Improving Evaporative Light Scattering Detector performance using Experiments and Modelling

Abstract

Agilent’s Evaporative Light Scattering Detector (ELSD) detects analyte concentration and is often used in conjunction with chromatographic techniques, wherein the chromatographic eluent is atomised to produce a spray which is dried in a ‘drift-tube’ and detected via light scattering. At present, in the wider literature, the underlying physics of the process is poorly understood. This gap in the understanding of the concepts involved is addressed through experiments and the development of models that elucidate the mechanics of the three main stages in the detector: atomisation, transport and evaporation, and light scattering. At the simplest level, transfer functions for the different stages are obtained via a combination of experiment and modelling, and joined together linking inputs (concentration, fluid properties, temperature, pressure, geometric parameters, index of refraction) to outputs (spray droplet size distribution, light scattering intensity). This study investigates the particle morphology and size distribution of analytes dried through an ELSD by employing multiple particle sizing techniques, including the Phase Doppler Particle Analyzer (PDPA), the Aerodynamic Aerosol Classifier (AAC), and the Scanning Mobility Particle Sizer (SMPS), to characterise droplet and particle distributions at various stages within the device. Initial droplet size distributions were reconstructed using dioctyl sebacate (DOS) as a non-evaporating surrogate and correlated to water droplets. Downstream particle measurements were conducted for caffeine, dextran, and citric acid at different concentrations and operating conditions. Scanning Electron Microscopy (SEM) was used to examine dried particle morphology. Results show that analyte properties significantly influence final particle size and morphology, with implications for ELSD detection mechanisms. This comprehensive characterisation of the drying process within the ELSD provides valuable insights into its operation and performance across different analytes. This study also presents a comprehensive model for simulating aerosol dynamics and signal response in the ELSD. The model integrates theoretical frameworks for atomisation, droplet transport, evaporation, and light scattering with computational fluid dynamics (CFD) simulations and experimental validation. A physically-based model is developed to predict ELSD signal response based on input parameters including chemical species properties, operational settings, and environmental conditions. The model accounts for complex phenomena such as multi-component evaporation, particle impingement, and size-dependent light scattering. CFD simulations provide detailed insights into flow characteristics within the ELSD geometry. Model predictions are compared against experimental data for various analytes and solvents across a range of concentrations and temperatures. The model accurately captures trends for volatile and semi-volatile species, but discrepancies are observed for non-volatile analytes at higher temperatures. This work advances understanding of ELSD operation and provides a tool for optimising detector performance and interpreting results in chromatographic applications.