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      Spreading of Oil Droplets Containing Surfactants and Pesticides on Water Surface Based on the Marangoni Effect

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      Molecules
      MDPI
      Marangoni effect, spreading, pesticide transport, surfactants

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          Abstract

          Oil droplets containing surfactants and pesticides are expected to spread on a water surface, under the Marangoni effect, depending on the surfactant. Pesticides are transported into water through this phenomenon. A high-speed video camera was used to measure the movement of Marangoni ridges. Gas chromatography with an electron capture detector was used to analyze the concentration of the pesticide in water at different times. Oil droplets containing the surfactant and pesticide spread quickly on the water surface by Marangoni flow, forming an oil film and promoting emulsification of the oil–water interface, which enabled even transport of the pesticide into water, where it was then absorbed by weeds. Surfactants can decrease the surface tension of the water subphase after deposition, thereby enhancing the Marangoni effect in pesticide-containing oil droplets. The time and labor required for applying pesticides in rice fields can be greatly reduced by using the Marangoni effect to transport pesticides to the target.

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            Dynamics and stability of thin liquid films

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              Computation of octanol-water partition coefficients by guiding an additive model with knowledge.

              We have developed a new method, i.e., XLOGP3, for logP computation. XLOGP3 predicts the logP value of a query compound by using the known logP value of a reference compound as a starting point. The difference in the logP values of the query compound and the reference compound is then estimated by an additive model. The additive model implemented in XLOGP3 uses a total of 87 atom/group types and two correction factors as descriptors. It is calibrated on a training set of 8199 organic compounds with reliable logP data through a multivariate linear regression analysis. For a given query compound, the compound showing the highest structural similarity in the training set will be selected as the reference compound. Structural similarity is quantified based on topological torsion descriptors. XLOGP3 has been tested along with its predecessor, i.e., XLOGP2, as well as several popular logP methods on two independent test sets: one contains 406 small-molecule drugs approved by the FDA and the other contains 219 oligopeptides. On both test sets, XLOGP3 produces more accurate predictions than most of the other methods with average unsigned errors of 0.24-0.51 units. Compared to conventional additive methods, XLOGP3 does not rely on an extensive classification of fragments and correction factors in order to improve accuracy. It is also able to utilize the ever-increasing experimentally measured logP data more effectively.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Molecules
                Molecules
                molecules
                Molecules
                MDPI
                1420-3049
                05 March 2021
                March 2021
                : 26
                : 5
                : 1408
                Affiliations
                Innovation Center of Pesticide Research, Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China; liujiangyu@ 123456cau.edu.cn (J.L.); guoxinyu@ 123456cau.edu.cn (X.G.)
                Author notes
                [* ]Correspondence: cauxy@ 123456cau.edu.cn (Y.X.); wuxuemin@ 123456cau.edu.cn (X.W.)
                Author information
                https://orcid.org/0000-0002-1478-6177
                https://orcid.org/0000-0002-5981-1292
                Article
                molecules-26-01408
                10.3390/molecules26051408
                7961330
                4ff06264-40ce-4b37-b999-f31c9f1b8826
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 February 2021
                : 03 March 2021
                Categories
                Article

                marangoni effect,spreading,pesticide transport,surfactants

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