A convergence metric for counting statistics in time-resolved small angle neutron scattering

Area of Science:

• Materials Science
• Physics
• Chemistry

Background:

• Time-resolved small-angle neutron scattering (TR-SANS) is crucial for studying dynamic processes in soft matter.
• Determining optimal measurement duration is challenging, often leading to inefficient data collection.

Purpose of the Study:

• To develop a model-independent metric for predicting optimal TR-SANS measurement duration.
• To enable real-time experimental optimization and improve efficiency in neutron scattering.

Main Methods:

• Utilized Gaussian process regression to reconstruct scattering profiles with quantified uncertainty.
• Developed a dimensionless convergence metric based on early-time data.
• Applied the method to the EQ-SANS instrument and generalized it for 2D detectors.

Main Results:

• Discovered a universal power-law scaling in profile evolution across soft matter systems.
• Demonstrated that normalized time data collapses onto a single curve within the first ten time steps.
• Enabled early prediction of measurement sufficiency.

Conclusions:

• The developed metric accurately predicts optimal TR-SANS measurement duration using minimal data.
• This approach significantly enhances experimental efficiency, particularly in low-flux neutron sources.
• The findings are applicable to various soft matter systems and SANS instruments.