APA Style
Sahu, S. , Sahu, V. K. , & Soni, A. K. (2021). Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study.
Current Research in Public Health, 1(1), 1-10.
https://doi.org/10.31586/ojc.2021.010101
ACS Style
Sahu, S. ; Sahu, V. K. ; Soni, A. K. Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study.
Current Research in Public Health 2021 1(1), 1-10.
https://doi.org/10.31586/ojc.2021.010101
Chicago/Turabian Style
Sahu, Sangeeta, Vishnu Kumar Sahu, and Anil Kumar Soni. 2021. "Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study".
Current Research in Public Health 1, no. 1: 1-10.
https://doi.org/10.31586/ojc.2021.010101
AMA Style
Sahu S, Sahu VK, Soni AK. Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study.
Current Research in Public Health. 2021; 1(1):1-10.
https://doi.org/10.31586/ojc.2021.010101
@Article{crph2,
AUTHOR = {Sahu, Sangeeta and Sahu, Vishnu Kumar and Soni, Anil Kumar},
TITLE = {Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2021},
NUMBER = {1},
PAGES = {1-10},
URL = {/10.31586/ojc-1-1-110.31586/ojc/1/1/1},
ISSN = {2831-5162},
DOI = {10.31586/ojc.2021.010101},
ABSTRACT = {Polychlorinated biphenyls (PCBs) are important class of persist organic pollutants that were used as a component of paints especially in printings, as plastificator of plastics and insulating materials in transformers and capacitors, heat transfer fluids, additives in hydraulic fluids in vacuum and turbine pumps. There is always a need to establish reliable procedures for predicting the bioconcentration potential of chemicals from the knowledge of their molecular structure, or from readily measurable properties of the substance. Hence, correlation and prediction of biococentration factors (BCFs) based on λmax and vibration frequencies of various bonds viz υ(C-H) and υ(C=C) of biphenyl and its fifty-seven derivatives have been made. For the study, the molecular modeling and geometry optimization of the PCBs have been performed on workspace program of CAChe Pro 5.04 software of Fujitsu using DFT method. UV-visible spectra for each compound were created by electron transition between molecular orbitals as electromagnetic radiation in the visible and ultraviolet (UV-visible) region is absorbed by the molecule. The energies of excited electronic states were computed quantum mechanically. IR spectra of transitions for each compound were created by coordinated motions of the atoms as electromagnetic radiation in the infrared region is absorbed by the molecule. The force necessary to distort the molecule was computed quantum mechanically from its equilibrium geometry and thus frequency of vibrational transitions was predicted. Project Leader Program associated with CAChe has been used for multiple linear regression (MLR) analysis using above spectroscopic data as independent variables and BCFs of PCBs as dependent variables. The reliability of correlation and predicting ability of the MLR equations (models) are judged by R2, R2adj, se, q2L10O and F values. This study reflected clearly that UV and IR spectroscopic data can be used to predict BCFs of a large number of related compounds within limited time without any difficulty.},
}
TY - JOUR
AU - Sahu, Sangeeta
AU - Sahu, Vishnu Kumar
AU - Soni, Anil Kumar
TI - Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study
T2 - Current Research in Public Health
PY - 2021
VL - 1
IS - 1
SN - 2831-5162
SP - 1
EP - 10
UR - /10.31586/ojc-1-1-110.31586/ojc/1/1/1
AB - Polychlorinated biphenyls (PCBs) are important class of persist organic pollutants that were used as a component of paints especially in printings, as plastificator of plastics and insulating materials in transformers and capacitors, heat transfer fluids, additives in hydraulic fluids in vacuum and turbine pumps. There is always a need to establish reliable procedures for predicting the bioconcentration potential of chemicals from the knowledge of their molecular structure, or from readily measurable properties of the substance. Hence, correlation and prediction of biococentration factors (BCFs) based on λmax and vibration frequencies of various bonds viz υ(C-H) and υ(C=C) of biphenyl and its fifty-seven derivatives have been made. For the study, the molecular modeling and geometry optimization of the PCBs have been performed on workspace program of CAChe Pro 5.04 software of Fujitsu using DFT method. UV-visible spectra for each compound were created by electron transition between molecular orbitals as electromagnetic radiation in the visible and ultraviolet (UV-visible) region is absorbed by the molecule. The energies of excited electronic states were computed quantum mechanically. IR spectra of transitions for each compound were created by coordinated motions of the atoms as electromagnetic radiation in the infrared region is absorbed by the molecule. The force necessary to distort the molecule was computed quantum mechanically from its equilibrium geometry and thus frequency of vibrational transitions was predicted. Project Leader Program associated with CAChe has been used for multiple linear regression (MLR) analysis using above spectroscopic data as independent variables and BCFs of PCBs as dependent variables. The reliability of correlation and predicting ability of the MLR equations (models) are judged by R2, R2adj, se, q2L10O and F values. This study reflected clearly that UV and IR spectroscopic data can be used to predict BCFs of a large number of related compounds within limited time without any difficulty.
DO - Bioconcentration Factor of Polychlorinated Biphenyls and Its Correlation with UV- and IR-Spectroscopic data: A DFT based Study
TI - 10.31586/ojc.2021.010101
ER -