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Chiral hierarchies at the nanoscale revealed by three-dimensional scanning electron diffraction

Mathias Nero · Mads Carlsen · Marianne Liebi · Tom Willhammar

17 Jun 2025 · 10.26434/chemrxiv-2025-8csxn

Abstract

Natural biocomposites such as wood and plant cell walls exhibit remarkable mechanical properties largely attributed to their nanoscale chiral organization of fibrous components, such as cellulose. However, resolving the three-dimensional (3D) arrangement of these structures at the nanoscale remains a significant challenge, particularly in beam-sensitive materials. This study introduces a method for 3D reconstruction of orientation based on scanning electron diffraction (SED), enabling the quantitative mapping of chiral supramolecular organization with sub-100 nm spatial resolution. By acquiring low-dose SED data at multiple tilt angles and applying a symmetry-based reconstruction algorithm, we resolved the 3D orientation of cellulose fibrils in native oat husk and birch wood. Our results reveal a multilayered cell wall architecture with alternating helical handedness, providing precise measurements of 3D fibril orientation. This method reveals complex hierarchical structures at the nanoscale, enabling rapid data acquisition and analysis using widely available instrumentation. The ability to resolve such chiral organization opens new understanding of materials properties as well as opportunities for the design of bio-inspired materials with tunable mechanical and functional properties.

Code and data availability

The article's Data and Code Availability statement declares that the SED datasets (diffraction data from oat husk and birch wood) and the authors' custom Python analysis script are publicly available on Zenodo (DOI: 10.5281/zenodo.15647651). This is a paper-specific, public, actionable asset directly reproducing the 3D

Datasetpublic

Data and Code Availability SED data and Python script for SED data analysis used in this study are available from Zenodo (DOI: 10.5281/zenodo.15647651).

Open resource ↗Zenodo · 10.5281/zenodo.15647651 · pdf-page:19 lines:1-36
Codepublic

SED data and Python script for SED data analysis used in this study are available from Zenodo (DOI: 10.5281/zenodo.15647651).

Open resource ↗Zenodo · 10.5281/zenodo.15647651 · pdf-page:19 lines:1-36