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Novel Simulation Strategies For Predicting Polymer Properties

预测聚合物性能的新颖模拟策略

基本信息

批准号：
1905632
负责人：
Scott Milner
金额：
$ 37.63万
依托单位：
Pennsylvania State Univ University Park
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：
2019-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1905632&HistoricalAwards=false
关键词：
Novel Simulation Strategies Predicting Polymer

项目摘要

NONTECHNICAL SUMMARYThis award supports theory, computation, and education with an aim to advance understanding of polymeric materials. Polymeric materials are long chain-like molecules. How sharp is that polymer interface? Important things happen at interfaces between different polymers. For example: hard plastic parts are stiff and tough to shatter, because they contain tiny droplets of rubbery polymer dispersed in a second, stiffer polymer. The rubbery droplets absorb impacts; without them, the plastic would crack when hit. This trick works because at the surface of the droplets, long polymer chains on each side of the interface intermingle enough to knit the interface together. Otherwise, the part could break easily, with the droplets pulling away from the stiff material as it cracked. Another application for which polymer interfaces are crucial is in polymer-based solar cell materials. These materials are the subject of intense research focus as alternatives to "hard" silicon-based photocells, with potential advantages including flexible materials and easier production; they are made like plastic sheeting in a chemical plant, not like computer chips in a billion-dollar ultraclean fab facility. Here, the interface is between special "donor" and "acceptor" semiconducting polymers. These donor-acceptor interfaces help pull apart pairs of opposite charges produced when sunlight is absorbed by the polymers, so the charges can be "harvested" as electricity. For rubber-toughened plastics, the interface needs to be a bit broad; for photocells, the interface needs to be sharp. For a given pair of polymers A and B, the interfacial width is controlled by how strongly the A and B chain repeat units repel each other. This repulsion depends on the chemical structure of A and B, which synthetic chemists can vary with amazing variety. But how strongly will polymers of structures A and B repel each other? If this can be predicted, it could help the chemist decide what structures to make. The PI's research group has developed a new way to use computer simulations to predict the strength of repulsion between pairs of polymers, as a complement to challenging experiments. The PI's method relies on the idea that the more A and B repel each other, the more work is required to mix A and B together.To compute the work of mixing, a trick inspired by CGI animation is used: start with a simulated sample of pure A chains, and gradually "morph" half the chains into B chains, measuring how the energy rises as the morph progresses. By comparing the work required to prepare an A-B mixture by morphing half the chains, to the work to make a pure sample of B chains, by morphing all the chains, the work required to mix A and B chains can be measured.The bigger the work of mixing is, the narrower the interface will be between demixed A and B material. In fact, the interface width is governed by a compromise between energy and entropy. Flexible polymer chains on either side of the interface have two conflicting desires: to avoid contact with the "other" chains, and to wander about freely. The greater the cost for repulsive contacts, the more restricted are the wanderings of chains across the interface.With the new "morphing" simulation method, the PI can predict interfacial widths for polymer pairs from chemical structure alone. This powerful tool will help polymer chemists and engineers design more effective polymers for solar cells, as well a host of other applications in advanced materials.TECHNICAL SUMMARYThis award supports theory, computation, and education with an aim to advance understanding of polymeric materials. With continuing improvements in computer power and recent advances in simulation techniques, it is finally becoming possible to predict key material properties for real polymers from their chemical structure. This project will develop and exploit new approaches to predict three kinds of properties: 1. interfacial tensions between polymer crystals, melts, and substrates, which are central to predicting nucleation barriers and designing nucleating agents; 2. chi parameters between polymer pairs, which are necessary for predicting miscibility, microphase separation, and strength of interfaces between immiscible polymers; and 3. entanglement length for flexible, semiflexible, and stiff polymer chains in melts and solutions, which is the central parameter in the modern theory predicting flow behavior of polymer melts and solutions from chain architecture. Most polymers crystallize very reluctantly. Practical processing relies on nucleating agents and flow-induced crystallization to achieve high nucleation rates, resulting in materials with smaller spherulites and improved properties (optical clarity and strength). Predicting nucleation rates starts with classical nucleation theory, which describes the critical nucleus in terms of its free energy and tension with surrounding melt. Correspondingly, nucleating agents provide substrates for nuclei to form, with interfacial tensions that favor crystal over melt. To predict nucleation rates and design nucleating agents, it is critical to predict tensions between polymer crystals, melts, and substrates. In this project, new simulation methods will be developed to do that, for chemically realistic chains. Predicting chi from chain structures is a grand unmet challenge for polymer theory. To account for how real molecules pack and interact, simulation is the right approach. Since chi measures the excess mixing free energy, free energies must be obtained from blend simulations. The PI has developed a new method, that computes the work to "morph" one kind of chain into another. The PI will extend this method, from simple bead-spring chains to real chains in atomistic detail. Multiple attempts have been made to construct theories for how the entanglement length scales with chain volume, flexibility, and concentration. Real polymer melts are well described by Lin-Noolandi scaling, stiff chains by Morse scaling. Everaers presented a scaling ansatz consistent with Morse but not LN. This project will develop a new scaling theory that unifies these approaches, and comprehensive simulations to measure entanglement across flexible and stiff chain melts and solutions. The shale gas revolution is leading to substantial new investment in U.S. polyolefin plants. Better nucleating agents to improve properties of these low-cost ubiquitous polymers could lead to increased use as lightweight, energy-saving structural materials. Chi parameters between donor and acceptor chains in semiconducting polymers are hard to measure, but are key attributes in the design of heterojunction interfaces in next-generation polymer photovoltaics, which are the subject of intense research focus as potential complementary materials to hard silicon-based photocells, and may help enable the U.S. and the world to confront climate change and transition to a less carbon-intensive energy economy.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.

