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Don’t Lose It: Getting Your Peaks in Shape - Choosing columns and conditions for thebest peak shape

Presentations | 2020 | Agilent TechnologiesInstrumentation
Consumables, LC columns
Industries
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Agilent Technologies

Summary

Importance of Topic


High-performance liquid chromatography (HPLC) relies on well-shaped peaks to deliver precise quantitation, high sensitivity and efficient separations. Poor peak shape—manifested as tailing, fronting, broadening or splitting—reduces resolution, compromises accuracy and shortens column life. Understanding and controlling parameters that govern peak symmetry is critical for robust method development and routine quality control in pharmaceutical, environmental and industrial analyses.

Objectives and Overview of the Study


This application note by Golnar Javadi (Agilent Technologies, 2020) examines:
  • Definitions and metrics of good peak shape (Gaussian symmetry, tailing and asymmetry factors, efficiency).
  • Common peak shape problems and their origins.
  • Influential factors across column chemistry, mobile phase, fittings, instrumentation and sample preparation.
  • Practical guidelines to optimize chromatographic conditions for reproducible, high-quality peaks.

Methodology and Instrumentation


The study reviews established metrics:
  • USP tailing factor at 5% peak height and asymmetry factor at 10%.
  • Number of theoretical plates (N) and peak width at half-height.
  • Van Deemter relationships to identify optimum linear velocity and flow rate.

Instrumentation examples include Agilent 1200/1260/1290 Infinity LC systems with diode array detectors (Max-Light or standard flow cells) and LC/MS/MS configurations. Column chemistries range from fully endcapped C18 and embedded polar phases to high-pH-stable Poroshell and Extend-C18 media. InfinityLab Quick Connect fittings and low-dead-volume capillaries minimize extra-column broadening.

Main Results and Discussion


Key findings highlight how each category impacts peak shape:
  • Column chemistry: High-purity, low-acidity silica and double/triple endcapping reduce silanol interactions and tailing of basic analytes.
  • Particle technology: Superficially porous (Poroshell) particles enable high efficiency at elevated flow rates for small molecules and biopolymers.
  • Mobile phase: Buffer composition, pH and additive selection (e.g., TEA, TFA, competing acids) control ionization and silanol shielding. Optimal buffer strength (20–50 mM) and pH choice relative to analyte pKa improve symmetry.
  • Temperature and organic modifier selection (acetonitrile vs. methanol) fine-tune viscosity and solute partitioning.
  • Connections and fittings: Properly sized tubing and spring-loaded connectors prevent extra-column volume and improper seating that cause peak broadening or splitting.
  • Detector settings: Data collection rate and flow cell volume must match peak widths to preserve shape.
  • Sample factors: Injection volume, solvent strength, cleanliness and metal chelation can induce fronting, tailing or peak distortion.

Benefits and Practical Applications


Applying these insights yields:
  • Improved resolution and sensitivity for complex mixtures.
  • More accurate and reproducible quantitation in QA/QC environments.
  • Extended column lifetime and lower maintenance costs.
  • Faster analyses with high-throughput superficially porous columns.

Future Trends and Possibilities for Use


Emerging directions include:
  • Advanced hybrid and high-pH-stable stationary phases for broader pH ranges and challenging basic compounds.
  • Micro- and nano-flow LC with ultra-low volume fittings to enhance MS sensitivity.
  • Predictive modelling and machine learning to automate method development and optimize peak shape.
  • Integration of novel buffer systems and green solvents to improve environmental sustainability.

Conclusion


Peak shape optimization in HPLC is a multi-parameter challenge. Selection of appropriate column chemistry, mobile phase conditions, system hardware and sample handling protocols is essential to achieve symmetrical, high-efficiency peaks. Implementing the recommended guidelines supports reliable method performance and accelerates analytical workflows across research and quality assurance laboratories.

References


  • Javadi G. Don’t Lose It: Getting Your Peaks in Shape. Agilent Technologies Application Note, July 2020.

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

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