PerMix: Algorithmic Pathway Planning for Multicomponent Halide Perovskite Synthesis
Abstract
The reproducible growth of multicomponent halide perovskite single crystals depends critically on the stoichiometry of the precursor solution: even small deviations introduced during weighing or dissolution can change phase purity, defect density, and the lattice parameters of the resulting crystals. Today, recipes for such systems are still planned largely by hand in spreadsheets, which are error-prone, difficult to audit, and impractical for the compositional spaces of multicomponent solid solutions. We present PerMix, an open-source Python framework that formalizes precursor planning as a constrained mass-balance problem and solves it transparently. The stoichiometric model, the combinatorial enumeration of precursor pathways based on a rigid/flexible partition of cations, tolerance-based validation, deduplication of identical salt formulations, deterministic ranking of pathways, geometric stability indicators (Goldschmidt tolerance and octahedral factors), and the SQLite reference database are described in full, with every governing equation stated explicitly. The tool was used to grow nine (MA1−xCsx)Pb(Br1−zYz)3 (Y = Cl, I) single crystals by antisolvent vapor-assisted crystallization; X-ray diffraction shows the systematic lattice expansion and contraction expected from the nominal substitutions. We also discuss the limits of the approach explicitly: precursor stoichiometry does not account for ion segregation, and quantitative composition analysis as well as homogeneity profiling are identified as future work.
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BibTeX
@misc{schmidberskaya2026permix,
title = {{PerMix: Algorithmic Pathway Planning for Multicomponent Halide Perovskite Synthesis}},
author = {Arina P. Schmidberskaya and Ilia O. Simonenko},
howpublished = {ChemRxiv},
year = {2026},
month = oct,
doi = {10.26434/chemrxiv.15010868/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010868/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - PerMix: Algorithmic Pathway Planning for Multicomponent Halide Perovskite Synthesis
AU - Arina P. Schmidberskaya
AU - Ilia O. Simonenko
PY - 2026
DA - 2026/10/22
PB - ChemRxiv
DO - 10.26434/chemrxiv.15010868/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010868/v1
AB - The reproducible growth of multicomponent halide perovskite single crystals depends critically on the stoichiometry of the precursor solution: even small deviations introduced during weighing or dissolution can change phase purity, defect density, and the lattice parameters of the resulting crystals. Today, recipes for such systems are still planned largely by hand in spreadsheets, which are error-prone, difficult to audit, and impractical for the compositional spaces of multicomponent solid solutions. We present PerMix, an open-source Python framework that formalizes precursor planning as a constrained mass-balance problem and solves it transparently. The stoichiometric model, the combinatorial enumeration of precursor pathways based on a rigid/flexible partition of cations, tolerance-based validation, deduplication of identical salt formulations, deterministic ranking of pathways, geometric stability indicators (Goldschmidt tolerance and octahedral factors), and the SQLite reference database are described in full, with every governing equation stated explicitly. The tool was used to grow nine (MA1−xCsx)Pb(Br1−zYz)3 (Y = Cl, I) single crystals by antisolvent vapor-assisted crystallization; X-ray diffraction shows the systematic lattice expansion and contraction expected from the nominal substitutions. We also discuss the limits of the approach explicitly: precursor stoichiometry does not account for ion segregation, and quantitative composition analysis as well as homogeneity profiling are identified as future work.
ER -