Highly Parallel Simulation Tool for the Design of Isotachophoresis Experiments

Abstract

Background

Isotachophoresis (ITP) is a well-established electrokinetic method for separation and preconcentration of analytes. Several simulation tools for ITP have been published, but their use for experimental design is limited by the computational time for a single run and/or by the number of conditions that can be investigated per simulation run. A large fraction of the existing solvers also do not account for ionic strength effects, which can influence whether an analyte focuses in ITP. There is currently no publicly available tool for the easy and rapid design of ITP experiments.

Results

We present a rapid, highly parallelized steady-state solver for the design of buffer electrolytes in ITP experiments. The tool is called Browser-based Electrolyte Analyses for ITP (BEAN). BEAN is designed to facilitate the evaluation and identification of functional buffer chemistries for ITP. Given a user-defined chemistry system, BEAN solves a set of coupled, non-linear integral conservation equations to determine whether a specific analyte is focused by the ITP system, and estimates quantities of interest in the design of related ITP processes. These quantities include zone concentrations, pH, and effective (observable) mobility values. BEAN also computes 972 variations of the specified ITP chemistry, including a broad range of buffer titrations and ion mobilities. All the calculations performed in BEAN include ionic strength and finite ionic radius effects, and the solver handles species with arbitrary valence. The tool further includes a searchable database of 521 commonly used electrolytes. BEAN is available at microfluidics.stanford.edu/bean.

Significance

This study introduces a novel tool that integrates known ITP steady-state equations with a highly parallel computational framework, an electrolyte database, and a web-based interface. BEAN requires no license nor compilation, and its parallel computations are performed automatically without specific implementation needed from the user. This enables users to screen wide ranges of experimental conditions in the design of ITP experiments.