Phase-Space Natural Orbital Functional Theory

计算化学已经成为预测、证实和解释实验结果的重要工具，不仅在化学的所有领域，而且在分子生物学和纳米技术等领域。高质量、数学上严格且计算上昂贵的计算在实验测量的误差内提供化学性质，但目前对于大型系统是不可行的。 因此，当研究系统，如蛋白质，材料表面，或整体性质的分子系综（如。由于密度泛函理论（DFT）的精确性和高效性，目前用于大分子体系计算研究的近似方法是密度泛函理论。 不幸的是，DFT无法正确描述键的断裂或形成，以及一般的过渡金属和激发态，这些现象是理解化学的关键。 最近的研究表明，许多DFT故障的基础是静态相关。 本文提出了一种基于自然轨道泛函理论（NOFT）的计算化学方法。NOFT的一个关键特征是电子分数占据自然轨道，有效地处理了DFT遇到的静态相关问题。 我们将利用DFT的成功概念，在NOFT框架内，设计一个通用的和准确的自然轨道泛函。我们将联合收割机结合我们的功能与最新的理论进展计算大型系统，创造一个计算化学方法，能够提供实验精度的大型和复杂的分子系统的结果。 这种方法的发展将使计算和实验研究人员能够可靠地确定分子结构，反应途径和当前计算方法不适合的系统的其他感兴趣的性质。

Computational chemistry has become an important tool for predicting, confirming, and explaining experimental results in not only all fields of chemistry, but in areas such as molecular biology and nanotechnology. High quality, mathematically rigorous, and computationally expensive calculations provide chemical properties within the errors of experimental measurements, but are currently unfeasible for large systems. Therefore when studying systems such as proteins, surfaces of materials, or bulk properties of molecular ensembles (eg. compounds dissolved in water), it is necessary to employ more approximate computational chemistry methods.The current approximate method of choice for the computational study of large molecular systems is density functional theory (DFT), due to its combination of accuracy and efficiency. Unfortunately, DFT is unable to properly describe bond breaking or formation, as well as transition metals and excited states in general, phenomena that are key to understanding chemistry. Recent research has revealed that the basis of many DFT failures is static correlation. I propose to develop a new computational chemistry method based on natural orbital functional theory (NOFT). A key feature of NOFT is the occupation of the natural orbitals by fractions of electrons which effectively treats the static correlation problem encountered by DFT. We will make use of the successful concepts of DFT, within an NOFT framework, to design a universal and accurate natural orbital functional. We will combine our functional with the latest theoretical advances for calculations on large systems to create a computational chemistry method capable of providing results within experimental accuracy for large and complex molecular systems. The development of such a method will allow computational and experimental researchers to reliably determine molecular structures, reaction pathways, and other properties of interest of systems for which current computational methods are unsuitable.