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ELECTROSPRAY IONIZATION OF POLYMERS: EVAPORATION, DROP FISSION, AND DEPOSITED PARTICLE MORPHOLOGY

机译:聚合物的电喷雾电离:蒸发,降裂和沉积颗粒形态

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The fundamental challenge of nanomanufacturing is to create, control, and assemble enormous quantities of nanoscale objects and distribute them over large surface areas. Electrospray ionization (ESI) has the potential to address this challenge due to its simplicity, applicability to a broad range of materials, and intrinsic scalability. ESI uses high voltages to electrically charge and disperse materials ranging in size from sub-nanometers to micrometers in diameter, which can then be guided and deposited on a substrate. However, the interactions between initial spray parameters and final deposited morphology are not well understood. In this study, we show that when electrospraying polymers, deposited particle size and morphology can be modified through the initial polymer concentration and nozzle-substrate distance. We report the results of electrospraying 0.1% and 0.5% concentrations of poly(acrylic acid) (PAA) onto substrates with 1, 3, and 5 cm nozzle-substrate distances. Scanning electron microscopy showed that deposited particles ranged from less than 10 nm to nearly 200 nm in diameter with tight, multi-modal size distributions. Particle shape and spread on the substrate were also examined. We use physics-based models to show that the size distributions are a function of the evaporation and drop fission during the spray along with the effect of solute concentration gradients within an evaporating drop. This work validates our previously developed models and will lead to future process guidelines.
机译:纳米建材的根本挑战是创造,控制和组装巨大的纳米级物体,并将它们分布在大型表面积上。电喷雾电离(ESI)由于其简单性,适用于广泛的材料以及内在的可扩展性,有可能解决这一挑战。 ESI使用高压电荷和分散材料的尺寸从亚纳米到直径的微米,然后可以被引导和沉积在基板上。然而,初始喷射参数与最终沉积形态之间的相互作用并不充分了解。在这项研究中,我们表明,当电喷雾聚合物,沉积的粒度和形态可以通过初始聚合物浓度和喷嘴 - 基板距离来改变。我们将电喷雾0.1%和0.5%浓度的聚(丙烯酸)(PAA)浓度的结果报告到具有1,3和5cm喷嘴基板距离的基材上。扫描电子显微镜显示,沉积的颗粒的直径小于10nm至近200nm,具有紧密,多模态尺寸分布。还检查了颗粒形状并在基材上涂抹。我们使用基于物理的模型来表明尺寸分布是喷雾过程中蒸发和下降裂变的函数,以及蒸发液滴内的溶质浓度梯度的效果。这项工作验证了我们以前开发的模型,并将导致未来的流程指南。

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