Engineering Research Equipment Grant: A Surface Force Instrument for Adhesion Membrane Transport and Polymer Studies

该项目提供的设备允许最近获得美国国家科学基金会“微型中心”资助的三名研究人员研究由受体-配体相互作用介导的细胞分离。表面力仪器（SFI）提供了关于这种键的强度、有效距离的直接信息，以及在流体膜表面（由沉积在云母表面的脂质双层模拟）的情况下，键形成分子扩散到彼此靠近的速度有多快。分子通过膜的运输也引起了另外两位研究者的极大兴趣。SFI提供了分子在孔隙（由两个云母表面的细缝“孔”模拟）和散装液体之间分配的直接信息。预测表明，随着孔隙半径的变化，分配系数的振荡变化可以进行测试。许多基本材料的性质直接取决于分子间的作用力。这些性质反过来又直接用于化学工程计算，以预测和关联聚合物的溶解度、胶体稳定性、粘附性、膜渗透、吸附和其他现象。在过去，有必要使用导出的量来衡量这些相互作用。SFI允许直接测量这些力以及它们如何随位置变化。因此，它有可能在化学工程的许多领域做出重要贡献：在产生准确的“第一性原理”数据，在测试基于分子相互作用的理论预测，并有助于产生改进的相关功能。

The equipment provided by this project allows three investigators who recently have been awarded an NSF "minicenter" grant to study cell separations mediated by receptor-ligand interactions. The surface force instrument (SFI) provides direct information on the strength of such bonds, the distances over which they are effective, and in the case of fluid membrane surfaces (modeled by lipid bilayers deposited on the mica surfaces) how rapidly the bond-forming molecules can diffuse into close proximity to one another. The transport of molecules through membranes is also of great interest to two other researchers. The SFI provides direct information on the partitioning of molecules between pore (modeled by the thin slit "pore" of the two mica surfaces) and bulk liquid. Predictions suggesting an oscillatory variation in the partition coefficient as pore radius changes can be tested. Many fundamental materials properties are directly dependent on intermolecular forces. These properties, in turn, are used directly in chemical engineering calculations to predict and correlate polymer solubility, colloid stability, adhesion, membrane permeation, adsorption, and other phenomena. In the past, it has been necessary to use derived quantities as a measure of these interactions. The SFI permits direct measurement of these forces and how they vary with position. It therefore has the potential for making important contributions to many areas of chemical engineering: in producing accurate "first-principles" data, in testing theoretical predictions based on molecular interactions, and i helping to produce improved correlating functions.