Liu Lili, Legg Benjamin A, Smith William, Anovitz Lawrence M, Zhang Xin, Harper Reed, Pearce Carolyn I, Rosso Kevin M, Stack Andrew G, Bleuel Markus, Mildner David F R, Schenter Gregory K, Clark Aurora E, De Yoreo James J, Chun Jaehun, Nakouzi Elias
Pacific Northwest National Laboratory, Richland, Washington 99354, United States.
Department of Chemistry, Washington State University, Pullman, Washington 99164, United States.
ACS Nano. 2023 Aug 22;17(16):15556-15567. doi: 10.1021/acsnano.3c02145. Epub 2023 Aug 9.
Predicting nanoparticle aggregation and attachment phenomena requires a rigorous understanding of the interplay among crystal structure, particle morphology, surface chemistry, solution conditions, and interparticle forces, yet no comprehensive picture exists. We used an integrated suite of experimental, theoretical, and simulation methods to resolve the effect of solution pH on the aggregation of boehmite nanoplatelets, a case study with important implications for the environmental management of legacy nuclear waste. Real-time observations showed that the particles attach preferentially along the (010) planes at pH 8.5 and the (101) planes at pH 11. To rationalize these results, we established the connection between key physicochemical phenomena across the relevant length scales. Starting from simulations of surface hydroxyl reactivity, we developed an model of the corresponding electrostatic potentials, with subsequent calculations of the resulting driving forces allowing successful prediction of the attachment modes. Finally, we scaled these phenomena to understand the collective structure at the . Our results indicate that facet-specific differences in surface chemistry produce heterogeneous surface charge distributions that are coupled to particle anisotropy and shape-dependent hydrodynamic forces, to play a key role in controlling aggregation behavior.
预测纳米颗粒的聚集和附着现象需要深入理解晶体结构、颗粒形态、表面化学、溶液条件和颗粒间作用力之间的相互作用,但目前尚无全面的认识。我们使用了一套综合的实验、理论和模拟方法,来解析溶液pH值对勃姆石纳米片聚集的影响,这是一个对遗留核废料环境管理具有重要意义的案例研究。实时观察表明,颗粒在pH值为8.5时优先沿(010)面附着,在pH值为11时沿(101)面附着。为了合理解释这些结果,我们建立了相关长度尺度上关键物理化学现象之间的联系。从表面羟基反应性的模拟开始,我们开发了相应静电势的模型,随后计算由此产生的驱动力,从而成功预测了附着模式。最后,我们对这些现象进行缩放,以了解宏观尺度上的聚集结构。我们的结果表明,表面化学的晶面特异性差异会产生异质表面电荷分布,这些分布与颗粒各向异性和形状相关的流体动力学力相互耦合,在控制聚集行为中起关键作用。