 10 ammonium chloride/ammonia buffer
- Titrant:
- 0.1 mol/L Na₂EDTA solution
- Titration settings:
- Photometric detection at 610 nm
- Stirring rate: 8
- Signal drift limit: 20 mV/min
- Volume increment: 0.05 mL
- Endpoint detection: greatest slope criterion
Used instrumentation
- 907 Titrando titrator
- 815 Robotic USB Sample Processor XL with 786 swing head and 6.1462.070 swing arm
- 800 Dosino dosing units (5 mL, 10 mL, 50 mL)
- 802 Stirrer
- Disposable 200 mL PP sample beakers
Main results and discussion
Seven replicate analyses yielded a mean manganese concentration of 2.170 g/L with a relative standard deviation of 0.29 %. These results demonstrate the method’s precision and the Optrode’s reliable endpoint detection in automated titration workflows.
Benefits and practical applications
- High throughput via automated sample handling and dosing
- Excellent reproducibility indicated by low RSD values
- Applicable to environmental waters, industrial effluents and QA/QC in production
- Minimal sample preparation and straightforward reagent protocols
Future trends and opportunities
- Integration with digital laboratory platforms and real‐time data analytics for advanced process control
- Development of compact, on‐site photometric titration systems using microfluidics
- Adoption of greener titrants and reduced reagent volumes to minimize environmental impact
- Expansion to multi‐element analysis through selective complexation strategies
Conclusion
The automated photometric titration method using the Optrode sensor offers a reliable, precise and efficient solution for manganese analysis in aqueous samples. Its automation, simplicity and reproducibility make it a valuable asset for laboratories requiring robust trace metal determinations.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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