Structure of surfactant and phospholipid monolayers at the air/water interface modeled from neutron reflectivity data
Structure of surfactant and phospholipid monolayers at the air/water interface modeled from neutron reflectivity data
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DOI：
10.1016/j.jcis.2018.07.022
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发表时间：
2018-12-01
影响因子：
9.9
通讯作者：
Lawrence, M. Jayne
中科院分区：
文献类型：
--
作者：
Campbell, Richard A.;Saaka, Yussif;Lawrence, M. Jayne
镜面反射中子反射仪是一种有效的软物质界面成分和结构分析技术。然而，令人惊讶的是，即使经过几十年，一个通用的建模方法，在空气/水界面的表面活性剂和磷脂单分子层的数据处理尚未建立。为了解决这个缺点，首先提出了一个系统的评价不同的模型的适用性。其结果是一个最佳的模型，这显然是非常需要在该领域的全面验证，我们建议作为未来的数据处理的起点。在公开讨论其局限性的同时，对未能考虑到各个关键方面的后果进行了严格审查，并对系统性错误进行了量化。在此物理框架的基础上，我们继续展示第一次，中子反射法可用于直接在空气/水界面上原位量化磷脂单分子膜相对于其相的酰基链压缩的程度。这种新的量化所实现的精度为10%。这些进展共同大大提高了未来研究数据的利用潜力，这些数据来自广泛的系统，包括涉及合成聚合物、蛋白质、DNA、纳米颗粒和药物的系统。(C)2018爱思唯尔公司All rights reserved.
Specular neutron reflectometry is a powerful technique to resolve interfacial compositions and structures in soft matter. Surprisingly however, even after several decades, a universal modeling approach for the treatment of data of surfactant and phospholipid monolayers at the air/water interface has not yet been established. To address this shortcoming, first a systematic evaluation of the suitability of different models is presented. The result is a comprehensive validation of an optimum model, which is evidently much needed in the field, and which we recommend as a starting point for future data treatment. While its limitations are openly discussed, consequences of failing to take into account various key aspects are critically examined and the systematic errors quantified. On the basis of this physical framework, we go on to show for the first time that neutron reflectometry can be used to quantify directly in situ at the air/water interface the extent of acyl chain compaction of phospholipid monolayers with respect to their phase. The achieved precision of this novel quantification is 10%. These advances together enhance significantly the potential for exploitation in future studies data from a broad range of systems including those involving synthetic polymers, proteins, DNA, nanoparticles and drugs. (C) 2018 Elsevier Inc. All rights reserved.