Transition metal controlled nitrogen chemistry in zeolite and protein environments using a unified quantum embedding model

氮化合物在地球的生态系统中起着至关重要的作用，当它们从大气进入陆地和海洋的生物体内时，不断地从一种形式转化为另一种形式。例如，一氧化氮气体（NO）是全球氮循环的关键中间体，在几乎所有生命形式的许多过程中起着重要作用，通常作为信号分子。然而，重工业和机动车排放的一氧化氮和有毒气体二氧化氮（统称为氮氧化物）改变了大气中氮化合物的组成，并对人类呼吸系统造成直接和间接的严重损害。从废气排放中去除氮氧化物是一个紧迫的环境问题，也是工业催化研究的重要目标，这是一个对英国经济极其重要的领域。我们建议在生物和工业环境中研究氮氧化物的化学性质，在这些环境中，对如何控制气体的充分了解至关重要，但仍然缺乏。在这两种情况下，化学反应都是由过渡金属控制的：细胞色素c'蛋白通过与铁络合物结合而对其他双原子气体进行区分，从而进化出了对NO的非凡控制程度，而在沸石催化剂（微孔铝硅酸盐结构）中，通过在选择性催化还原（SCR）过程中添加氨，NOx气体可以在铜中心转化为更安全的副产物。然而，确切的机制目前还没有得到证实。我们将通过在高性能集群上进行的计算模拟来研究两种系统中二氧化氮和氮氧化物的化学性质。所得数据将用于模拟光谱特征，即电磁辐射（如光或x射线）如何与物质相互作用。这些结果将与两种体系的红外、拉曼、紫外可见和x射线吸收实验结果进行比较，以更好地了解化学反应所涉及的过程，这将为未来设计改进的沸石催化剂和生物工程蛋白提供信息。我们将使用量子力学/分子力学（QM/MM）建模来确定反应机理并计算两种体系的光谱特征。在这种方法中，沸石和蛋白质活性位点将使用高度精确但计算昂贵的量子力学理论水平来处理，嵌入在一个由有效的经典计算描述的环境中。新的QM/MM方法将实现，可以计算更大的QM区域和更精确的光谱特征，包括非谐波振动效应。重要的是，我们将计算模型与实验结果相结合的方法将普遍适用于复杂系统中的任何化学过程，包括其他工业催化剂和生物分子。

Nitrogen compounds play a crucial role in the earth's ecosystems, being continually converted from one form to another as they pass from the atmosphere to living organisms on land and in the sea. Nitric oxide gas (NO), for example, is a key intermediate in the global nitrogen cycle, and plays important roles in many processes in almost all forms of life, often acting as a signalling molecule. However, emissions of NO and the toxic gas nitrogen dioxide (collectively known as NOx) from heavy industry and motor vehicles alter the composition of nitrogen compounds in the atmosphere and are highly damaging both directly and indirectly to the human respiratory system. The removal of NOx from exhaust emissions is a pressing environmental concern and an important target for industrial catalysis research, an area of extreme importance to the UK economy.We propose to study the chemistry of nitrogen oxides in biological and industrial environments where a full understanding of how the gases are controlled is crucial but still lacking. In both cases the chemistry is controlled by transition metals: cytochrome c' proteins have evolved an extraordinary degree of control of NO through binding to an iron complex which discriminates against other diatomic gases, while in zeolite catalysts (microporous aluminosilicate structures) NOx gases can be converted into safer by-products at copper centres through the addition of ammonia in a process known as selective catalytic reduction (SCR). The precise mechanisms, however, are not currently proven.We will investigate the chemistry of nitrogen dioxide and nitrogen oxide in both systems by computational simulations performed on high performance clusters. The resulting data will be used to model spectroscopic signatures, i.e. how electromagnetic radiation (such as light or X-rays) interacts with matter. These will be compared with the results of infrared, Raman, UV-visible and X-ray absorption experiments on the two systems to better understand the processes involved in the chemical reactions, which will inform the future design of improved zeolite catalysts and bioengineered proteins.We will use quantum mechanical/molecular mechanical (QM/MM) modelling to identify the reaction mechanisms and calculate spectroscopic signatures of the two systems. In this approach the zeolite and protein active sites will be treated using a highly accurate, but computationally expensive, quantum mechanical level of theory, embedded in an environment described by an efficient classical calculation. New QM/MM methods will be implemented that can enable larger QM regions to be calculated and more accurate spectroscopic signatures including anharmonic vibrational effects. Importantly, our approach for combining computational modelling with experimental results will be generally applicable to any chemical processes in complex systems, including other industrial catalysts and biomolecules.