Modeling impurity concentrations in liquid argon detectors

TL;DR

This paper develops and experimentally verifies a model for impurity dynamics in liquid argon detectors, enabling better control of impurity levels crucial for neutrino and dark matter experiments.

Contribution

The paper introduces a validated model for impurity transport in liquid argon detectors, including a simple exponential solution for impurity concentration analysis.

Findings

Henry's coefficient for oxygen in LAr is 0.84$^{+0.09}_{-0.05}$

The model accurately describes impurity concentrations under various conditions

Flow barriers can effectively reduce impurity levels in large detectors

Abstract

Impurities in noble liquid detectors used for neutrino and dark matter experiments can significantly impact the quality of data. We present an experimentally verified model for describing the dynamics of impurity distributions in liquid argon (LAr) detectors. The model considers sources, sinks, and transport of impurities within and between the gas and liquid argon phases. Measurements of oxygen concentrations in a 20-L LAr multi-purpose test stand are compared to calculations made with this model to show that an accurate description of the concentrations under various operational conditions can be obtained. A result of this analysis is a determination of Henry's coefficient for oxygen in LAr. These calculations also show that some processes have small effects on the impurity dynamics and excluding them yields a solution as a sum of two exponential terms. This solution provides a simple way to extract Henry's coefficient with negligible approximation error. It is applied to the data and the Henry's coefficient for oxygen in LAr is obtained as 0.84$^{+0.09}_{-0.05}$, consistent with literature results. Based on the analysis of the data with the model, we further suggest that, for a large liquid argon detector, barriers to flow ("baffles") installed in the gas phase to restrict flow can help reduce the ultimate impurity concentration in the LAr.