Computational Modeling of Carbon Monoxide Dehydrogenase Model Systems for Carbon Dioxide Fixation

用于二氧化碳固定的一氧化碳脱氢酶模型系统的计算模型

• 批准号: 9813186
• 负责人: Julien Panetier
• 金额: $ 43万
• 依托单位: STATE UNIVERSITY OF NY,BINGHAMTON
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-10 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9813186
• 关键词: Acids; Active Sites; Address; Anions; Area; Back; Base Pairing; Binding; Biological Models; Carbon; Carbon Dioxide; Carbon Monoxide; Carbon monoxide dehydrogenase; Catalysis; Charge; Chemicals; Chemistry; Collaborations; Computer Simulation; Consumption; Crystallization; Depressive disorder; Development; Droughts; Economics; Electricity; Electron Transport; Electrons; Electrostatics; Energy-Generating Resources; Environment; Enzymes; Exposure to; Family; Feeling suicidal; Floods; Fossil Fuels; Frequencies; Global Warming; Goals; Guidelines; Health; Histidine; Human; Hurricane; Hydrogen Bonding; Infrastructure; Ions; Iron; Kinetics; Learning; Ligands; Literature; Mental Health; Metals; Molecular; Nickel; Outcome; Oxidation-Reduction; Planet Earth; Population Growth; Post-Traumatic Stress Disorders; Production; Property; Protons; Reaction; Recycling; Reporting; Research; Research Project Grants; Resources; Role; Solar Energy; Source; Structure; Students; Sulfur; Techniques; Thermodynamics; Time; Transition Elements; Universities; Work; acute traumatic stress disorder; adduct; anthropogenesis; atmospheric carbon dioxide; base; biological systems; carbene; carbon compound; carbon emissions; catalyst; chemical bond; chemical reduction; climate change; computational chemistry; cost; design; electronic structure; experience; experimental group; functional group; fundamental research; greenhouse gases; improved; innovation; insight; next generation; nutrition; sample fixation; suicidal risk

Project Abstract Atmospheric CO2 concentrations have reached their highest to date, which holds immediate and dire consequences for the environment and all areas of human health. Based on these imminent and growing threats, there is an urgent need to transition our current infrastructure from fossil fuels to renewable energy sources. In this context, solar energy or renewable electricity could be used to drive the catalytic conversion of CO2 and H2O into energy-rich chemicals (similar to biological systems) whereby energy is stored indefinitely in chemical bonds for on-demand use. The chemical reduction of CO2 to other carbon compounds with higher chemical energy would close the carbon cycle and deliver chemical fuels that are compatible with existing infrastructure. However, existing CO2 catalysts often suffer from very high overpotentials, low turnover frequency and poor substrate selectivity in the presence of H2O. In contrast, carbon monoxide dehydrogenase (CODH) enzymes, such as the nickel-carbon monoxide dehydrogenase II from Carboxydothermus hydrogenoformans are able to extract energy from their environments in order to carry out the reversible conversion of CO to CO2 at high rates and selectivity while operating near the thermodynamic potential. Crystal structure of Ni-CODHCh II reveals the presence of an iron-sulfur cluster combined with a nickel atom, called C-cluster. One structural feature of this C-cluster is the presence of a Fe3S4 cluster, which bridges the nickel and iron atoms together. This cooperative Lewis acid-base pair is considered a key feature for the exceptional activity of Ni-CODHCh II. The long-term goal of this proposal is to employ computational chemistry in combination with complementary experimental efforts to design innovative catalysts that mimic essential structural features and functions of CODH enzymes for the selective conversion of CO2 to CO in the presence of H2O. We propose to accomplish this goal through the following specific aims: (i) To investigate earth-abundant materials supported by macrocyclic redox-active ligands; and (ii) To catalyze the production of carbon monoxide through the use of charged functional groups in the secondary coordination sphere. More specifically, this proposal outlines a plan for the rational design of innovative catalysts for CO2-to-CO conversion based on thermodynamic and kinetic properties. These principles have been established as critical in heterogeneous catalysis. For instance, in the Sabatier principle, the magnitude of the substrate binding energy at the metal in critical intermediates is related to the overall catalyst rate. The use of molecular catalysts will allow us to tune these crucial bond energies in order to achieve optimal values. In this context, electronic structure calculations will provide a straightforward approach to study the key thermodynamic and kinetic properties that are required in the development of molecular catalysts with (i) high selectivity for the desired product; and (ii) fast kinetics over a long period of time. Successful completion of these aims will produce general guidelines based on fundamental thermodynamic and kinetic properties for the design of next generation molecular catalysts for CO2 reduction to CO or any high value C1 product.

项目摘要 大气中二氧化碳浓度已达到迄今为止的最高水平，这将带来直接而可怕的后果 对环境和人类健康所有领域的影响。基于这些迫在眉睫且日益增长的威胁， 迫切需要将我们现有的基础设施从化石燃料转变为可再生能源。在 在此背景下，太阳能或可再生电力可用于驱动CO2和H2O的催化转化 转化为富含能量的化学物质（类似于生物系统），能量无限期地储存在化学键中 供按需使​​用。将CO2化学还原为具有更高化学能的其他碳化合物 将关闭碳循环并提供与现有基础设施兼容的化学燃料。然而， 现有的 CO2 催化剂通常存在非常高的过电势、低周转频率和较差的底物 H2O 存在下的选择性。相比之下，一氧化碳脱氢酶（CODH），例如 来自 Carboxydothermus Hydrogenoformans 的镍一氧化碳脱氢酶 II 能够提取能量 以便以高速率和选择性将 CO 可逆转化为 CO2 同时在热力学势附近运行。 Ni-CODHCh II 的晶体结构揭示了 铁硫簇与镍原子结合，称为C簇。该 C 簇的结构特征之一是 Fe3S4 簇的存在，将镍和铁原子桥接在一起。这种协同路易斯酸碱 这对被认为是 Ni-CODHCh II 卓越活性的关键特征。本提案的长期目标 是采用计算化学与互补的实验努力相结合来设计 模仿CODH酶的基本结构特征和功能的创新催化剂，用于选择性 在 H2O 存在下，CO2 转化为 CO。我们建议通过以下方式实现这一目标 具体目标： (i) 研究由大环氧化还原活性配体支持的地球丰富的材料； (二) 通过使用二级带电官能团催化一氧化碳的产生 协调范围。更具体地说，该提案概述了创新催化剂合理设计的计划 基于热力学和动力学性质的 CO2 到 CO 的转化。这些原则已 被认为是多相催化中的关键。例如，在萨巴蒂尔原理中， 关键中间体中金属的底物结合能与总催化剂速率有关。使用 分子催化剂将使我们能够调整这些关键的键能，以达到最佳值。在这个 在上下文中，电子结构计算将为研究关键热力学提供一种直接的方法 和开发分子催化剂所需的动力学特性，（i）对 想要的产品； (ii) 长时间内的快速动力学。成功完成这些目标将产生 基于基本热力学和动力学特性的下一代设计的一般准则 用于将 CO2 还原为 CO 或任何高价值 C1 产品的分子催化剂。