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Computational techniques for nanostructure determination of substances that resist standard crystallographic methods are often laborious processes starting from initial guess solutions not derived from experimental data. The Liga algorithm can create nanostructures using only lists of lengths or distances between atom pairs, providing an experimental basis for starting structures. These distance lists may be extracted from a variety of experimental probes and we illustrate the procedure with distances determined from the pair distribution function. Candidate subclusters that are a subset of a structure's atoms compete based on adherence to the length list. Atoms are added to well performing candidates and removed from poor ones, until a complete structure with sufficient agreement to the length list emerges. The Liga algorithm is shown to reliably recreate Lennard-Jones clusters from ideal length lists and the C60 structure from neutron-scattering data. The correct fullerene structure was obtained with experimental data which missed several distances and had loosened constraints on distance multiplicity. This suggests that the Liga algorithm may have robust applicability for a wide range of nanostructures even in the absence of ideal data.

Supporting information

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Gzipped tape archive (TGZ) file https://doi.org/10.1107/S0108767308027591/mk5018sup1.tgz
C++ source code package

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Gzipped tape archive (TGZ) file https://doi.org/10.1107/S0108767308027591/mk5018sup2.tgz
Program inputs and parameters for simulations reported in the paper


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