Quantum chemical computation and machine learning in NMR

2020 ◽  
Vol 58 (6) ◽  
pp. 477-477
Author(s):  
Ariel M. Sarotti
2021 ◽  
Author(s):  
Masato Sumita ◽  
Kei Terayama ◽  
Naoya Suzuki ◽  
Shinsuke Ishihara ◽  
Ryo Tamura ◽  
...  

Correlations between molecular properties and structures, such as those between the absorption wavelength and conjugate length, are beneficial for designing materials and controlling their properties. However, determining the molecular structures that correlate with the target molecular properties (such as molecular fluorescence) is not an easy task. In this study, we have used a de novo molecule generator (DNMG) coupled with quantum-chemical computation (QC) to develop new fluorescent molecules, which are garnering significant attention in various disciplines. With massive parallel computation (1024 cores, 5 days), DNMG has produced 3,643 candidate molecules within the density functional theory (DFT; one of QC) framework. Among the generated molecules, we have selected an unreported molecule and synthesized it for photoluminescence spectrum measurement. Our experimental verification demonstrated that DNMG can successfully create a new molecule which emits fluorescence detectable by the naked eye, as predicted by the DFT.


2019 ◽  
Vol 123 (33) ◽  
pp. 20251-20256 ◽  
Author(s):  
Junya Ohyama ◽  
Jumpei Shibano ◽  
Atsushi Satsuma ◽  
Ryoichi Fukuda ◽  
Yuta Yamamoto ◽  
...  

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