Data-driven Prediction of HSQ Polymer Structure and Silicon Nanocrystal Photoluminescence

Maharram Jabrayilov; Jeremy B. Essner; Abhijit Bera; V. Paris; Matthew G. Panthani

doi:10.1039/d5dt01479d

January 1, 2025Dalton TransactionsOpen Access

Data-driven Prediction of HSQ Polymer Structure and Silicon Nanocrystal Photoluminescence

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Key Points

Photoluminescence increased with better control over silicon nanocrystal synthesis, indicating potential advancements.
Key metrics include distinct photoluminescent maxima linked to silicon nanocrystal size control during synthesis.
Data-driven analysis optimized the prediction of polymer structure in relation to nanocrystal photoluminescence.
This approach highlights new possibilities for tailoring silicon nanocrystals for potential applications; further testing needed.

Implication

Data-driven prediction enhances photoluminescence in silicon nanocrystals, suggesting improved synthesis techniques.

Abstract

Synthesis of silicon nanocrystals through high-temperature pyrolysis of hydrogen silsesquioxane has emerged as a valuable approach for obtaining quantum-sized crystallites with controllable size and distinct photoluminescent maxima. Nevertheless, the use...

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Cite This Study

Jabrayilov et al. (2025) studied this question.

synapsesocial.com/papers/68a365740a429f797332bbaf https://doi.org/10.1039/d5dt01479d

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Data-driven Prediction of HSQ Polymer Structure and Silicon Nanocrystal Photoluminescence

Key Points

Implication

Abstract

Discussion

Cite This Study

Data-driven Prediction of HSQ Polymer Structure and Silicon Nanocrystal Photoluminescence

Key Points

Implication

Abstract

Discussion

Cite This Study

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