CDI Type II: New cyber-enabled strategies to realize the promise of quantum chemistry as a far-reaching tool for engineering applications

定量预测自然和工程系统将如何表现的能力是技术发展和进步的关键因素。这种预测是通过将计算机应用于感兴趣的系统的数学模型来开发的。所有这些系统都是由无数分子组成的材料组成的，但通常没有必要承认这一事实来进行有用的定量预测。然而，随着纳米技术的不断发展和复杂性，先进材料的发展，以及对极端应用的兴趣日益增长，认识到分子在产生物理行为中的潜在作用对于可靠和准确的预测是必不可少的。实现这一目标所需的原理在量子力学定律中已经得到了很好的确立，但是将这种理解转化为对宏观材料行为的预测的手段非常有限。计算机科学和工程的最新进展和趋势为纠正这种情况提供了机会。两个关键的发展是多核处理器和分布式计算的出现，除此之外，对数据驱动知识的关注。必须从头开始重新考虑计算密集型方法，以便真实的利用计算机科学的这些进步。如果不对基本的计算方法进行更根本和彻底的重新表述，新的计算技术的前景就不可能实现。该项目旨在为这些转变做出贡献。未来的发展为第一原理计算化学方法的实验验证开辟了新的途径（即，通过提供从第一原理到流体性质的路线，这项研究提供了一种跨大部分科学和工程的使能技术，同时通过新的网络方法将基础化学转化为应用。该项目的进展预计将直接影响化学工程，计算化学和计算机科学，并可能在纳米技术，材料科学和工程，地质学，能源，大气科学等领域产生广泛的次级影响，以及可以从预测和建模材料特性的能力中受益的无数领域。作为该项目的一部分，数据分析方案的开发可以以不可预见的方式扩展和应用于其他离散对象系统，这里开发的计算机编程工具旨在足够通用，以允许应用于远远超出激励这项工作的各种问题。此外，通过为高中生举办研讨会，并通过分发新的易于使用的开源软件，使其他人能够在自己的应用程序中应用这里开发的方法，促进教育和推广。这是一个网络启用的发现和创新计划奖，由化学部，多学科活动办公室，计算机信息科学理事会和化学，生物工程，环境和运输系统部共同资助。

The ability to predict quantitatively how natural and engineered systems will behave is a critical element to the growth and advancement of technology. Such predictions are developed through the application of computers to mathematical models of the system of interest. All such systems are made of materials that are ultimately composed of countless molecules, but often it is not necessary to acknowledge this fact to make useful quantitative predictions. However, with the continued growth and sophistication of nanotechnology, the development of advanced materials, and the growing interest in extremes of application, recognition of the underlying role of molecules in producing physical behavior is indispensable for reliable and accurate predictions. The principles required to achieve this are well established in the laws of quantum mechanics, but the means to convert this understanding into predictions about macroscopic material behaviors is quite limited. Recent advances and trends in computer science and engineering present opportunities to remedy this situation. Two key developments are the advent of multicore processors and distributed computing in general and, apart from this, a focus on data-driven knowledge. Computationally-intensive methods must be reconsidered from the ground up to make real use of these advances in computer science. The promise of new computing technologies is not likely to be met without a more fundamental and radical reformulation of the basic computational approach. This project aims to contribute to these transformations. Future developments open up new avenues for experimental validation of first-principles computational chemistry methods (i.e., requiring no input from experiment), improving them and thereby technologies where they can be applied.By supplying a route to fluid properties from first principles, this research provides an enabling technology across much of science and engineering while translating fundamental chemistry into applications via new cyber-approaches. Advances made in this project are expected to impact most directly chemical engineering, computational chemistry, and computer science, with a potentially broad array of secondary impacts in areas such as nanotechnology, materials science and engineering, geology, energy, atmospheric science and any other of the myriad fields that can benefit from the capability to predict and model material properties. The development of data-analysis schemes as part of this project can be extended and applied in unforeseen ways to other systems of discrete objects, and the computer-programming tools developed here aim to be sufficiently general to allow application to a diverse set of problems well beyond those that motivate this work. Additionally, education and outreach are promoted via a workshop for high-school students, and via distribution of new easy-to-use open-source software enabling others to apply the methods developed here in their own applications.This is a Cyber-Enabled Discovery and Innovation Program award and is co-funded by the Division of Chemistry, the Office of Multidisciplinary Activities, the Directorate of Computer & Information Science and the Division of Chemical, Bioengineering, Environmental, and Transport Systems.