CAREER: Nitrogen Activation: Splitting Kinetic Cycles and Breaking Energetic Barriers with Pulsed Catalysis

职业:氮活化:通过脉冲催化分裂动力学循环并打破能量屏障

基本信息

  • 批准号:
    1944619
  • 负责人:
  • 金额:
    $ 57.29万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-07-01 至 2025-06-30
  • 项目状态:
    未结题

项目摘要

Many industrial chemical processes utilize catalysts to increase reaction rates at fixed conditions of feed rates, temperature, and pressure. The project addresses a new approach to process technology, known as dynamic catalysis, in which the catalyst temperature is varied on the time scale of reactions occurring on the catalyst surface. The rapid temperature modulation can potentially create conditions that dramatically accelerate the overall reaction rate or change the product distribution in favorable ways. The study will evaluate the effectiveness of dynamic catalysis by both experimental and theoretical means, with an ultimate aim of decreasing the energy requirements for the catalytic synthesis of ammonia. Considering the highly energy-intensive nature of the industrial ammonia synthesis process, a cleaner and less energy-intensive alternative will have significant economic and environmental impacts. The primary goal of the study is to develop a new catalytic strategy for overcoming thermodynamic and kinetic barriers by dynamically operating a catalytic cycle at various temperatures and thermodynamic environments. However, the catalytic nitrogen fixation cycle is blocked at near-ambient conditions by a lack of energy to overcome kinetic/thermodynamic barriers (low temperature) or unfavorable binding energies for surface intermediates (high temperature/low pressure). The study will investigate the possibility that energetic barriers can be overcome at catalytically relevant resonant cycle times by rapidly and dynamically pulsing energy into the system (timescale of approximately 10 milliseconds). The approach combines 1) multi-scale modeling to demonstrate expected catalytic enhancement and determine optimal operating conditions, and 2) experimental testing and reactor design of a pulsed catalysis platform. The expected outcome is new understanding of the potential for nonequilibrium catalytic turnover from both theoretical and experimental approaches. Ideally, the fundamental understanding will lead to the design of catalyst platforms that operate beyond the theoretical maximum in catalytic turnover suggested by the classic volcano plot relation. The research will be integrated with a wide range of educational and outreach activities aimed at elevated engagement in STEM from students and the public, with particular emphasis on connections between basic research and societal impacts of the nitrogen cycle.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.
在一定的进料速率、温度和压力条件下,许多工业化学过程利用催化剂来提高反应速率。该项目提出了一种新的工艺技术方法,称为动态催化,其中催化剂温度随催化剂表面发生的反应的时间尺度而变化。快速的温度调制可以潜在地创造条件,显着加快总体反应速率或以有利的方式改变产物分布。该研究将通过实验和理论两方面的手段来评估动态催化的有效性,最终目的是降低催化合成氨的能量需求。考虑到工业氨合成过程的高能耗性质,一种更清洁、更低能耗的替代方法将对经济和环境产生重大影响。本研究的主要目标是开发一种新的催化策略,通过在不同温度和热力学环境下动态操作催化循环来克服热力学和动力学障碍。然而,由于缺乏能量来克服动力学/热力学障碍(低温)或表面中间体的不利结合能(高温/低压),催化固氮循环在近环境条件下受阻。该研究将探讨通过快速和动态地将能量脉冲进入系统(大约10毫秒的时间尺度),在催化相关的共振周期时间内克服能量障碍的可能性。该方法结合了1)多尺度建模来证明预期的催化增强并确定最佳操作条件;2)脉冲催化平台的实验测试和反应器设计。预期的结果是从理论和实验两方面对非平衡催化周转的潜力有了新的认识。理想情况下,基本的理解将导致催化剂平台的设计,超出经典火山情节关系所建议的催化周转的理论最大值。该研究将与广泛的教育和推广活动相结合,旨在提高学生和公众对STEM的参与度,特别强调基础研究与氮循环的社会影响之间的联系。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。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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Andrew Teixeira其他文献

FlowAR: A Mixed Reality Program to Introduce Continuous Flow Concepts
FlowAR:引入连续流概念的混合现实程序
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    3
  • 作者:
    Max Chen;Yichen Li;Hilson Shrestha;Noëlle Rakotondravony;Andrew Teixeira;Lane Harrison;Robert E. Dempski
  • 通讯作者:
    Robert E. Dempski
PFAS Incineration: Known Unknowns, Reaction Simulation, and ML to Predict Product Properties
PFAS 焚烧:已知的未知物、反应模拟和机器学习来预测产品特性

Andrew Teixeira的其他文献

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