Assemblies disaggregation and diffusion dictated droplet impact and wetting behaviors on hydrophobic surface

Li, Zilu; Li, Zehuan; Gao, Yuxia; Zhang, Chenhui; Zhao, Kefei; Guo, Yongfei; Bao, Zhenping; Wu, Tianyue; Li, Xiangdong; Du, Fengpei

doi:10.1016/j.molliq.2021.116826

Cited by 16 publications

(14 citation statements)

References 35 publications

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“…album and I. chinensis, high-efficiency adjuvants are supposed to promote herbicide retention, such as didecyldimethylammonium bromide (DDAB) . In our system, the value of dispersion component is much higher than that of the polar component, indicating the weak polarity of these weed leaf surfaces (Figure J).…”

Section: Resultsmentioning

confidence: 90%

Improved Method to Characterize Leaf Surfaces, Guide Adjuvant Selection, and Improve Glyphosate Efficacy

Zhang

Wang

et al. 2023

J. Agric. Food Chem.

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Glyphosate, one of the most widely used herbicides, plays an important role in controlling weeds and ensuring crop production. While using glyphosate, adjuvants are commonly added to improve its deposition on weeds and control efficacy. However, changes in weed leaf surface characteristics may reduce glyphosate penetration and contribute to evolved glyphosate resistance. Therefore, it is significant to introduce an improved method for regularizing leaf surface characterization and guide adjuvant selection to improve glyphosate efficacy. In this work, surface characteristics of typical weed leaves have been systematically investigated by 3D surface analysis and scanning electron microscopy, finally quantified by apparent surface free energy (ASFE) due to its comprehensive and quantitative evaluation of leaf surfaces. Moreover, the relationship between the weed leaf surface characteristics and the retention of glyphosate on weeds was established, further related to the control efficacy against weeds. To maximize the utilization rate of glyphosate, the types and concentrations of adjuvants should be regulated according to the ASFE of weeds. Our findings not only regularize the surface properties of weed leaves but also reveal their influencing mechanism on the deposition and biological activity of glyphosate, which provide effective guidance for the use of glyphosate.

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Section: Resultsmentioning

confidence: 90%

Improved Method to Characterize Leaf Surfaces, Guide Adjuvant Selection, and Improve Glyphosate Efficacy

Zhang

Wang

et al. 2023

J. Agric. Food Chem.

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“…In the first stage, the absolute value of the slope of all lines is less than 1, which means that the adsorption capacity of molecules at the liquid–vapor interface is greater than that at the solid–liquid interface (Figure D). Among them, the steric hindrance of CAPB and APG reduces the compactness of the adsorption film, resulting in a smaller adsorption capacity . The droplet is unable to access the potential energy barrier to replace the air layer among the micro–nano structures of the hydrophobic surface and then in the Cassie-Baxter state, the CA decreases slowly.…”

Section: Resultsmentioning

confidence: 99%

“…Among them, the steric hindrance of CAPB and APG reduces the compactness of the adsorption film, resulting in a smaller adsorption capacity. 8 The droplet is unable to access the potential energy barrier to replace the air layer among the micro−nano structures of the hydrophobic surface and then in the Cassie-Baxter state, the CA decreases slowly. In the second stage, the adsorption capacity of surfactant molecules at the solid−liquid interface is greater than that at the liquid−vapor interface, making the solid surface hydrophilic and improving the wettability.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

“…Generally, by modulating liquid properties such as viscosity, surface tension, and aggregate morphology, − the interfacial behavior can be influenced, which regulates deposition on hydrophobic leaves . It is shown that adding silica particles and poly(ethylene oxide) (PEO) can increase the viscoelasticity of the droplet and reduce droplet splashing. , However, limited wetting capacity caused by increased bulk viscosity cannot obtain uniformly deposited droplets.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning to Predict the Interfacial Behavior of Pesticide Droplets on Hydrophobic Surfaces for Minimizing Environmental Risk

Song

Bao

et al. 2022

ACS Sustainable Chem. Eng.

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Achieving accurate and efficient target deposition of pesticide droplets is the principal factor in minimizing environmental risk. For hydrophobic surfaces, adding tank-mix adjuvants containing surfactants to modulate interfacial behavior is warranted, which lacks common laws to guide practical applications directly. Machine learning is developing rapidly and makes many data-based decisions in various industrial processes. Hence, according to machine learning-based analysis of fundamental physical quantities, proposing quantitative sustainability metrics to improve interface behavior is essential. Comparing the interfacial behavior of five adjuvants, the common denominator is that droplets in the Wenzel state with higher adhesion tension and lower contact angles can generate the pinning force that causes energy dissipation, reduces pesticide losses, and weakens environmental pollution. Simultaneously, the interfacial behavior of pesticide droplets including adjuvants on citrus leaves is verified, while the phytotoxicity experiment under high temperature and the laboratory bioassay are carried out. The results show that the eco-friendly alkyl polyglycoside (APG) as the glycosidic surfactant has nontarget biosafety and better mite control, which can be exploited as a commercial tank-mix adjuvant for promotion. This study provides a new insight into guiding adjuvants added to pesticides on account of quantitative sustainability metrics, which has important implications for food safety and agricultural green development.

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“…53 However, leaf tissues of rice, maize and cucumber have rough surfaces with dense textures and very good hydrophobicity. [54][55][56] The sprays of NPs on the leaf surface of the hydrophobic plants slip off easily, limiting their potential to enter the plant. 34 The NBCFs of dosed leaves were further studied and are illustrated in Fig.…”

Section: Effect Of Enzyme On Npsmentioning

confidence: 99%

Uptake and bioaccumulation of nanoparticles by five higher plants using single-particle-inductively coupled plasma-mass spectrometry

Wang

Yue

Zhao

et al. 2022

Environ. Sci.: Nano

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Assemblies disaggregation and diffusion dictated droplet impact and wetting behaviors on hydrophobic surface

Cited by 16 publications

References 35 publications

Improved Method to Characterize Leaf Surfaces, Guide Adjuvant Selection, and Improve Glyphosate Efficacy

Improved Method to Characterize Leaf Surfaces, Guide Adjuvant Selection, and Improve Glyphosate Efficacy

Machine Learning to Predict the Interfacial Behavior of Pesticide Droplets on Hydrophobic Surfaces for Minimizing Environmental Risk

Uptake and bioaccumulation of nanoparticles by five higher plants using single-particle-inductively coupled plasma-mass spectrometry

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