March 17, 2025
by Baljit Bains, Marketing Communications Specialist, ACD/Labs
Fine-Tune Your Method for Accuracy, Reproducibility, and Efficiency
Chromatography is a powerful analytical tool used across industries to separate and identify components within a mixture. However, even the most robust chromatography systems can encounter issues that compromise results. Knowing how to troubleshoot these problems efficiently is essential for maintaining reliable performance. Here, we’ll explore common difficulties in method development and provide actionable solutions.
A Method is More than a Separation
Developing a chromatography method is more than just achieving separation—it’s about understanding the goal of the analysis, i.e., preparative scale up, quantitative, etc. This means considering structural and physical properties, selecting the right chromatographic mode and equipment, running screening experiments, and optimizing key parameters like solvents, columns, buffers, and flow rates. Since analysts need a complete, validated method and not just a separation—you must also factor in HPLC vs. UPLC, detector type, stationary phase, mobile phase composition, and more—keeping a clear plan in mind to ensure accuracy and transferability.
Factors that Affect an Analytical Method
Many factors can affect an analytical method, including:
Structural and Physical Properties
Knowledge of physicochemical properties can help you choose the correct diluent and separation conditions (column, mode of separation). Properties such as solubility, logD, logP, pKa, and pH can be quickly calculated with software tools such as and can assist with stationary phase selection.
The first step is to determine the solubility of analytes. Solubility information can help select the separation mode (i.e., reverse phase, normal phase, HILIC, and SFC), and sample diluent. Insufficient solubility can result in , blocked/damaged column, blocked injector, void in column, blocked/damaged flow cells, or even no peaks at all.
The next step is to look at pKa. Retention of ionizable compounds depends on pH. Non-charged analytes have better retention. Choose a pH at least 2 units away from the pKa.
Common problems that can occur with unsuitable pH conditions include poor peak shape (i.e., peak tailing, splitting, multiple peaks), no elution of analytes, changes in specificity and resolution, non-reproducible separations, damaged columns and flow cells, and incorrect selection of analytical wavelength. To avoid these potential issues, you should:
- Prepare the sample in a buffer solution to maintain pH
- Use a UV-transparent buffer through the entire wavelength range to prevent inaccurate absorption readings and accurately determine the analytical wavelength
Stationary Phase Selection
Choosing the right column is key to achieving optimal separation, high resolution, and consistent results in chromatographic analysis. Factors like stationary phase chemistry, particle size, column dimensions, and pore size directly impact retention, peak shape, and selectivity. Selecting the right column ensures efficient separations, reduces analysis time, and improves method robustness, leading to reliable and high-quality results.
When choosing a column, we want to achieve an acceptable resolution of >1.5. One stationary phase does not fit all cases. So, we must consider the goals of the separation as well as the molecular structure and physicochemical properties of analytes. For maximum interaction, select a column with similar polarity to the analyte. There is always a compromise between the eluent and column selection to obtain optimum retention, resolution, and selectivity.
Many things can go wrong with column selection, including poor peak shape, no retention of analytes or strong retention of analytes, changes in specificity and resolution, excessively long run times, and non-reproducible separations.
With ACD/Labs , there are two approaches to screen a set of columns:
- Fine-tuning a reference method—The column selection tool will select a set of column chemistries with selectivity close to the one used in the reference method to help you choose the correct column.
- Developing a new method—Plan a comprehensive column screening and select a set of column chemistries with orthogonal selectivity. The software calculates column difference factor (CDF) based on Tanaka parameters to rank different columns, and displays radar plots to represent the space the column occupies within these parameters.
Selection of Chromatographic Mode
Selecting the right chromatographic mode is critical for developing a robust, efficient, reproducible method. Each factor plays a key role in separation performance:
- Mobile phase composition—Determines elution strength, selectivity, and peak shape. Choosing the right solvent (e.g., acetonitrile vs. methanol) impacts retention times, resolution, and detector compatibility. For more complex separations, a single solvent system may not always work, and it may be necessary to find combinations of solvents with varying selectivity.
- Ion pair reagent—Stabilizes ionizable compounds and improves peak shape and reproducibility. The right buffer helps control interactions with the stationary phase.