该奖项支持理论、计算和教育，旨在促进对聚合物材料的理解。高分子材料是长链状分子。聚合物界面有多锋利？重要的事情发生在不同聚合物的界面上。例如：硬塑料部件坚硬且不易破碎，因为它们含有分散在第二种更硬的聚合物中的橡胶聚合物的微小液滴。橡胶液滴吸收冲击；没有它们，塑料在受到撞击时会破裂。这种方法之所以有效，是因为在液滴的表面，界面两侧的长聚合物链相互混合，足以将界面编织在一起。否则，零件很容易破裂，当它破裂时，液滴会从坚硬的材料中脱落。聚合物界面的另一个重要应用是聚合物基太阳能电池材料。作为“硬”硅基光电池的替代品，这些材料是研究热点，其潜在优势包括材料柔性和更容易生产；它们就像化工厂里的塑料板一样，而不像价值数十亿美元的超净工厂里的电脑芯片。在这里，界面是在特殊的“供体”和“受体”半导体聚合物之间。当阳光被聚合物吸收时，这些供体-受体界面有助于分离成对的相反电荷，因此电荷可以“收获”为电能。对于橡胶-增韧塑料，界面需要稍微宽一点；对于光电池来说，接口必须是锐利的。对于给定的一对聚合物a和B，界面宽度由a和B链重复单元相互排斥的强度来控制。这种斥力取决于A和B的化学结构，而合成化学家的化学结构变化惊人。但是结构A和结构B的聚合物相互排斥的强度有多大呢？如果能预测到这一点，就能帮助化学家决定制造什么样的结构。PI的研究小组已经开发出一种新的方法，使用计算机模拟来预测聚合物对之间的排斥力强度，作为对具有挑战性的实验的补充。PI的方法基于A和B相互排斥越多，将A和B混合在一起所需的功就越多。为了计算混合的效果，使用了一个受CGI动画启发的技巧：从纯a链的模拟样本开始，逐渐将一半的链“变形”为B链，测量随着变形的进行能量是如何上升的。通过比较通过改变一半链来制备a -B混合物所需的功，和通过改变所有链来制备B链纯样品所需的功，可以测量混合a链和B链所需的功。混合功越大，解混后的A、B材料界面越窄。事实上，界面宽度是由能量和熵之间的折衷决定的。界面两侧的柔性聚合物链有两个相互冲突的愿望：避免与“其他”链接触，并自由地漫游。斥力接触的代价越大，链在界面上的漂移就越受限制。利用新的“变形”模拟方法，PI可以仅从化学结构预测聚合物对的界面宽度。这个强大的工具将帮助聚合物化学家和工程师为太阳能电池设计更有效的聚合物，以及许多其他先进材料的应用。该奖项支持理论、计算和教育，旨在促进对聚合物材料的理解。随着计算机能力的不断提高和模拟技术的最新进展，通过化学结构预测真实聚合物的关键材料特性终于成为可能。该项目将开发和利用新的方法来预测三种性质：1。聚合物晶体、熔体和基底之间的界面张力，这是预测成核屏障和设计成核剂的核心；2. 聚合物对之间的Chi参数，这是预测不混相聚合物之间的混相、微相分离和界面强度所必需的；和3。柔性、半柔性和刚性聚合物链在熔体和溶液中的缠绕长度，是现代理论中从链结构预测聚合物熔体和溶液流动行为的中心参数。大多数聚合物不容易结晶。实际加工依赖于成核剂和流动诱导结晶来实现高成核率，从而使材料具有更小的球晶和更好的性能（光学清晰度和强度）。预测成核速率从经典成核理论开始，该理论用自由能和与周围熔体的张力来描述临界核。相应地，成核剂为原子核的形成提供了基底，其界面张力有利于晶体而不是熔体。为了预测成核速率和设计成核剂，预测聚合物晶体、熔体和衬底之间的张力是至关重要的。在这个项目中，新的模拟方法将被开发出来，用于化学上真实的链。从链结构预测chi是聚合物理论面临的巨大挑战。为了解释真实的分子是如何聚集和相互作用的，模拟是正确的方法。由于chi测量的是过量的混合自由能，因此必须从混合模拟中获得自由能。PI开发了一种新方法，计算将一种链“变形”为另一种链所需的功。PI将扩展这种方法，从简单的串珠弹簧链到原子细节的实链。对于缠结长度如何随链的体积、柔韧性和浓度的变化而变化的理论，人们进行了多次尝试。真实的聚合物熔体用Lin-Noolandi标度来描述，用Morse标度来描述硬链。Everaers给出了一个符合Morse但不符合LN的标度分析。该项目将开发一种新的标度理论，将这些方法结合起来，并进行全面的模拟，以测量柔性和刚性链熔体和溶液之间的缠结。页岩气革命正在为美国聚烯烃工厂带来大量新投资。更好的成核剂可以改善这些低成本普遍存在的聚合物的性能，从而增加其作为轻质节能结构材料的使用。半导体聚合物中供体链和受体链之间的Chi参数很难测量，但却是下一代聚合物光伏电池中异质结界面设计的关键属性，作为硬硅基光电池的潜在补充材料，这是一个备受关注的研究主题，可能有助于美国和世界应对气候变化，并向低碳密集型能源经济过渡。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。