BRAND / VENDOR: Agilent

Agilent, US-700001713, Refractive index detector OQ standard

CATALOG NUMBER: US-700001713

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Product Description

Refractive index detector OQ standard

Specifications:
Analysis Type: Quantitative
Chemical Type: Organic
Concentration: Caffeine (analytical grade)2000 µg/mLCAS #: 58-08-2
Format: Single component mixture
Quality Standard: ISO 17034
Solvent: Water/methanol (81:19 w/w)
Technique: LC & LC/MSUV-Vis
Volume: 10 mL

**********The following product description is generated by AI and is for reference only. If you have any questions, please contact customer service.**********
The Refractive Index Detector OQ Standard is a highly reliable solution for the operational qualification and routine performance verification of refractive index detectors used in liquid chromatography workflows. Designed to ensure instrument accuracy and regulatory compliance, this standard enables precise calibration and validation of detector response. It is an essential tool for laboratories performing quality control, pharmaceutical testing, food and beverage analysis, and other applications where consistent refractive index measurements are critical.

The OQ standard is formulated to deliver stable and reproducible results, supporting both routine checks and in-depth qualification protocols. Its traceability to recognized reference materials makes it suitable for laboratories adhering to stringent compliance standards, including GLP and GMP requirements. The solution is ready to use and compatible with a wide range of Agilent refractive index detectors, such as those found in InfinityLab, 1200 Series, and 1260 Infinity II LC systems. It may also be employed alongside other detector qualification kits within an integrated LC platform.

By enabling reliable verification of refractive index detector functionality, this standard helps ensure data integrity, supports robust system performance, and satisfies the demands of regulated laboratory environments, ultimately contributing to confidence in critical analytical results.

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Collaboration

Tony Tang

Email: Tony.Tang@iright.com

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