Skip to content
Preprint

FDTBX - Computational Tools for Simulation of X-ray Fiber Diffraction Patterns from Atomic Coordinates

Aug 2026 · 0 citations · 6 references
Physics

Abstract

Fiber diffraction is one of the few experimental techniques capable of resolving molecular structure in partially ordered, non-crystalline systems such as fibrous proteins, biopolymers and synthetic polymers. Because fiber diffraction patterns are complex, exhibiting paracrystalline order, packing defects and broad, overlapping reflections, their interpretation relies on model-based refinement, in which theoretical patterns simulated from candidate atomic models are iteratively compared with experiment. We present fdtbx, a modern, open and extensible Python toolbox for simulating X-ray fiber diffraction patterns directly from atomic coordinates. Built on the crystallographic library cctbx and designed for readability and multicore execution, fdtbx computes structure factors from a PDB model and constructs realistic reciprocal-space reflection profiles that incorporate the principal physical broadening mechanisms of fiber diffraction: finite crystallite size, orientational disorder (with Gaussian, Lorentzian and Voigt angular peak shapes) and paracrystalline (second-kind) lattice disorder in Hosemann's formulation. A per-reflection shell-quadrature scheme evaluates the required convolutions at arbitrary query points rather than on a fixed grid, giving direct control over the trade-off between accuracy and speed, and an analytic Ewald-projection routine maps each sampled reflection, with an appropriate Lorentz correction, onto a flat detector to produce a simulated pattern for direct comparison with measured images. We illustrate the toolbox on $\alpha$-chitin, cellulose~I$\alpha$ and I$\beta$, cellulose triacetate and A-form DNA, and outline a practical simulation workflow. By providing a transparent, well-documented and parallelizable implementation of the specialized algorithms of fiber diffraction, fdtbx lowers the barrier to reproducible model-based analysis.

View source

Similar papers

Preprint Sep 2026

Simulating Continuous-Rotation 3D Electron Diffraction: A Multislice and Bloch Wave Framework

To improve the agreement between measured and calculated intensities of three-dimensional electron diffraction (3D ED) experiments, a simulation pipeline is needed to assess and quantify the influence of various structural and experimental parameters. We present a computational pipeline, built upon the abTEM Python pac...

M. Cabaj, Jacob Madsen, T. Susi et al. · 0 citations
Review Open access Aug 2026

From Static Structures to Molecular Dynamics: Emerging Directions in X-Ray and Electron Materials Characterization

Structural analysis using X-rays and electron beams has long provided the average arrangement of atoms and molecules—that is, “structural information”—with high precision. By contrast, static measurements cannot directly yield dynamic information on how a material changes over time; instead, information on motion is co...

Daisuke Sasaki, Kazuhiro Mio, Yuji C. Sasaki · 0 citations
Open access Nov 2026

The role of absorption in 3D electron diffraction dynamical structure refinement.

The role of absorption in 3D electron diffraction is established through analytical theory, simulation and dynamical refinement. A two-beam expression for the absorbed integrated intensity in centrosymmetric crystals is derived, showing that for t/ξg ≪ 1 reflections follow a uniform exponential decay set by the mean ab...

Benjamin Colmey, T. Doherty, Shreshth A. Malik et al. · 0 citations
Open access Sep 2026

PARCE: Accurate Inference of Crystal Structure Information From Phonon Vibrational Modes

An accurate description of crystal structures is a prerequisite for experimental synthesis and understanding of the physicochemical properties of materials. However, conventional X‐ray diffraction (XRD) often requires stringent experimental conditions and offers limited access to certain types of data, highlighting t...

Hong-Yu Chen, Meng-Yu Dai, Hong-Jian Chen et al. · 0 citations
Open access Sep 2026

Deterministic combinatorial calculation of lattice parameters using Python

Introduction: Determining lattice parameters is crucial for characterizing crystalline materials, as these constants dictate their physical and chemical behavior. While Rietveld refinement is the standard, it can be unnecessarily complex when the goal is limited to finding lattice parameters, particularly for low-sy...

Jones Soares, Jobson Soares · 0 citations
Open access Sep 2026

Combining X‑ray Diffraction, Solid-State NMR, and Computational Chemistry for Structural Insights and Performance Evaluation of GIPAW/GIAO 13C Chemical-Shift Calculations for Lamivudine and Three Pharmaceutical Salts

The increasing prevalence of polymorphism and multicomponent crystal forms in active pharmaceutical ingredients demands rigorous structural characterization tools for quality control. Here, lamivudine and three pharmaceutical salts, hydrochloride, salicylate monohydrate, and hydrogen phthalate, were investigated by com...

Jefferson R. Dias-Silva, V. S. Ferreira, F. Martins et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.