Agilent Captiva syringe filters
Brochures and specifications | 2019 | Agilent TechnologiesInstrumentation
Filtration of liquid samples is a critical preparatory step in analytical chemistry workflows. Proper removal of particulates extends column lifetime, ensures reproducible chromatographic performance, and minimizes contamination. Agilent Captiva syringe filters offer a balance of high throughput, low extractables, and minimal protein binding, making them suitable for demanding applications in pharmaceutical, environmental, and biochemical analysis.
This white paper evaluates the performance advantages of Agilent Captiva syringe filters relative to competing products. Key goals include:
Filtration experiments involved passing a 0.3 µm latex‐bead suspension through syringe filters and measuring backpressure on a sub‐2 µm chromatographic column over repeated injections. Filtration efficiency was determined by comparing particulate removal across multiple filter membranes and suppliers. All tests followed standard liquid chromatography protocols, employing consistent solvent matrices and flow rates.
The studies demonstrate that Captiva filters deliver industry-leading flow rates and capacity. In column lifetime tests, unfiltered samples caused backpressure to rise sharply after fewer than 150 injections. In contrast, samples filtered through 0.3 µm Captiva membranes exceeded 800 injections before equivalent pressure increases, indicating an over fivefold extension of column life.
Filtration efficiency measurements against rival 0.2 µm and 0.45 µm nylon filters showed average removal rates above 96 % for Captiva products, compared to sub-90 % performance from other suppliers. Protein binding tests confirmed that premium PES membranes exhibit the lowest nonspecific adsorption, critical for bioanalytical assays. Extractables analysis verified negligible leachables under certified conditions.
By integrating Captiva syringe filters, laboratories can:
Advancements in membrane technology will focus on enhancing chemical compatibility and further reducing nonspecific binding. Emerging applications in proteomics and nanomaterial analysis will benefit from ultra-low protein adsorption filters. Integration with automated sample preparation platforms and disposable vial formats will streamline high-throughput workflows.
Agilent Captiva syringe filters provide a robust solution for demanding analytical workflows, offering high flow rates, superior filtration efficiency, and extended column life. Their low protein binding and minimal extractables make them well suited for both routine QC analyses and advanced research applications.
No external literature references were provided in the original document.
Consumables
IndustriesManufacturerAgilent Technologies
Summary
Importance of the Topic
Filtration of liquid samples is a critical preparatory step in analytical chemistry workflows. Proper removal of particulates extends column lifetime, ensures reproducible chromatographic performance, and minimizes contamination. Agilent Captiva syringe filters offer a balance of high throughput, low extractables, and minimal protein binding, making them suitable for demanding applications in pharmaceutical, environmental, and biochemical analysis.
Objectives and Study Overview
This white paper evaluates the performance advantages of Agilent Captiva syringe filters relative to competing products. Key goals include:
- Assessing flow rates and loading capacity.
- Measuring protein binding characteristics.
- Comparing extractable levels under standard conditions.
- Quantifying the impact on column lifetime and filtration efficiency.
Methodology and Instrumentation
Filtration experiments involved passing a 0.3 µm latex‐bead suspension through syringe filters and measuring backpressure on a sub‐2 µm chromatographic column over repeated injections. Filtration efficiency was determined by comparing particulate removal across multiple filter membranes and suppliers. All tests followed standard liquid chromatography protocols, employing consistent solvent matrices and flow rates.
Key Results and Discussion
The studies demonstrate that Captiva filters deliver industry-leading flow rates and capacity. In column lifetime tests, unfiltered samples caused backpressure to rise sharply after fewer than 150 injections. In contrast, samples filtered through 0.3 µm Captiva membranes exceeded 800 injections before equivalent pressure increases, indicating an over fivefold extension of column life.
Filtration efficiency measurements against rival 0.2 µm and 0.45 µm nylon filters showed average removal rates above 96 % for Captiva products, compared to sub-90 % performance from other suppliers. Protein binding tests confirmed that premium PES membranes exhibit the lowest nonspecific adsorption, critical for bioanalytical assays. Extractables analysis verified negligible leachables under certified conditions.
Benefits and Practical Applications
By integrating Captiva syringe filters, laboratories can:
- Increase sample throughput with faster filtration.
- Reduce maintenance costs through longer column lifetimes.
- Improve data accuracy by minimizing particulate and protein interference.
- Ensure compliance with low-extractable requirements in regulated environments.
Future Trends and Applications
Advancements in membrane technology will focus on enhancing chemical compatibility and further reducing nonspecific binding. Emerging applications in proteomics and nanomaterial analysis will benefit from ultra-low protein adsorption filters. Integration with automated sample preparation platforms and disposable vial formats will streamline high-throughput workflows.
Conclusion
Agilent Captiva syringe filters provide a robust solution for demanding analytical workflows, offering high flow rates, superior filtration efficiency, and extended column life. Their low protein binding and minimal extractables make them well suited for both routine QC analyses and advanced research applications.
Reference
No external literature references were provided in the original document.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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