DMREF: Computational Chemistry to Accelerate Development of Long Wave Infrared Polymers

DMREF：计算化学加速长波红外聚合物的开发

• 批准号: 2118578
• 负责人: Jeffrey Pyun
• 金额: $ 179.95万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118578&HistoricalAwards=false
• 关键词: DMREF; Computational; Chemistry; Accelerate; Development

This project will develop plastic optical materials to create lenses, windows, and optical elements for long wave infrared (LWIR) thermal imaging systems. IR thermal imaging and optical technologies are critical across the defense and military sectors, while the potential of IR thermal imaging and detection for applications in consumer electronics, transportation, medical imaging, security and robotics have also been known for decades. However, the high cost of IR cameras & detectors has impeded widespread use of these systems in consumer markets. In the vast majority of these imaging systems, expensive, inorganic semiconductors are required for the fabrication of LWIR optical components. Importantly, one of the common materials used in these efforts, germanium, has been identified as a US critical mineral, a lack of which would profoundly impact US defense capabilities. Hence, the development of new inexpensive and moldable polymers for use as LWIR plastic optics would be a significant advance to lower the cost of LWIR cameras and ensure US national security. To address this challenging problem, this interdisciplinary project has been launched in collaboration with scientists at the Air Force Research Laboratory (AFRL), and it will harness a wide range of computational tools and machine learning capabilities to accelerate materials discovery. Thus, the project closely aligns with the Materials Genome Initiative for Global Competitiveness (MGI).This project aims to yield optical polymers with high LWIR transparency, high refractive index, and melt processability. The research will examine the use of elemental sulfur and liquid sulfur media to prepare high refractive index (RI, or n), LWIR transparent polymer optics for LWIR thermal imaging. The project will be directed by computational chemistry tools to accelerate design and synthesis efforts. Density functional theory (DFT) and molecular dynamics (MD) will be used in tandem to simulate infrared (IR) spectra of comonomers and hybrid sulfur copolymers and rapidly screen candidates with high LWIR transparency from databases of millions of known molecules. Furthermore, machine learning tools will be developed to rapidly create new candidate material libraries. Quantum cluster equilibrium (QCE) calculations, along with DFT and MD, will be exploited to quantify the complex, dynamic nature of liquid sulfur and to determine solubility parameters in order to expand the scope of miscible/soluble organic comonomers. ML tools will be developed to integrate all of these efforts and create a universal computational package for rapid LWIR polymers discovery. The computational work will be closely looped to (macro)molecular synthesis, polymer processing and optical characterization of new chalcogenide-based hybrid polymers.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.

该项目将开发塑料光学材料，用于制造长波红外（LWIR）热成像系统的透镜，窗口和光学元件。 红外热成像和光学技术在国防和军事领域至关重要，而红外热成像和检测在消费电子、运输、医疗成像、安全和机器人等领域的应用潜力也已经被人们所知了几十年。 然而，IR相机检测器的高成本阻碍了这些系统在消费者市场中的广泛使用。在绝大多数这些成像系统中，需要昂贵的无机半导体来制造长波红外光学元件。 重要的是，在这些努力中使用的常见材料之一，锗，已被确定为美国的关键矿物，缺乏这将深刻影响美国的防御能力。 因此，开发新的廉价和可模塑的聚合物用作长波红外塑料光学器件将是降低长波红外相机成本和确保美国国家安全的重大进步。 为了解决这个具有挑战性的问题，这个跨学科项目已经与空军研究实验室（AFRL）的科学家合作启动，它将利用广泛的计算工具和机器学习能力来加速材料发现。 因此，该项目与全球竞争力材料基因组计划（MGI）紧密结合，旨在生产具有高长波红外透明性、高折射率和熔融加工性的光学聚合物。该研究将研究使用元素硫和液体硫介质来制备用于长波红外热成像的高折射率（RI或n）、长波红外透明聚合物光学器件。该项目将由计算化学工具指导，以加速设计和合成工作。密度泛函理论（DFT）和分子动力学（MD）将用于串联模拟共聚单体和混合硫共聚物的红外（IR）光谱，并从数百万已知分子的数据库中快速筛选具有高LWIR透明度的候选分子。此外，还将开发机器学习工具，以快速创建新的候选材料库。量子簇平衡（QCE）计算，沿着与DFT和MD，将被用来量化复杂的，动态的液体硫的性质，并确定溶解度参数，以扩大范围的可混溶/可溶性有机共聚单体。ML工具将被开发来整合所有这些努力，并创建一个通用的计算包，用于快速发现LWIR聚合物。计算工作将与（大）分子合成、聚合物加工和新型硫族化合物基混合聚合物的光学表征紧密相连。该奖项反映了NSF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。

项目成果

Ring-to-Chain Structural Relaxation of Elemental Sulfur upon Photoexcitation

光激发下元素硫的环链结构弛豫

• DOI: 10.1021/acsmaterialslett.2c00866
• 发表时间: 2022
• 期刊: ACS Materials Letters
• 影响因子: 11.4
• 作者: Cho, Eunkyung;Pratik, Saied Md;Pyun, Jeffrey;Coropceanu, Veaceslav;Brédas, Jean-Luc
• 通讯作者: Brédas, Jean-Luc

High Refractive Index Chalcogenide Hybrid Inorganic/Organic Polymers for Integrated Photonics

用于集成光子学的高折射率硫属化物杂化无机/有机聚合物

• DOI: 10.1002/adom.202200176
• 发表时间: 2022
• 期刊: Advanced Optical Materials
• 影响因子: 9
• 作者: Nishant, Abhinav;Kim, Kyung‐Jo;Showghi, Sasaan A.;Himmelhuber, Roland;Kleine, Tristan S.;Lee, Taeheon;Pyun, Jeffrey;Norwood, Robert A.
• 通讯作者: Norwood, Robert A.

Nuclear magnetic resonance structural characterization of sulfur‐derived copolymers from inverse vulcanization. Part 1: Styrene

反硫化硫衍生共聚物的核磁共振结构表征。

• DOI: 10.1002/pol.20220329
• 发表时间: 2022
• 期刊: Journal of Polymer Science
• 影响因子: 3.4
• 作者: Pyun, Jeffrey;Carrozza, Chiara Francesca;Silvano, Selena;Boggioni, Laura;Losio, Simona;de Angelis, Alberto Renato;O'Neil Parker Jr, Wallace
• 通讯作者: O'Neil Parker Jr, Wallace

Sulfenyl Chlorides: An Alternative Monomer Feedstock from Elemental Sulfur for Polymer Synthesis

• DOI: 10.1021/jacs.2c10317
• 发表时间: 2022-12-07
• 期刊: JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
• 影响因子: 15
• 作者: Kang, Kyung-Seok;Olikagu, Chisom;Pyun, Jeffrey
• 通讯作者: Pyun, Jeffrey

Hole versus electron transport in fullerenes

• DOI: 10.1016/j.orgel.2023.106798
• 发表时间: 2023-03
• 期刊: Organic Electronics
• 影响因子: 3.2
• 作者: Eunkyung Cho;V. Coropceanu;J. Brédas