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QSPR modeling
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This modeling is performed on an experimental data set of complexes, where the metal ions of these complexes include transition ion metals and lanthanide ion metals. We use these models to develop a series of new thiosemicarbazone and their complexes; simultaneously, the complexes are worked out the stability constants from the novel models.
9p
dianmotminh02
03-05-2024
4
1
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In ebook "A primer on QSAR/QSPR modeling: Fundamental concepts" the authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and pharmacy.
129p
nhanphanguyet
28-01-2024
4
2
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The molecular descriptors, physicochemical and quantum descriptors of complexes were generated from molecular geometric structure and semi-empirical quantum calculation PM7 and PM7/sparkle.
13p
vimarillynhewson
02-01-2024
3
0
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The QSPR modeling is popularly used in many fields as in silico approach for predicting properties of chemical compounds based on the relationships between the structural characteristics and the properties.
11p
viargus
03-03-2023
2
2
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In this study, The QSPR models were built with knotp, SHBa, HOMO, xvpc4, N4, LUMO, ionization potential, dipole, molecular weight, Maxneg and Hf descriptors selected from the descriptor sets.
13p
viaudi
04-08-2022
4
1
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The structural descriptors of the complexes include the 2D, 3D molecular and physicochemical descriptors. The stability constants with experimental parameters are collected from published literature.
13p
viaudi
04-08-2022
7
1
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The suggested approach can expedite remediation technology design for emerging contaminants or newly developed chemicals for which the knowledge about their fate and behaviour in the environment is limited.
14p
thebadguys
15-01-2022
7
0
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In this study, the stability constants (logB11) of twenty-eight new complexes between several ion metals and thiosemicarbazone ligands were predicted on the basis of the quantitative structure property relationship (QSPR) modeling. The stability constants were calculated from the results of the QSPR models. The QSPR models were built by using the multivariate least regression (QSPRMLR) and artificial neural network (QSPRANN)
15p
viwilliamleiding
10-12-2021
13
1
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