scholarly journals Tuning the molecular weight distribution from atom transfer radical polymerization using deep reinforcement learning

2018 ◽  
Vol 3 (3) ◽  
pp. 496-508 ◽  
Author(s):  
Haichen Li ◽  
Christopher R. Collins ◽  
Thomas G. Ribelli ◽  
Krzysztof Matyjaszewski ◽  
Geoffrey J. Gordon ◽  
...  

Combination of deep reinforcement learning and atom transfer radical polymerization gives precise in silico control on polymer molecular weight distributions.

2013 ◽  
Vol 295-298 ◽  
pp. 3-7
Author(s):  
Guo Bin Yi ◽  
Ying Wu ◽  
Ping Ke Ai

The reverse atom transfer radical polymerization (RATRP) of N-vinylpyrrolidone (NVP) using azobisisobutyronitrile (AIBN)/FeCl3/triphenylphosphine(PPh3) as the initiating system, was successfully carried out in bulk at 80°C. Plots of In ([M]0/[M]) vs time and molecular weight evolution vs monomer conversion presented a linear dependence and the polymerization was proved to accord with the first-order kinetics. After 10 hours’ reaction, the monomer conversion was up to 84%. Gel permeation chromatography (GPC) was used in testing the molecular weight of polymer and molecular weight distribution, the results showed that polymer molecular weight distribution was as low as 1.018 (Mn=3288 g/mol). Moreover, the resultant polymer was characterized by 1H-NMR, 13C-NMR spectroscopy and Pyrolysis GC-MS, and the results showed that the polymerization mechanism is consistent with RATRP.


2021 ◽  
Author(s):  
Rongguan Yin ◽  
Zongyu Wang ◽  
Michael R. Bockstaller ◽  
Krzysztof Matyjaszewski

Molecular weight distribution imposes considerable influence on the properties of polymers, making it an important parameter, impacting morphology and structural behavior of polymeric materials.


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