Exploring temperature-dependent photoluminescence dynamics of colloidal CdSe nanoplatelets using machine learning approach

Exploring temperature-dependent photoluminescence dynamics of colloidal CdSe nanoplatelets using machine learning approach

Abstract The study explore machine learning (ML) techniques to predict temperature-dependent photoluminescence (PL) spectra in colloidal CdSe nanoplatelets (NPLs), leveraging polynomial regression models trained on experimental data from 85 to 270 K spanning temperatures to forecast PL spectra backw...

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Bibliographic Details
Main Authors: Ivan P. Malashin, Daniil Daibagya, Vadim Tynchenko, Vladimir Nelyub, Aleksei Borodulin, Andrei Gantimurov, Alexandr Selyukov, Sergey Ambrozevich, Roman Vasiliev
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
Machine learning
CdSe
Nanoplatelets
Luminescence
Temporal dynamics
Online Access:https://doi.org/10.1038/s41598-024-81200-9
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https://doi.org/10.1038/s41598-024-81200-9

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