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Shimadzu Gel Permeation Chromatography System - Nexera GPC System

Brochures and specifications | 2020 | ShimadzuInstrumentation
GPC/SEC
Industries
Manufacturer
Shimadzu

Summary

Importance of the Topic


Gel permeation chromatography (GPC) remains a cornerstone technique for characterizing polymer molecular weight distributions, intrinsic viscosity, and additive content. Accurate polymer profiling is critical across industries—from quality control in manufacturing to research and development of advanced materials. The integration of automated intelligence and robust instrumentation enhances data reliability and throughput, making GPC indispensable for routine and challenging applications.

Objectives and Overview


This application note introduces the Shimadzu Nexera GPC System, detailing its design features, automated analytical intelligence functions, and performance metrics. The aim is to demonstrate how the system improves precision, protects columns, streamlines workflows, and expands analytical capabilities for both organic and aqueous polymer analyses.

Methodology and Instrumentation Used


Analytical workflows leverage the following components:
  • Controller: CBM-40 series
  • Pump: LC-40D parallel double-plunger pump with FlowPilot for gradual flow ramping
  • Degasser: DGU-403 vacuum membrane unit
  • Autosampler: SIL-40C series with overlap injection functionality
  • Column oven: CTO-40C with forced-air circulation, 10 °C above ambient to 85 °C
  • Detector: RID-20A differential refractive index detector with dual temperature control (30–60 °C), auto-purge reference cell, and optional recycle valve kit
  • Software: LabSolutions GPC module for calibration, peak integration, system suitability testing, and automated report generation
  • Columns: Shim-pack GPC series (polystyrene gels for THF, CHCl₃, DMF; mixed gels; preparative columns)

Main Results and Discussion


Automated intelligence features such as FlowPilot protect columns by avoiding sudden pressure changes and pump starts/stops. Real-time mobile phase level monitoring prevents run-out events via weight sensors. Auto-diagnosis of pressure fluctuations triggers flow-path purging and seamless restart, minimizing sample loss. Overlapped injection cuts multi-sample cycle times by nearly 50%, boosting throughput. High-speed micro-plunger actuation and pulse compensation deliver excellent retention reproducibility, crucial for reliable molecular weight determination. The RID-20A’s dual-temperature control reduces baseline drift after power-up and, with the recycle valve kit, lowers solvent consumption by ~30%. Combining RID and PDA detectors with MCR-ALS peak convolution enables identification and quantitation of coeluted additives within a single run.

Benefits and Practical Applications


  • Reproducible molecular weight and polydispersity data regardless of operator skill
  • Protection of expensive GPC columns and reduction of maintenance downtime
  • Automated system suitability testing ensures data quality before each batch
  • Flexible report generation and database storage support paperless, compliant laboratory operations
  • Wide application range: from high-sensitivity nano-scale analysis to preparative separations

Future Trends and Possibilities


Advances in digital instrumentation and artificial intelligence are expected to further automate decision-making, predictive maintenance, and remote monitoring. Integration with mass spectrometry and advanced detectors will enable deeper structural insight and real-time compositional analysis. Higher flow-rate preparative GPC and greener solvent recycling schemes will support sustainable large-scale polymer separations.

Conclusion


The Shimadzu Nexera GPC System combines analytical intelligence with high-performance hardware and software to deliver robust, operator-independent polymer characterization. Its modular design, automated diagnostics, and data processing tools make it a versatile platform for both routine QC and advanced research in polymer science.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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