Single-shot spatially-localized NQR using field-dependent relaxation rates

Area of Science:

• Solid-state physics
• Analytical chemistry
• Materials science

Background:

• Nuclear quadrupole resonance (NQR) is vital for characterizing solids with quadrupolar nuclei.
• NQR applications include detecting explosives and authenticating pharmaceuticals.
• Spatially-resolved NQR is crucial for automated analysis and object authentication.

Purpose of the Study:

• To develop a rapid, single-shot method for spatially-resolved NQR.
• To leverage field-dependent NQR relaxation rates for spatial mapping.
• To enhance spatial resolution and classification using machine learning (ML).

Main Methods:

• Utilized field-dependent NQR relaxation rates to convert relaxation time distributions into spatial distributions.
• Employed Laplace inversion of time-domain data in a static field gradient.
• Applied machine learning for classifying spatial distributions and improving resolution.

Main Results:

• Successfully validated the method using 35Cl and 37Cl NQR of sodium chlorate.
• Demonstrated accurate ML-based classification of 3D-printed objects with sodium chlorate distributions.
• Achieved NQR-based "embedded barcodes" for high-value object authentication.

Conclusions:

• The proposed single-shot NQR method offers rapid, spatially-resolved analysis.
• ML integration significantly improves classification accuracy and spatial resolution.
• This technique holds promise for advanced authentication and material characterization applications.