# One-pot neutron imaging of liquid–gas system: a parametric method study

## TL;DR

This paper introduces improved neutron imaging techniques to study liquid-gas interactions under different pressure and temperature conditions.

## Contribution

A Python-based pipeline and hardware improvements enhance the accuracy and efficiency of one-pot neutron imaging.

## Key findings

- Hardware improvements reduce uncertainty in surface tension measurements.
- A Python pipeline enables efficient data processing and meniscus shape detection.
- The parametric study demonstrates the method's effectiveness for interfacial phenomena.

## Abstract

We present advancements in the one-pot neutron imaging method for investigating hydrocarbon-based liquid–gas interactions under varying pressure and temperature. Improvements in hardware enable the optimization of cell geometry and material, overall leading to reduced uncertainty in surface tension measurements. The integration of snubbers minimizes initial pressure surge, improving experimental stability. A Python-based pipeline is developed for image batch-processing, incorporating rigorous image reduction algorithms specific to the one-pot approach. This results in efficient data management and enhanced meniscus shape detection. Moreover, we provide a parametric study on chosen variables to further demonstrate the one-pot neutron imaging as a powerful tool for studying interfacial phenomena and fluid for a wide variety of applications.

The online version contains supplementary material available at 10.1007/s10967-025-10561-w.