Nanocraft: Nanocrystal Assembly and Functionalization Toolkit

Abstract

Nanoparticles find broad applications in optoelectronics, catalysis, and nanomedicine. While machinelearning and computational screening can accelerate their design, the structural chemical space of these materials remains underrepresented in current databases. Obtaining realistic atomistic models requires the proper representation of both the inorganic core and its surface chemistry, which are commonly treated through disjoint workflows relying on separate tools. We present Nanocraft, an open source Python toolkit for the generation and functionalization of nanocrystals and nanoparticles. Operating locally through an accessible Jupyter Notebook interface, Nanocraft does not require advanced coding skills and enables the rapid generation and manipulation of large datasets by varying core stoichiometries, shapes, ligand types and surface coverage. The toolkit provides automated surface passivation based on local oxidation states and enables facet selective ligand attachment within a single framework. Its structure generation pipeline accepts crystallographic CIF files or XYZ supercells and exports the resulting structures in XYZ format for direct use in molecular dynamics, density functional theory, and machine-learning workflows. We demonstrate Nanocraft’s capabilities by constructing a dataset of thiolcapped CdSe quantum dots. Both Nanocraft and the supporting information, including a User Guide, are available at https://github.com/jgrll/Nanocraft/.

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Cite

BibTeX RIS

BibTeX

@misc{grill2026nanocraft,
  title = {{Nanocraft: Nanocrystal Assembly and Functionalization Toolkit}},
  author = {Justin Grill and Dominik Domin and Christophe Humbert and Carine Clavaguéra},
  howpublished = {ChemRxiv},
  year = {2026},
  month = sep,
  doi = {10.26434/chemrxiv.15009532/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009532/v1},
  note = {CC BY},
}

RIS

TY  - UNPB
TI  - Nanocraft: Nanocrystal Assembly and Functionalization Toolkit
AU  - Justin Grill
AU  - Dominik Domin
AU  - Christophe Humbert
AU  - Carine Clavaguéra
PY  - 2026
DA  - 2026/09/28
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15009532/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009532/v1
AB  - Nanoparticles find broad applications in optoelectronics, catalysis, and nanomedicine. While machinelearning and computational screening can accelerate their design, the structural chemical space of these materials remains underrepresented in current databases. Obtaining realistic atomistic models requires the proper representation of both the inorganic core and its surface chemistry, which are commonly treated through disjoint workflows relying on separate tools. We present Nanocraft, an open source Python toolkit for the generation and functionalization of nanocrystals and nanoparticles. Operating locally through an accessible Jupyter Notebook interface, Nanocraft does not require advanced coding skills and enables the rapid generation and manipulation of large datasets by varying core stoichiometries, shapes, ligand types and surface coverage. The toolkit provides automated surface passivation based on local oxidation states and enables facet selective ligand attachment within a single framework. Its structure generation pipeline accepts crystallographic CIF files or XYZ supercells and exports the resulting structures in XYZ format for direct use in molecular dynamics, density functional theory, and machine-learning workflows. We demonstrate Nanocraft’s capabilities by constructing a dataset of thiolcapped CdSe quantum dots. Both Nanocraft and the supporting information, including a User Guide, are available at https://github.com/jgrll/Nanocraft/.
ER  -

Abstract

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