Sánchez-Velázquez Gabriel, Khong Duc Thinh, Park Minkyung, Jin Xiaojia, Yuan Zhe, Gong Xun, Ang Mervin Chun-Yi, Strano Michael S
Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Disruptive & Sustainable Technologies for Agricultural Precision IRG, Singapore-MIT Alliance for Research and Technology, 1 CREATE Way, #03-06/07/08 Research Wing, Singapore 138602, Singapore.
Langmuir. 2025 Jul 15;41(27):17602-17614. doi: 10.1021/acs.langmuir.5c01222. Epub 2025 Jul 1.
The nanoparticle corona─a molecular layer adsorbed on nanoparticle surfaces─is critical for controlling molecular interactions and enabling applications in catalysis, nanoparticle separations, and sensing technologies. However, to date, characterizing the adsorbed surface area occupied by the corona phase has been difficult and not accessible with conventional particle sizing methods. Herein, we advance the technique of molecular probe adsorption (MPA) to measure this surface area by applying it to a large number of data sets. MPA employs a fluorescent probe that is quenched on adsorption to the nanoparticle surface to quantify the solvent-exposed surface area. We use MPA to evaluate 20 new carbon nanotube (CNT) corona phases and further analyze five previously studied constructs that have been used as nanosensors. We find that polymer stiffness, measured by its persistence length, correlates with corona phase CNT surface coverage, providing a new design criterion. We also establish a structure-property relationship linking MPA-derived surface area to probe adsorption parameters, noting that single-stranded DNA and high-molecular-weight polymers exhibit differing probe-corona interactions, with binding affinities varying by a factor of nearly 2.7. MPA-derived surface areas are shown to complement molecular-dynamics/thermodynamic calculations to predict binding affinities for 42 phytohormones entirely in silico, providing a means to screen corona phases virtually. In this way, MPA is shown to be a predictive design tool for nanoparticle and nanosensor applications.
纳米颗粒晕层——吸附在纳米颗粒表面的分子层——对于控制分子相互作用以及实现催化、纳米颗粒分离和传感技术等应用至关重要。然而,迄今为止,表征晕层相占据的吸附表面积一直很困难,传统的颗粒尺寸测量方法无法实现。在此,我们改进了分子探针吸附(MPA)技术,通过将其应用于大量数据集来测量该表面积。MPA使用一种荧光探针,该探针在吸附到纳米颗粒表面时会淬灭,以量化溶剂暴露的表面积。我们使用MPA评估20种新的碳纳米管(CNT)晕层相,并进一步分析5种先前研究过的用作纳米传感器的构建体。我们发现,通过其持久长度测量的聚合物刚度与晕层相CNT表面覆盖率相关,这提供了一种新的设计标准。我们还建立了一种结构-性质关系,将MPA衍生的表面积与探针吸附参数联系起来,注意到单链DNA和高分子量聚合物表现出不同的探针-晕层相互作用,结合亲和力相差近2.7倍。结果表明,MPA衍生的表面积可补充分子动力学/热力学计算,以完全在计算机上预测42种植物激素的结合亲和力,提供一种虚拟筛选晕层相的方法。通过这种方式,MPA被证明是一种用于纳米颗粒和纳米传感器应用的预测性设计工具。