Improved Data Quality Through Automated Sample Preparation

Significance of the Topic

Automated sample preparation plays a crucial role in ensuring high-quality chromatographic data by minimizing human error, reducing variability, and increasing laboratory throughput. In routine GC and LC analyses, precise dilution, calibration, and derivatization are often time-consuming and resource-intensive when performed manually. Implementing an automated system addresses these challenges, leading to more reproducible results and cost savings.

Objectives and Study Overview

This study evaluates the Agilent 7696A Automated Sample Prep WorkBench for three common tasks: sample dilutions with and without internal standards, calibration curve standard preparation, and fatty acid derivatization. A direct comparison with manual methods was conducted to quantify improvements in precision, accuracy, solvent consumption, and overall efficiency.

Methodology and Instrumentation

The 7696A WorkBench integrates two liquid-dispensing modules, a single-vial heater (up to 80 °C), a vortex mixer, and a barcode reader. Sample workflows included:

• GC dilutions: addition of isooctane, analyte mix (C10–C16), and internal standard (undecane–pentadecane) to 2 mL vials, followed by mixing and transfer to GC.
• LC dilutions: dispensing acetonitrile, pesticide standard (diuron), and p-terphenyl ISTD into autosampler vials, mixing, and LC analysis.
• Calibration curve preparation: linear dilution of a stock solution (methyl esters and dimethyl maleate) to six concentration levels, comparing manual volumetric flask dilutions with automated dispensing into autosampler vials.
• Fatty acid derivatization: silylation of caprylic, capric, myristic, and palmitic acids using BSTFA, performed manually and on the WorkBench with onboard heating.

Results and Discussion

Automated GC and LC dilutions achieved RSDs below 1% (gravimetric validation) and maintained accuracy within 2%. Calibration curves prepared with the WorkBench showed exceptional linearity (R² ≥ 0.997) and reproducibility (average RSD of relative response factors of 3.9%), compared to 16% RSD for manual methods. Silylation reactions yielded identical analyte ratios in both manual and automated preparations, with slightly improved precision (0.7% vs. 0.9% RSD). Solvent usage decreased from over 60 mL to 0.6 mL per calibration series.

Practical Benefits and Applications

The automated workflow delivers:

• Enhanced reproducibility and accuracy across dilution, calibration, and derivatization steps.
• Significant reductions in solvent and reagent consumption.
• Lower analyst workload, freeing personnel for higher-value tasks.
• Time savings through parallel processing and minimized manual handling.

Future Trends and Opportunities

Emerging developments in automated sample preparation may include:

• Integration with inline chromatographic systems for true on-line sampling.
• Advanced robotics for multi-step workflows, including solid-phase extractions and enzymatic digestions.
• AI-driven protocols to optimize reagent volumes, sequence order, and error correction.
• Miniaturization and green chemistry approaches to further reduce solvent use and waste.

Conclusion

Automation via the 7696A Sample Prep WorkBench markedly improves data quality in GC and LC workflows by delivering superior precision, accuracy, and efficiency compared to manual methods. The system reduces reagent consumption, shortens preparation times, and minimizes human error, making it an invaluable tool for high-throughput analytical laboratories.

Used Instrumentation

• Agilent 7696A Automated Sample Prep WorkBench
• Gas Chromatograph (GC) with autosampler
• Liquid Chromatograph (LC) with autosampler
• Onboard vortex mixer and single-vial heater (up to 80 °C)
• Barcode reader for sample tracking

References

1. Susanne Moyer, Dale Snyder, Rebecca Veeneman, Bill Wilson, “Typical Injection Performance for the Agilent 7693A Autoinjector,” Agilent Technologies Publication 5990-4606EN.