CDS&E:CAS:Automated Embedded Correlated Wavefunction Theory for Kinetic Modeling in Heterogeneous Catalysis

在化学系化学催化项目的支持下，东北大学的赵青正在开发先进的计算模拟工具，以了解以可再生电能/储存电子为动力的氨合成中的基础化学。氨是化肥中的关键成分，也是理想的零碳能源载体。如果人们能够在常温和有限压力下利用氮气和水实现电化学合成氨，并获得有利的动力学曲线，人们将拥有一种更可持续的技术来取代传统的工业哈伯-博世工艺来生产氨，该工艺消耗大量化石燃料并排放大量二氧化碳。对反应机理的可靠理解是设计更有效的电催化剂的基础。本研究旨在发展超越传统建模工具的高水平量子力学模拟，以阐明这一重要的催化转化。这个项目将在一个研讨会中整合多种教育活动和推广，帮助K-12教师开发关于计算、催化和可持续发展主题的课程材料，旨在促进更多样化的科学界对科学的兴奋。在这个奖项下，东北大学的赵青和她的研究团队将开发一种定性和定量可靠的量子力学方法和自动化嵌入式关联波函数(AutoECW)理论，用于多相催化的动力学建模。该项目旨在开发和实现AutoECW，以消除标准嵌入式相关波函数(ECW)理论中的两个瓶颈-需要专业知识和高计算成本-以加速该理论在计算多相催化中的主流应用。本项目以氨电合成为例，利用开发的AutoECW对金属催化剂的电化学氮还原反应(NRR)进行微观动力学模拟，试图重新阐明反应机理。基础认识的改进有可能启发氨电合成的新设计原则和描述，以实现发现具有更高活性和选择性的新型催化剂的目标。AutoECW旨在实现对多相催化中许多引人注目的系统的适当模拟，这些系统很难用传统的密度泛函理论建模。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。

With the support of the Chemical Catalysis program in the Division of Chemistry, Qing Zhao of Northeastern University is developing advanced computational modeling tools to understand fundamental chemistry in ammonia synthesis powered by renewable electrical energy/stored electrons. Ammonia is a critical component in fertilizers and an ideal zero-carbon energy carrier. If one could achieve the electrochemical production of ammonia using nitrogen gas and water at ambient temperature and limited pressure with a favorable kinetic profile, one would have a more sustainable technology to replace the traditional industrial Haber-Bosch process for ammonia production, which consumes tremendous amounts of fossil fuel and emits massive amounts of carbon dioxide. A reliable understanding of reaction mechanisms is foundational in designing more efficient electrocatalysts. This research aims to develop high-level quantum mechanical simulations beyond the conventional modeling tools to elucidate this important catalytic transformation. This project will integrate multiple educational activities and outreach in a workshop to help K-12 teachers develop curriculum materials on the topics of computation, catalysis, and sustainability, aiming at advancing excitement about science in a more diverse scientific community.Under this award, Qing Zhao and her research team at Northeastern University will develop a qualitatively and quantitatively reliable quantum mechanical method and an automated embedded correlated wavefunction (AutoECW) theory for kinetic modeling in heterogeneous catalysis. This project aims to develop and implement AutoECW to eliminate two bottlenecks in standard embedded correlated wavefunction (ECW) theory – requiring specialized expertise and high computational cost – to accelerate the mainstream use of this theory in computational heterogeneous catalysis. Using ammonia electrosynthesis as an example, this project seeks tol re-elucidate reaction mechanisms by performing microkinetic modeling of the electrochemical nitrogen reduction reaction (NRR) with metal catalysts using the developed AutoECW. Improvements in fundamental understanding have the potential to inspire new design principles and descriptors for ammonia electrosynthesis toward the goal of discovering novel catalysts with improved activity and selectivity. AutoECW aims to enable proper simulations of many compelling systems within heterogeneous catalysis that are difficult to model with conventional density functional theory.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.