CAS: Degradable Polyacrylates From Natural and Scalable Building Blocks

CAS：来自天然和可扩展构件的可降解聚丙烯酸酯

• 批准号: 2348679
• 负责人: Christopher Bates
• 金额: $ 42万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2348679&HistoricalAwards=false
• 关键词: CAS; Degradable; Polyacrylates; Natural; Scalable

NON-TECHNICAL SUMMARY:A wide variety of everyday products, ranging from diapers to glues and cosmetics, rely on a class of polymeric materials known as ‘acrylics’ to create the properties of interest. However, like many plastics, current acrylics are difficult to reuse, recycle, or degrade, causing environmental and societal problems in the long-term sustainability of these important materials. This project seeks to develop cheap and commercially available additives that can be incorporated into acrylic products in small amounts to dramatically improve their recyclability and degradability without impacting their properties, while at the same time providing broader fundamental scientific understanding. Emphasis is placed on a combination of experiments and computer simulations to provide fundamental insights into the most efficient design of these special additives. In addition, a collection of broader impact activities is planned to cultivate the next generation of scientists and engineers through the development of digital outreach activities for K-12 students and a series of interactive lectures to improve the scientific communication skills for students of all ages. In summary, improving the sustainability of acrylics and the pipeline of future leaders in society will serve the national interest by promoting progress in science with implications in economic development and national prosperity.TECHNICAL SUMMARY:The intellectual merit of this project seeks to maximize the degradability of polyacrylates through the use of natural and scalable building blocks that are commercially available and inexpensive. Specifically, two thrusts will optimize the copolymerization of 1,2-dithiolanes such as alpha-lipoic acid and ethyl lipoate with acrylate comonomers through the development of semi-batch polymerization techniques that counteract composition drift, which is characteristic of these free-radical copolymerizations. Hybrid simulation strategies that leverage the fast method-of-moments framework will be developed to enable in-silico machine learning routines for the inverse design of polymer sequence and related degradability as a function of reaction conditions. The connection between average molecular sequence, degradability, and material properties will be studied in the context of adhesive performance using a suite of characterization techniques to create a feedback loop between simulations and experiments. In addition, broader impacts activities are planned that will strengthen the pipeline of next-generation scientists and engineers. For K-12 students, the creation of a phone app will serve to complement outreach activities either in-person or fully remote and excite them about the world of polymers. For students of all ages, but with a particular emphasis on undergraduate and graduate, a series of interactive lectures will convey tried-and-true strategies for strengthening scientific communication skills, both written and oral..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.

非技术概要：各种各样的日常用品，从纸尿裤到胶水和化妆品，都依赖于一类被称为“丙烯酸”的聚合物材料来创造感兴趣的性能。然而，像许多塑料一样，目前的丙烯酸很难再利用、回收或降解，在这些重要材料的长期可持续性方面造成了环境和社会问题。该项目旨在开发廉价且商业化的添加剂，这些添加剂可以少量添加到丙烯酸产品中，以显着提高其可回收性和可降解性，同时不影响其性能，同时提供更广泛的基础科学理解。重点放在实验和计算机模拟的结合，以提供最有效的设计这些特殊添加剂的基本见解。此外，还计划开展一系列更广泛的影响活动，通过为K-12学生开展数字外展活动和一系列互动讲座来培养下一代科学家和工程师，以提高各年龄段学生的科学交流技能。总之，提高丙烯酸的可持续性和未来社会领导者的管道将通过促进经济发展和国家繁荣的科学进步来服务于国家利益。技术概述：这个项目的知识价值是通过使用天然的、可扩展的、市售的、廉价的构建块来最大限度地提高聚丙烯酸酯的可降解性。具体来说，两个推力将通过开发半间歇聚合技术来优化1,2-二硫代烷（如α -硫辛酸和硫酸乙酯）与丙烯酸酯共聚单体的共聚，以抵消这些自由基共聚的特征组成漂移。利用快速矩量法框架的混合模拟策略将被开发出来，以使计算机机器学习程序能够用于聚合物序列的逆设计和相关的降解性作为反应条件的函数。平均分子序列、可降解性和材料性能之间的联系将在粘合剂性能的背景下进行研究，使用一套表征技术来创建模拟和实验之间的反馈回路。此外，还计划开展更广泛的影响活动，以加强下一代科学家和工程师的培养。对于K-12学生来说，创建一个手机应用程序将有助于补充面对面或完全远程的外展活动，并激发他们对聚合物世界的兴趣。对于所有年龄段的学生，特别是本科生和研究生，一系列的互动讲座将传达有效的策略，以加强书面和口头的科学交流技能。该奖项反映了美国国家科学基金会的法定使命，并通过基金会的智力价值和更广泛的影响评估标准进行了评估，认为值得支持。