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可能设计生物材料来做出决策的那一刻。 这些决定 - 包括运动，复制，集体行为，康复和分泌 - 可以由嵌入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复杂性越来越复杂，可以在人造细胞和组织中嵌入嵌入的合成网络，从而可以进行智能信息处理或自我复制材料。 该奖项提出了一个研讨会，以建立联系和想法是国际研究合作网络（RCN），以支持信息驱动材料领域的美国和欧洲科学家之间的合作工作。 这次会议的目的是确定生物材料合成与响应和信息编码之间交集的关键领域。 会议是在2018年秋季在NSF举行的一张非常成功的方形桌子之后，确定了该领域的许多关键科学问题。会议的重点将放在材料和网络设计中的基本问题上，并通过定量方法和计算来告知，并评估通过最先进的材料设计可以实现的目标。由于该学科是高度跨学科的，因此会议将使化学，物理学，生物学，工程和生物材料科学的基础科学家聚集在一起。此外，这次会议将重点介绍如何激活有效的协作网络，并在NSF上确定有关信息驱动的生物材料的未来计划的潜在支持领域。该奖项反映了NSF的法定任务，并被认为是通过基金会的评估来评估的值得支持的。智力优点和更广泛的影响审查标准。