المؤلفون: Changyu Tian, Yullim Lee, Youngho Song, Mohamed R. Elmasry, Minyeong Yoon, Dong-Hwan Kim, Soo-Yeon Cho

مصطلحات موضوعية: Biophysics, Biochemistry, Biotechnology, Space Science, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, world applications due, training data set, spatiotemporal monitoring capabilities, signal extraction near, practical sensing performance, distinct sensing performances, conventional statistical methods, carbon quantum dots, 41 %, respectively, 100 pm cu, 3 +, 2 +, various environmental factors, fluorescence features (<, 6 , 4 , seven different types, original detection limit, machine learning algorithms, various types, different types

Relation: https://figshare.com/articles/journal_contribution/Machine-Learning-Enhanced_Fluorescent_Nanosensor_Based_on_Carbon_Quantum_Dots_for_Heavy_Metal_Detection/25303673

الاتاحة: https://doi.org/10.1021/acsanm.4c00359.s001
https://figshare.com/articles/journal_contribution/Machine-Learning-Enhanced_Fluorescent_Nanosensor_Based_on_Carbon_Quantum_Dots_for_Heavy_Metal_Detection/25303673

المؤلفون: Changyu Tian, Yullim Lee, Youngho Song, Mohamed R. Elmasry, Minyeong Yoon, Dong-Hwan Kim, Soo-Yeon Cho

مصطلحات موضوعية: Biophysics, Biochemistry, Biotechnology, Space Science, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, world applications due, training data set, spatiotemporal monitoring capabilities, signal extraction near, practical sensing performance, distinct sensing performances, conventional statistical methods, carbon quantum dots, 41 %, respectively, 100 pm cu, 3 +, 2 +, various environmental factors, fluorescence features (<, 6 , 4 , seven different types, original detection limit, machine learning algorithms, various types, different types

Relation: https://figshare.com/articles/journal_contribution/Machine-Learning-Enhanced_Fluorescent_Nanosensor_Based_on_Carbon_Quantum_Dots_for_Heavy_Metal_Detection/25303673

الاتاحة: https://doi.org/10.1021/acsanm.4c00359.s001