How to Reduce ICP-OES Remeasurement Caused by Sample Problems and Errors

Importance of the Topic

Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) is a cornerstone analytical method for quantifying elemental content in diverse matrices across mining, environmental monitoring, food, pharmaceutical and industrial laboratories.
Effective sample handling and robust quality control practices are critical to minimizing costly remeasurements, ensuring data accuracy, and improving laboratory productivity.

Objectives and Overview of the Study

This article reviews common sample-related challenges that lead to time-wasting remeasurements in ICP-OES.
It presents practical strategies and instrumental advances designed to prevent errors from sample characteristics, preparation mistakes and instrument issues.
The goal is to help analysts obtain reliable results on the first measurement, reducing downtime and operational cost.

Instrumentation

This study highlights features of modern ICP-OES instruments and supporting equipment:

• Agilent 5800 and 5900 ICP-OES systems with IntelliQuant data analytics for spectral interference detection, IntelliQuant Screening for rapid elemental profiling, and Intelligent Rinse for automated sample introduction cleaning.
• Dichroic Spectral Combiner in the 5900 model for simultaneous axial and radial view measurements without time-consuming optical reconfiguration.
• ESI prepFAST autodilutor for automated sample dilution of over-range measurements.
• Microwave digestion vessels and hot-block digesters for sample preparation, complemented by certified reference materials to validate digestion protocols.

Main Results and Discussion

Sample issues in ICP-OES cluster into three areas:

1. Sample characteristics and matrix effects, including spectral interferences from overlapping emission lines and signal suppression or enhancement by high dissolved solids.
2. Preparation and calibration errors, such as pipetting mistakes, missing acids in digestions, mis-prepared standards, and sample mix-ups in autosamplers.
3. Instrument-related problems, including contamination carryover, blocked nebulizers, and maintenance timing misalignments.

Key findings:

• Spectral interferences: Arsenic detection at 193.696 nm suffers false positives when aluminum overlaps. Utilizing alternate wavelengths and data analytics (IntelliQuant) improves accuracy.
• Calibration quality: Monitoring % Relative Standard Error in addition to correlation coefficients helps detect suboptimal calibration curves early.
• Contamination control: Preparation blanks, dual rinse stations with automated rinse threshold monitoring, and internal standard ratio tracking prevent carryover of sticky elements.
• Sample preparation QC: Certified reference materials processed identically to unknowns confirm digestion completeness and detect missing reagents via element monitoring (e.g., chlorine for HCl).
• Sample tracking: Barcode integration with control software reduces sample mix-ups and remeasurement requirements.
• High-matrix handling: Vertical torches and dual-view optics with Dichroic Spectral Combiner resist salt buildup and extend analytical range without manual view switching.
• Over-range workflow: Automated switching to less sensitive emission lines or autodilutor modules avoids manual dilutions and repeat analyses.

Benefits and Practical Applications

Implementing these strategies yields:

• Fewer sample remeasurements and reduced reagent and labor costs.
• Improved confidence in data quality and compliance with regulatory requirements.
• Faster turnaround times and enhanced laboratory throughput.
• Streamlined maintenance scheduling based on usage metrics rather than fixed intervals.

Future Trends and Opportunities

Emerging directions include:

• Advanced data analytics and machine learning integrated into spectrometers for real-time interference correction and method optimization.
• Expanded use of in-line dilution and automated sample pre-screening to adapt to unknown or variable matrices.
• Internet-connected devices for remote monitoring of instrument health and predictive maintenance alerts.
• Broader adoption of quality management principles such as poka-yoke to further minimize human errors in sample preparation.

Conclusion

By combining rigorous sample preparation protocols, modern ICP-OES instrumentation features and proactive quality control measures, laboratories can effectively minimize remeasurements, ensure accurate elemental data and maximize operational efficiency.

Reference

• United States Environmental Protection Agency (2001a) OTS Alert #2, Use of the ICP analytical method (CLP SOW ILM04.1, SW-846 6010, MCAWW 200.7) for drinking water samples may result in false-positive detections of arsenic, lead, and/or thallium above their respective MCLs.
• Dudek-Burlikowska M, Szewieczek D (2001) The Poka-Yoke method as an improving quality tool of operations in the process, Journal of Achievements in Materials and Manufacturing Engineering 36:95–102.