DMREF: Collaborative Research: Simulation-Based Design of Functional Sub-nanometer Porous Membranes
DMREF: Collaborative Research: Simulation-Based Design of Functional Sub-nanometer Porous Membranes
批准号:
1235439
负责人:
Ting Xu
金额:
$22.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2016-08-31
中文摘要
含有高密度纳米管阵列的聚合物薄膜是一种非常理想的环境友好型和高效的选择性运输系统。然而,成功设计和合成可在溶液中加工的聚合物膜,具有精确的亚纳米直径孔,垂直通道排列,以及类似于生物跨膜蛋白的可调孔内部化学性质,仍然具有挑战性。本项目采用理论/实验合作的方式对功能化环肽纳米管(CPNs)进行建模、设计和合成,以了解其在溶液中组装和与嵌段共聚物共组装的机制。本研究项目的目标是产生具有功能内部的机械坚固的自组装肽纳米管,可用于选择性多孔膜。为了实现这一总体目标,我们将(i)制造和表征具有极性(胺)基团功能化的多孔环状肽纳米管(cpn), (ii)使用交联嵌段共聚物基质生产具有极性和非极性基团的CPs垂直分布控制的层状膜,以及(iii)研究具有可调孔功能的膜的选择性机制,以实现新的运输能力。经过验证的大规模模拟工作将与实验相结合,以快速评估材料设计参数并预测材料性能,从而规避与纯组合方法相关的挑战。该研究项目旨在通过模拟来绘制有机纳米管的新生材料空间,从而开辟新的领域。有关肽/聚合物杂化纳米结构的基本物理的新知识将为生成新型功能亚纳米孔膜提供基础,为研究生物学中观察到的关键运输现象的分子机制提供新的平台。西北大学(Northwestern University)和加州大学伯克利分校(University of California, Berkeley)分别开展的K-12外展和本科研究项目,将利用这两所大学的暑期机会,招募代表性不足的少数族裔学生和女性加入研究团队。一个有机纳米管材料的图像库将被创建,并将作为一个开放访问的数据库,为公众服务,并为其他研究人员确定我们的功能纳米结构和方法的更广泛的应用。将创建虚拟和实验室实验模块,以促进各级材料物理和化学的有效学习,并将贡献给NanoHub和即将到来的网络基础设施。通过与学术界、工业界和国家实验室的互动,为研究生和博士后提供职业发展和工作与生活平衡方面的指导和指导。
英文摘要
1234305/1235439 PI: Keten/Xu Polymer thin films containing high-density arrays of nanotubes as through channels are very desirable as environmentally friendly and efficient selective transport systems. However, successful design and synthesis of polymer membranes that can be processed in solution and have precise subnanometer diameter pores, vertical channel alignment, and tunable pore interior chemistry similar to biological transmembrane proteins has remained challenging to produce. This project employs a collaborative theoretical / experimental effort to model, design and synthesize functionalized cyclic peptide nanotubes (CPNs) to understand mechanisms governing their assembly in solution and co-assembly with block copolymers. The objective of this research project is to generate mechanically robust self-assembling peptide nanotubes with functional interiors that could be used in selective porous membranes. To achieve this overarching objective, we will (i) fabricate and characterize porous cyclic peptide nanotubes (CPNs) functionalized with a polar (amine) group, (ii) produce layered membranes with control over the vertical distribution of CPs with polar and non-polar groups using crosslinkable block copolymer matrix, and (iii) investigate selectivity mechanisms in membranes with tunable pore functionalities toward novel transport capabilities. Validated large-scale simulation efforts will be integrated with experiments to rapidly evaluate material design parameters and predict material properties, circumventing challenges associated with purely combinatorial approaches. This research project aims to break new ground by mapping out the nascent material space of organic nanotubes through simulations. Fresh knowledge pertaining to the underlying physics of peptide/polymer hybrid nanostructures will be foundational for generating novel functional subnanoporous membranes toward new platforms to study molecular mechanisms underpinning key transport phenomena observed in biology. K-12 outreach and undergraduate research programs at Northwestern University and the University of California, Berkeley, respectively, will be leveraged to recruit underrepresented minority students and women into the research team through summer opportunities at both institutions. An image library for organic nanotube materials will be created and will serve as an open-access database for public outreach, and for other researchers to identify broader applications of our functional nanostructures and methods. Modules for virtual and laboratory experiments will be created to promote effective learning in materials physics and chemistry at all levels, and will be contributed to NanoHub and forthcoming cyber infrastructures. Guidance and mentorship on career development as well as work-life balance will be provided for graduate students and postdoctoral fellows through interactions with academia, industry and national labs.
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