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) strongly influences their properties and growth behavior, requiring accurate and reproducible evaluation methods. Nanobeam electron diffraction (NBED) is a powerful approach for ( n , m ) assignment, but practical analysis is often affected by analyst-dependent steps, manual measurement errors, and the tilt of individual nanotubes relative to the incident electron beam. Here, building on the previously developed calibration-free diffraction analysis framework, we further developed a practical SWCNT chirality-assignment protocol that combines local candidate search with self-consistency-based cross-check correction while explicitly accounting for manual measurement errors and CNT tilt. Feature extraction and candidate screening were semi-automated using an ImageJ script and an Excel VBA macro, thereby improving efficiency and reproducibility. Using 2394 simulated NBED images covering CNT diameters of 0.4–2.3 nm, chiral angles of 0–30°, and tilt angles of 0.5–16.5°, the assignment accuracy improved from 71.6% for conventional TRUNC-based analysis to 97.7% with the proposed protocol. Errors in mean CNT diameter, mean chiral angle, and metallic CNT fraction were also significantly reduced. This improvement was primarily attributable to the newly introduced overlap ratio, which reduced ambiguity in initial candidate selection.