Improved Data Quality Through Automated Sample Preparation

Importance of the Topic

The quality of chromatographic analyses strongly depends on the consistency and accuracy of sample preparation. Manual workflows are time-consuming, prone to variability and reagent waste. Automating key tasks such as dilutions, standard preparation and derivatization enhances data reliability, reduces costs and frees analysts for higher-value work.

Objectives and Study Overview

This study evaluates the performance benefits of the Agilent 7696A Automated Sample Prep WorkBench versus conventional manual procedures for three common tasks:

• GC and LC sample dilution with internal standard addition
• Calibration curve standard preparation by dilution
• Fatty acid derivatization via silylation

The aim is to compare reproducibility, accuracy, solvent consumption and operational efficiency between automated and manual methods.

Methodology and Instrumentation

All workflows were executed on the 7696A WorkBench, featuring dual liquid dispensers, a vial heater (up to 80 °C), vortex mixer and barcode reader. Tasks were performed offline, paired with GC–MS or LC–UV analysis.

• Sample dilution: 50 µL each of isooctane, analyte mix and 0.5 µL internal standard for GC; 187.5 µL acetonitrile, 62.5 µL pesticide standard and 125 µL internal standard for LC.
• Calibration curves: manual dilution in 10 mL flasks versus automated dilution into 2 mL vials for six concentration levels (50–500 ppm).
• Derivatization: addition of 100 µL BSTFA to fatty acid solutions manually and via the onboard heater.

Results and Discussion

Automated dilutions achieved gravimetric RSDs below 1% (GC) and 0.5% (LC), whereas manual dilutions showed higher variability. Calibration curves prepared with the WorkBench had an average relative response factor (RRF) RSD of 3.9%, compared to 16% for manual standards. Automated derivatization yielded R2 values above 0.997, matching manual performance but with improved consistency across replicates.

Notable observations:

• Solvent consumption for standard preparation dropped from over 60 mL to 0.6 mL per set.
• Internal standard addition did not compromise accuracy but improved linearity and reproducibility.
• Automated workflows completed sample prep faster and with fewer manual steps.

Benefits and Practical Applications

Key advantages include:

• Enhanced reproducibility and data quality, reducing rework.
• Significant reagent and solvent savings, lowering operational costs.
• Labor efficiency gains, allowing analysts to focus on data interpretation.

This approach is particularly relevant for high-throughput laboratories in environmental testing, pharmaceuticals, food safety and QA/QC settings.

Future Trends and Applications

Emerging opportunities include integration with laboratory information management systems (LIMS) for seamless data flow, expanded protocols for bioanalysis and green chemistry, and miniaturized platforms to further reduce sample and reagent volumes. Advances in robotic automation may enable fully unattended end-to-end workflows.

Conclusion

The Agilent 7696A WorkBench demonstrably improves precision, lowers error rates and cuts solvent usage in routine GC and LC sample preparation tasks. Automation delivers robust calibration curves, consistent derivatization and efficient internal standard addition. Laboratories adopting this technology can expect higher data quality, cost savings and increased throughput.

Reference

1. Moyer S., Synder D., Veeneman R., Wilson B. Typical Injection Performance for the Agilent 7693A Autoinjector. Agilent Technologies Publication 5990-4606EN.