CAREER: First Principles Modeling of Solvothermal and Coverage Effects for Selective Deoxygenation on Transition Metal Catalysts

将生物质转化为燃料或化学品通常涉及对生物衍生石油进行催化处理，以生产高价值的产品。催化剂的选择涉及到一项复杂的工作，即确定有选择地促进所需化学反应的材料，同时避免不希望发生的副反应。通常，催化剂是通过对多种材料组合进行繁琐的反复试验筛选而选出的。相比之下，该项目寻求通过数学和计算机模型来加速催化剂发现过程，这些模型将潜在催化材料的性质与它们在广泛条件下执行预期反应的能力联系起来。该项目带来的改进的催化剂设计将促进生物质作为碳中性能源的更广泛利用，直接解决国家能源安全问题，同时将对环境的影响降至最低。对研究生和本科生的计算研究培训将为新兴的计算和数据使能科学和工程领域提供未来的劳动力。该项目将专注于一个综合的研究和教育计划，提供对过渡金属催化剂(TMC)选择性催化脱氧活性的分子见解，特别是那些基于双金属磷化物和碳化物材料作为活性成分的催化剂。从技术角度来看，主要目标将是了解溶剂、温度和压力对芳香族含氧物结合模式的影响，同时揭示在存在溶剂和吸附物种的高表面覆盖率情况下不需要的产品的C-O键断裂和竞争路径的机理。这些目标将通过开发先进的第一原理蒙特卡罗(FPMC)和分子动力学(FPMD)算法来实现。这些新的采样算法将被用来通过考虑含有酚羟基的模型化合物来研究包括β-O-4键在内的碳-氧键断裂的催化活性。在所有这些计算中，溶剂分子将被显式表示，以确定它们对反应物、过渡态、产物和催化位置的影响。将系统地改变模型磷化物和碳化物催化剂的组成，以了解催化活性的结构-组成-性能关系。更广泛地说，FPMC和FPMD模拟将极大地推动计算建模的最先进水平，并提供先进的模拟工具来模拟相关热力学约束下的催化过程。由此产生的基本知识将为设计将木质纤维素生物质转化为燃料和化学品的高效和有效的催化剂提供合理的框架。算法开发将在一个广泛分布的软件套件CP2K中实施，从而能够对广泛的多相催化过程进行建模，包括基于沸石的催化和电催化。除了研究生和本科生教育部分外，该项目还将向经济困难社区提供K-12教育服务。此外，通过以探究性学习为目标的研讨会，中学教师的专业发展将导致STEM学科中代表性不足群体的留存率更高。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The conversion of biomass into fuels or chemicals often involves catalytic treatment of the bio-derived oil to produce high-value products. Catalyst selection involves a complicated juggling act to identify materials that selectively promote desired chemical reactions while avoiding undesired side reactions. Typically, catalysts are selected through tedious trial-and-error screening of many combinations of materials. In contrast, this project seeks to accelerate the catalyst discovery process through mathematical and computer models that relate the properties of prospective catalytic materials to their ability to carry out the desired reactions under a wide range of conditions. The improved catalyst designs resulting from the project will promote broader utilization of biomass as a carbon-neutral source of energy, directly addressing the nation's energy security while minimizing environmental impact. Training of graduate and undergraduate students in computational research will provide a future workforce for the emerging areas of computational and data-enabled science and engineering.The project will focus on an integrated research and education program that provides molecular insights into the selective catalytic deoxygenation activity of transition metal catalysts (TMCs), particularly those based on bimetallic phosphide and carbide materials as the active components. From a technical standpoint, the primary objectives will be to understand the effects of solvent, temperature, and pressure on the binding modes of aromatic oxygenates while revealing mechanistic insights into C-O bond cleavage and competitive pathways for undesired products in the presence of solvents and high surface coverages of adsorbed species. The objectives will be accomplished by developing advanced first-principles Monte Carlo (FPMC) and molecular dynamics (FPMD) algorithms. These novel sampling algorithms will be used to investigate catalytic activity for the cleavage of carbon oxygen bonds including the beta-O-4 linkage by considering model compounds containing a phenolic hydroxyl group. In all these calculations, solvent molecules will be explicitly represented to determine their effect on reactants, transition states, products, and catalytic sites. Composition of model phosphide and carbide catalysts will be systematically varied to understand the structure-composition-property relationship for catalytic activity. More broadly, the FPMC and FPMD simulations will significantly advance the state-of-the-art in computational modeling, and provide advanced simulation tools to model catalytic processes under relevant thermodynamic constraints. The fundamental knowledge thus generated will provide a rational framework for designing efficient and effective catalysts for converting lignocellulosic biomass into fuels and chemicals. The algorithmic developments will be implemented in a widely distributed software suite, CP2K, enabling modeling of a wide range of heterogeneous catalytic processes, including zeolite-based catalysis and electrocatalysis. Beyond the graduate and undergraduate educational components, the project will provide K-12 educational outreach to economically disadvantaged communities. In addition, professional development of middle school teachers, through workshops targeted at inquiry-based learning, will lead to higher retention of underrepresented groups in STEM disciplines.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.