DMREF/Collaborative Research: Accelerated Discovery of Sustainable Bioplastics: Automated, Tunable, Integrated Design, Processing and Modeling

尽管经过多年的回收努力，只有大约10%的聚合物废物最终进入回收设施，大多数仍然堆积在垃圾填埋场或海洋中，这强调了对可再生来源、可持续处理和生物降解性相结合的环保材料的需求。可热成型生物聚合物组件或生物塑料是可从生物细胞或组织（生物物质）中提取的环保材料，无需昂贵且浪费的提取和预处理。在设计这些生物塑料的能力中，最重要的限制是对控制生物物质向内聚生物塑料转化的基本机制的理解不足。这项设计材料以革新和工程我们的未来（DMREF）资助支持的研究将结合高通量数据捕获，多尺度建模和机器学习，以了解在加工过程中控制从生物体到生物塑料过渡的分子和化学机制。有了这样的理解，设计途径将被开发，以定制初始结构的加工和组成，以控制宏观性能，以及在使用期间和之后发生的降解。这项工作的广泛影响将是一种新型的完全可生物降解塑料，其性能与商品塑料相当，但可以可持续地制造。为了支持下一代可持续材料劳动力，该赠款还将支持研究生和本科生的指导，积极参与外展活动，并努力提高STEM的多样性和包容性。在开发环保材料的过程中，一个新兴的变革概念是使用生物物质，而不需要任何提取过程来制造生物塑料。在了解生物聚合物混合物如何转化为可热成型的生物塑料以及加工参数如何控制结构和性能方面，仍然存在重大挑战。为了提供关键的见解，该项目将使用高通量方法来测量加工、光谱和形态特征，并应用机器学习方法来识别控制从生物到塑料转化的关键描述符。分子动力学模拟和高保真实验将增加对生物塑料形成和生物降解反应的理解。详细的结构和性能测量将用于验证有限元分析工具，该工具将能够识别最佳结构，从而使用高通量方法实现与商用塑料相当的性能。螺旋藻是一种丰富的光合微生物，已被证明在加热和加压处理时可以产生生物塑料，将作为概念验证系统。该项目的根本贡献将是一种设计方法，该方法可以解释原料生物材料向生物塑料过渡的复杂性，体现了材料基因组计划对预测性材料设计和数据驱动方法的重视，以促进循环经济的可持续和创新材料。该项目由工程理事会（ENG）的土木、机械和制造创新司（CMMI）、数学和物理科学理事会（MPS）的材料研究司（DMR）以及计算机和信息科学与工程理事会（CISE）的信息和智能系统司（IIS）支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Despite years of recycling efforts, only about 10 percent of polymer waste ends up in recycling facilities, with the majority still accumulating in landfills or oceans, emphasizing the need for eco-friendly materials combining renewable sourcing, sustainable processing, and biodegradability. Thermoformable biopolymer assemblies or bioplastics are eco-friendly materials that could be sourced from biological cell or tissue (biomatter), without expensive and wasteful extraction and pre-processing. The most significant limitation in the ability to design these bioplastics is a poor understanding of the fundamental mechanisms controlling the transformation of biomatter to cohesive bioplastics. This Designing Materials to Revolutionize and Engineer our Future (DMREF) grant supports research that will combine high-throughput data capture, multiscale modeling, and machine learning to understand the molecular and chemical mechanisms controlling the transition from organism to bioplastic during processing. With that understanding, design pathways will be developed to tailor the processing and composition of the initial structure to control the macroscopic properties, and degradation that occurs during and after use. The broad impact of this work will be a new class of entirely biodegradable plastics with performance comparable to commodity plastics but manufactured sustainably. To support the next-generation sustainable materials workforce, the grant will also support mentoring of graduate and undergraduate students, active engagement in outreach activities, and efforts to enhance diversity and inclusivity in STEM.An emerging transformative concept in developing eco-friendly materials is to use biological matter without any extraction process to create bioplastics. Significant challenges remain in understanding how mixtures of biopolymers transform into thermoformable bioplastics and how the processing parameters control structure and properties. To provide key insights, this project will use high throughput methods to measure processing, spectroscopic, and morphology features and apply machine learning methods to identify the key descriptors controlling the transformation from organism to plastic. Molecular dynamics simulations and high-fidelity experiments will augment the understanding of the reactions towards bioplastic formation as well as biodegradation. Detailed structure and property measurements will be used to validate a finite element analysis tool that will enable the identification of the optimal structure to achieve properties comparable to commercial plastics using high throughput methods. Spirulina, an abundant photosynthetic microorganism that has been demonstrated to produce bioplastics when processed with heat and pressure will serve as a proof-of-concept system. The fundamental contribution of this project will be a design approach that accounts for the complexities of the transition of raw biomatter to bioplastics, exemplifying the Materials Genome Initiative's emphasis on predictive materials design and data-driven approaches to foster sustainable and innovative materials for a circular economy. This project is supported by the Division of Civil, Mechanical and Manufacturing Innovation (CMMI) of the Directorate for Engineering (ENG), the Division of Materials Research (DMR) of the Directorate for Mathematical and Physical Sciences (MPS), and the Division of Information and Intelligent Systems (IIS) of the Directorate for Computer and Information Science and Engineering (CISE).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.