- pH—Essential for ionizable compounds, as it affects their charge state, retention behavior, and peak symmetry. A well-optimized pH ensures selectivity and peak symmetry.
- Flow rate—Influences run time, column efficiency, and peak resolution. A flow rate that is too high can reduce resolution, while if it is too low it can extend analysis time unnecessarily.
- Isocratic or gradient—Influences how analytes are separated. Isocratic methods work well for simple separations, offering easier method transfer. Gradient methods are ideal for complex mixtures, improving resolution and reducing run time.
Optimizing these factors ensures the method is efficient, reproducible, and suited to the intended analysis, minimizing rework and improving overall method performance.
Screening and Optimization Experiments
Method development aims to achieve better resolution with faster separation. Resolution depends on separation selectivity, column efficiency and retention factor. Separation selectivity depends on how the analyte interacts with the stationary and mobile phase. Retention factor is dependent on many parameters, that can be easily adjusted.
Parameters are set during screening and fine-tuned in optimization to adjust retention factor (k’) and selectivity (S) for robustness. Optimization requires extensive experimental work to strike the right balance between the speed of separation and resolution, for all peak pairs in the chromatogram.
The LC Simulator tool in our method development software (Method Selection Suite and AutoChrom) builds models and simulates parameters to help with calculations, visualization and optimization. With it you can set up suitability criteria (resolution, retention factor, temperature, and run time), and use a linear or non-linear model to optimize pH, gradient, and temperature simultaneously for optimal separation with fewer experimental runs.
Optimizing these parameters is essential to achieving efficient, reproducible, and high-resolution separations. Here’s why each factor matters:
Optimizing these parameters is necessary to:
- Improve the separation of closely eluting compounds—reducing run times, and enhancing peak resolution
- Enhance analyte interactions with stationary phase, and enhance separation selectivity—influencing retention time, peak shape and reproducibility
Fine-tuning these parameters ensures a robust and high performing method. This helps achieve analytical goals while minimizing variability for method transfer.
Why Extra Column Volume (ECV) Matters in Chromatography
Extra column volume (ECV) might not be the first thing you think about in method development, but it plays a huge role in peak shape, resolution, and overall performance. ECV includes all the volume outside the column—like tubing, fittings, and detector flow cells—where dispersion can occur. Too much ECV can lead to broader peaks, reduced sensitivity, and lower resolution, especially in fast separations. Optimizing system components help to preserve sharp peaks and accurate quantification. When developing or transferring methods, accounting for ECV helps maintain consistency between instruments, improving reproducibility and data quality.
Managing ECV with software involves:
- Modeling and Simulation—software tools can simulate and visualize the effects of ECV on peak shape—helping identify and correct issues before running experiments
- Instrument Specific Adjustments—adjust system parameters like dwell volume, flow rate, and injection settings, to compensate for ECV differences
- Method Transfer Optimization—compare and align chromatograms from different instruments, ensuring consistency when transferring between systems with variations in ECV
Leveraging software tools to manage ECV helps labs to fine-tune their chromatography setup to minimize the impact of ECV, leading to more precise and reproducible results.
Understanding Dwell Volume in Chromatography
Dwell volume (also known as gradient delay volume), plays a key role in chromatography, impacting how quickly the mobile phase composition changes. It refers to the volume between where solvents mix and the column inlet, including components like mixers, transfer lines, and injection systems. In low-pressure mixing systems, it also factors in the proportioning valve and pump components.
Since different instruments have varying dwell volumes, this can affect peak retention, gradient formation, and overall method reproducibility. Adjusting gradient start times or re-optimizing parameters may be necessary to maintain consistency when transferring methods. Using software to fine-tune dwell volume settings ensures smoother method transfer, reliable results, and better chromatographic performance.
Optimizing Chromatography—Achieve Accurate and Reproducible Methods
A well-optimized chromatography method is the key to achieving accurate, reproducible, high-resolution separations. Fine-tuning factors like the stationary phase, mobile phase composition, and instrument settings can significantly enhance method performance and reliability. By using software tools for simulation, optimization, and method transfer, scientists can simplify development, create robust methods, and ensure smooth, efficient analysis across different systems.
Find out more about method development software tools.
Watch the webinar series to get a deeper understanding of the tools that can help streamline method development.
About the Author
