ST3: Research Collaborative Network on Information-driven Biomaterials

ST3：信息驱动生物材料研究合作网络

• 批准号: 1941318
• 负责人: Daniel Hammer
• 金额: $ 10万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1941318&HistoricalAwards=false
• 关键词: ST3; Research; Collaborative; Network; Information

New concepts in the design of biomaterials have led to the moment in which biomaterials may be designed to make decisions. These decisions - including motility, replication, collective behavior, healing, and secretion - can be driven by molecular computational and decision-making networks embedded in materials. Increasing sophistication of both soft matter design and synthetic networks allow for the possibility of embedded synthetic networks in artificial cells and tissues that allow for intelligent information processing or self replication of materials. This award proposes a workshop to develop connections and ideas an international Research Collaborative Network (RCN) for the purposes of supporting collaborative work between U.S. and European scientists in the area of information-driven materials. The goal of this meeting will be to identify key areas of intersection between biomaterials synthesis and response and information encoding. The meeting follows upon a very successful Square Table that was held at NSF in the Fall of 2018 that identified many of the key scientific issues in this area. The focus of the meeting will be on fundamental issues in the design of materials and networks, informed by quantitative methods and computing, and to assess what can be achieved through state of the art materials design. Because the discipline is highly interdisciplinary, the meeting will bring together basic scientists from chemistry, physics, biology, engineering, and biomaterials science. Furthermore, this meeting will focus on how to activate an effective network of collaboration and identify areas of potential support at NSF for future programs on information-driven biomaterials.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

生物材料设计中的新概念导致了生物材料可能被设计来做出决定的时刻。这些决定--包括运动、复制、集体行为、愈合和分泌--可以由嵌入在材料中的分子计算和决策网络驱动。软物质设计和合成网络的日益复杂使得在人造细胞和组织中嵌入合成网络成为可能，从而允许智能信息处理或材料的自我复制。该奖项提议举办一个研讨会，以发展国际研究合作网络(RCN)的联系和想法，目的是支持美国和欧洲科学家在信息驱动材料领域的合作工作。本次会议的目标将是确定生物材料合成和响应与信息编码之间的关键交叉领域。在这次会议之前，2018年秋季在国家科学基金会举行了一次非常成功的方桌会议，确定了这一领域的许多关键科学问题。会议的重点将是材料和网络设计中的基本问题，通过定量方法和计算获得信息，并评估通过最先进的材料设计可以实现的成果。由于该学科是高度跨学科的，这次会议将汇集来自化学、物理、生物、工程和生物材料科学的基础科学家。此外，本次会议将重点讨论如何激活有效的合作网络，并确定NSF未来信息驱动生物材料项目的潜在支持领域。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。