Literature DB >> 22288868

Prediction of aqueous solubility of organic chemicals based on molecular structure.

N N Nirmalakhandan, R E Speece.   

Abstract

Year:  1988        PMID： 22288868     DOI： 10.1021/es00168a014

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN： 0013-936X            Impact factor:   9.028


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  6 in total

1.  Simultaneous prediction of aqueous solubility and octanol/water partition coefficient based on descriptors derived from molecular structure.

Authors:  D J Livingstone; M G Ford; J J Huuskonen; D W Salt
Journal:  J Comput Aided Mol Des       Date:  2001-08       Impact factor: 3.686

2.  Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review.

Authors:  Laure Mamy; Dominique Patureau; Enrique Barriuso; Carole Bedos; Fabienne Bessac; Xavier Louchart; Fabrice Martin-Laurent; Cecile Miege; Pierre Benoit
Journal:  Crit Rev Environ Sci Technol       Date:  2015-06-18       Impact factor: 12.561

3.  Accurate Physical Property Predictions via Deep Learning.

Authors:  Yuanyuan Hou; Shiyu Wang; Bing Bai; H C Stephen Chan; Shuguang Yuan
Journal:  Molecules       Date:  2022-03-03       Impact factor: 4.411

4.  Evaluation of Deep Learning Architectures for Aqueous Solubility Prediction.

Authors:  Gihan Panapitiya; Michael Girard; Aaron Hollas; Jonathan Sepulveda; Vijayakumar Murugesan; Wei Wang; Emily Saldanha
Journal:  ACS Omega       Date:  2022-04-25

5.  Determination and estimation of partitioning properties for substituted phosphates and thiophosphates.

Authors:  Yuying Dong; Guanghui Ding; Ying Cao; Zhuang Wang; Cheng Sun
Journal:  Environ Monit Assess       Date:  2008-05-23       Impact factor: 2.513

6.  Prediction of partition coefficients of organic compounds between SPME/PDMS and aqueous solution.

Authors:  Keh-Ping Chao; Yu-Ting Lu; Hsiu-Wen Yang
Journal:  Int J Mol Sci       Date:  2014-02-14       Impact factor: 5.923
  6 in total

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