Accurate (n,m) Assignment of Single-Walled Carbon Nanotubes From Electron Diffraction Patterns Via Local Candidate Search and Self-Consistency Correction.

The chirality (n,m) of single-walled carbon nanotubes (SWCNTs) critically governs their properties and growth behavior, yet reliable assignment from nanobeam electron diffraction (NBED) remains challenging because of analyst-dependent procedures, manual measurement errors, and nanotube tilt relative to the incident electron beam. Here, a practical and interpretable chirality-assignment protocol is developed by extending a calibration-free diffraction-analysis framework with local candidate search and self-consistency-based cross-check correction. Feature extraction and candidate screening are semiautomated using an ImageJ script and an Excel VBA macro to improve efficiency and reproducibility. The protocol is evaluated using 2394 simulated NBED images spanning diameters of 0.48-2.3 nm, chiral angles of 0°-30°, and tilt angles of 0.5°-16.5°. The exact assignment accuracy increases from 71.6% with conventional TRUNC-based analysis to 97.7% with the proposed protocol, while errors in the mean diameter, mean chiral angle, and metallic SWCNT fraction are substantially reduced. The improvement is mainly enabled by the newly introduced overlap ratio, which serves as the primary criterion for final candidate ranking. This error-resilient workflow provides a reproducible route for extracting reliable structural information from experimentally imperfect diffraction patterns without requiring instrument calibration or data-driven model training.