Stochastic Chromatography Retention Time Estimation
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Solution Overview
Problem
Current chromatography models are inadequate for simulating the behavior of particles in columns where operating parameters, such as temperature and phase compositions, evolve during the particle's passage, as they do not accurately account for these changes in their calculations.
Innovation Solution
A stochastic modeling approach that simulates the individual path of particles using probability laws describing their behavior in the column, allowing for the estimation of retention times and distribution based on evolving parameters like temperature and phase compositions, which can change temporally or spatially.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional chromatography models are used, then the model structure is simple, but the model cannot accurately account for parameter evolution during particle passage
Solution Approach 1:
The chromatography column is divided into multiple discrete stages along the flow path. Each stage has its own equilibrium parameters (K values) that can vary spatially. This segmentation allows the model to capture parameter evolution without requiring continuous differential equations, thus improving accuracy while maintaining computational tractability.
Solution Approach 2:
The model transitions from static equilibrium parameters to dynamic parameters that evolve along the column length. The equilibrium constant K becomes a function of position (K(z)), allowing the model to account for temperature gradients, mobile phase composition changes, or stationary phase degradation that occur during particle passage through the column.
2Manufacturing precision
If operating parameters are modulated to improve separation, then separation quality improves, but the model must account for temporal and spatial parameter evolution
Solution Approach 1:
The model预先 defines the spatial distribution of equilibrium parameters K(z) before simulation. This allows the practitioner to account for anticipated temperature gradients or composition changes without requiring real-time parameter adjustment during the simulation, simplifying the computational approach while maintaining accuracy for programmed temperature ramps or gradient elution profiles.
Solution Approach 2:
The model explicitly incorporates changes in equilibrium parameters K along the column length to reflect operating condition variations. By allowing K to be a function of position rather than a constant, the model naturally accounts for the effects of temperature modulation, mobile phase gradient composition, or stationary phase property changes on particle retention and separation.
3Measurement precision
If the model accounts for parameter evolution during particle passage, then retention time estimation accuracy improves, but computational complexity increases
Solution Approach 1:
The model replaces complex continuous differential equations with a discrete stage-based computational approach. Instead of solving partial differential equations that describe continuous parameter evolution, the system uses iterative calculations over discrete stages with defined equilibrium parameters, significantly reducing computational complexity while preserving the ability to model parameter evolution effects on retention time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides a more accurate modeling of chromatography columns by accounting for parameter evolution, leading to improved separation and retention time predictions, enhancing the precision of chromatogram estimation.
Implementation Method 1
The wall of the channel has a coating, called stationary phase, with which the particle has an affinity, such that the particle is capable of being momentarily adsorbed, then desorbed.
Implementation Method 2
a particle travels through a channel, between an inlet and an outlet, being carried by a fluid, called carrier fluid
Data Source
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Figure 3A
AI summary
The invention is a method for estimating the retention time of a particle in a chromatography column, and more particularly in a chromatography column in which a parameter, such as temperature, is modulated. The retention time is estimated probabilistically by sequentially modeling the particle's path through the column. When this stochastic approach is applied to a set of particles of the same type, it allows for the determination of a statistical distribution of the retention time in the column.