Removal of Cr (VI) from an aqueous solution using an activated carbon obtained from teakwood sawdust: Kinetics, equilibrium, and density functional theory calculations

2020 ◽  
Vol 8 (2) ◽  
pp. 103702 ◽  
Author(s):  
Anyi Ramirez ◽  
Raúl Ocampo ◽  
Stephanie Giraldo ◽  
Erika Padilla ◽  
Elizabeth Flórez ◽  
...  
2019 ◽  
Vol 233 (4) ◽  
pp. 527-550 ◽  
Author(s):  
M. Gokhan Habiboglu ◽  
Orkid Coskuner-Weber

Abstract Carbohydrate complexes are crucial in many various biological and medicinal processes. The impacts of N-acetyl on the glycosidic linkage flexibility of methyl β-D-glucopyranose, and of the glycoamino acid β-D-glucopyranose-asparagine are poorly understood at the electronic level. Furthermore, the effect of D- and L-isomers of asparagine in the complexes of N-acetyl-β-D-glucopyranose-(L)-asparagine and N-acetyl-β-D-glucopyranose-(D)-asparagine is unknown. In this study, we performed density functional theory calculations of methyl β-D-glucopyranose, methyl N-acetyl-β-D-glucopyranose, and of glycoamino acids β-D-glucopyranose-asparagine, N-acetyl-β-D-glucopyranose-(L)-asparagine and N-acetyl-β-D-glucopyranose-(D)-asparagine for studying their linkage flexibilities, total solvated energies, thermochemical properties and intra-molecular hydrogen bond formations in an aqueous solution environment using the COnductor-like Screening MOdel (COSMO) for water. We linked these density functional theory calculations to deep learning via estimating the total solvated energy of each linkage torsional angle value. Our results show that deep learning methods accurately estimate the total solvated energies of complex carbohydrate and glycopeptide species and provide linkage flexibility trends for methyl β-D-glucopyranose, methyl N-acetyl-β-D-glucopyranose, and of glycoamino acids β-D-glucopyranose-asparagine, N-acetyl-β-D-glucopyranose-(L)-asparagine and N-acetyl-β-D-glucopyranose-(D)-asparagine in agreement with density functional theory results. To the best of our knowledge, this study represents the first application of density functional theory along with deep learning for complex carbohydrate and glycopeptide species in an aqueous solution medium. In addition, this study shows that a few thousands of optimization frames from DFT calculations are enough for accurate estimations by deep learning tools.


Pteridines ◽  
2009 ◽  
Vol 20 (1) ◽  
pp. 124-128 ◽  
Author(s):  
Michael Soniat ◽  
Christopher B. Martin

Abstract Pterins exist as several tautomeric forms and behave as weak acids in aqueous solutions. Therefore, several acidbase equilibria may be present. For several pterin derivatives, the range of the experimental pKa lies in the range 6-8. The anionic form of the lactam structure is the only structure considered in the literature to represent the chemistry of pterins in alkaline solution. In the present study, density functional theory calculations were used to determine the relative energies of various anionic tautomers of pterin present in aqueous solution which may play a role in chemical and biological systems.


2006 ◽  
Vol 71 (11-12) ◽  
pp. 1525-1531 ◽  
Author(s):  
Wojciech Grochala

The enthalpy of four polymorphs of CaN has been scrutinized at 0 and 100 GPa using density functional theory calculations. It is shown that structures of diamagnetic calcium diazenide (Ca2N2) are preferred over the cubic ferromagnetic polymorph (CaN) postulated before, both at 0 and 100 GPa.


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