SusChEM: Multiscale Interaction Potentials for Cellulose

非技术总结材料研究部和化学部为该奖项提供资金。这个SusChEM项目涉及将纤维素生物质转化为生物燃料作为可持续能源和新材料的可持续原料的计算研究。从多年生植物(如草)中提取的生物燃料最受欢迎，因为这些植物生长在边际土地上，可以重复收获。植物生物质的经济利用的一个主要障碍是纤维素纤维对预处理的抵抗力，以便将其转化为可用燃料。关于纤维的详细结构以及它们与水、其他化学溶剂和酶的相互作用，许多问题都知之甚少。该团队将使用高质量的量子力学计算机模拟来开发准确的计算模型来描述这些相互作用，最终目标是提高生物质转化的效率，并应用于发现和建模基于纤维素的材料。研究团队将让本科生和研究生参与可持续性研究，旨在找到解决方案，使碳排放与碳封存达到平衡。学生们将有机会参观橡树岭国家实验室，并在政府实验室体验研究。该团队将开发一种自给自足的计算化学USB记忆棒，带有执行电子结构和其他建模的组件。所包含的计算机程序将包括许多不需要详细了解分子量子力学就可以使用的程序。该团队将向地区大学传播USB记忆棒，并帮助教职员工在课堂上融入建模。PI还将开发建模模块和教程，在物理化学和有机化学课程中教授概念。技术总结材料研究部和化学部为该奖项提供资金。通过这个SusChEM项目，研究小组将开发一个多尺度的纤维素纤维模型，并研究纤维和纤维束的基本性质，将其应用于可持续能源和发现可持续的纤维素材料。研究小组将利用自适应作用力匹配方法，通过与精确的电子结构力进行拟合，开发出准确的纤维素潜力。通过迭代过程，自适应力匹配提供了高质量的参考力和用于拟合的代表性训练集。这使得可以在不使用非常复杂的能量表达式的情况下开发出准确的力场。因此，可以高效地对较大的结构进行建模。一旦自适应作用力匹配纤维素场可用，将使用多尺度粗粒化方法来开发精确的粗粒化势场。粗粒化的潜力将允许对长纤维和纤维束进行建模。纤维素势的发展将只有电子结构信息作为输入。该模型将被验证以重现实验性质，如晶格常数和旋量分布。经过验证的全原子和粗粒势将用于解决纤维原纤维的基本问题，包括原纤维中的链的数量、扭曲的倾向、界面上的旋转构象、多形转变的自由能和原纤维的持续长度。将开发的精确多尺度潜力将使水合纤维素纤维的可靠建模成为可能，并将进一步研究纤维素生物质和纤维素基材料的建模。纤维素力场将是开发其他模型的垫脚石，这些模型涉及替代溶剂，如离子液体和酶。准确的纤维素势的成功开发将代表着自适应力匹配的重大进步。将自适应力匹配发展成为一种可靠的协议，将昂贵的电子结构势映射到简单的分子力学力场，将对材料研究产生广泛的影响。该奖项还支持将计算建模融入化学教育的教育活动。将开发一个独立的计算化学USB记忆棒，以方便本科生进行计算机建模，并在课堂上使用计算机建模。不需要安装或许可，允许用户专注于问题而不是计算细节。PI将向地区大学传播USB记忆棒，并帮助教职员工在课堂上融入建模。PI还将开发建模模块和教程，以教授物理化学和有机化学中的重要概念。PIS将让本科生和研究生参与碳中性可持续性研究，并为他们提供参观橡树岭国家实验室和在国家实验室体验研究的机会。

NON-TECHNICAL SUMMARYThe Division of Materials Research and the Chemistry Division contribute funds to this award. This SusChEM project involves computational research on the conversion of cellulosic biomass to biofuel as a sustainable energy source and a sustainable feedstock for new materials. Biofuel derived from perennial plants, such as grass, is most desirable since these plants grow on marginal land and can be harvested repeatedly. One major roadblock for economical utilization of plant biomass is the resistance of cellulosic fibrils to pretreatment to facilitate their conversion to usable fuels. Many questions regarding the detailed structures of fibrils and their interactions with water, other chemical solvents, and enzymes are poorly understood. The team will use high quality quantum mechanical computer simulations to develop accurate computational models to describe these interactions, with the ultimate goal of improving the efficiency of biomass conversion and for applications for the discovery and modeling of cellulose-based materials.The research team will engage undergraduate and graduate students in sustainability research which aims to find solutions to enable the balance of carbon emission with carbon sequestration. Students will have the opportunity to visit Oak Ridge National Laboratory and experience research in a government laboratory. The team will develop a self-contained computational chemistry USB memory stick with packages to perform electronic structure and other modeling. The computer programs contained will include many that can be used without a detailed knowledge of molecular quantum mechanics. The team will disseminate the USB memory stick to regional colleges and help the faculty to incorporate modeling in their classrooms. The PI will also develop modeling modules and tutorials to teach concepts in physical and organic chemistry curricula. TECHNICAL SUMMARYThe Division of Materials Research and the Chemistry Division contribute funds to this award. Through this SusChEM project, the research team will develop a multiscale model for cellulose fibrils and investigate fundamental properties of fibrils and fiber bundles with application to sustainable energy and the discovery of sustainable cellulose-based materials. The research team will develop an accurate potential for cellulose by fitting to accurate electronic structure forces using the adaptive force matching method. Through an iterative procedure, adaptive force matching provides both high quality reference forces and representative training sets for fitting. This allows accurate force fields to be developed without using very complex energy expressions. As a consequence, larger structures can be modeled efficiently. Once the adaptive force matching cellulose force field is available, an accurate coarse-grained potential will be developed using the multiscale coarse-graining approach. The coarse-grained potential will allow long cellulose fibrils and fibril bundles to be modeled. The cellulose potential will be developed with only electronic structure information as input. The model will be validated to reproduce experimental properties, such as lattice constants and rotamer distributions. The validated all-atom and coarse-grained potentials will be used to address fundamental problems of cellulosic fibrils, including the number of chains in a fibril, the tendency for twisting, rotamer conformations at the interface, free energy of polymorph transformations, and the persistence length of the fibril. The accurate multiscale potentials to be developed will enable reliable modeling of hydrated cellulosic fibrils, and further research in modeling cellulosic biomass and cellulose-based materials. The cellulose force field will be a stepping stone for the developments of additional models that involve alternative solvents, such as ionic liquids, and enzymes. Successful development of an accurate cellulose potential will represent a major advance of adaptive force matching. The development of adaptive force matching into a reliable protocol for mapping an expensive electronic structure potential to a simple molecular mechanics force field will have broad impact for material research in general. This award also supports educational activities to integrate computational modeling into Chemistry education. A self-contained computational chemistry USB memory stick will be developed to facilitate computer modeling by undergraduate students and the use of computer modeling in classrooms. No installation or licensing is needed, allowing the user to focus on the problem instead of computational details. The PI will disseminate the USB memory stick to regional colleges and help the faculty incorporate modeling in their classrooms. The PI will also develop modeling modules and tutorials to teach important concepts in physical and organic chemistry. The PIs will engage undergraduate and graduate students in carbon neutral sustainability research and provide them with the opportunity to visit Oak Ridge National Laboratory and experience research in a national laboratory.