SusChem: High-throughput Computational Discovery of New Nanoporous Materials for Energy Storage

SusChem：用于储能的新型纳米多孔材料的高通量计算发现

• 批准号: 1308799
• 负责人: Randall Snurr
• 金额: $ 27.29万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1308799&HistoricalAwards=false
• 关键词: SusChem; throughput; Computational; Discovery; New

Technical AbstractThe development of new nanoporous materials is critical for many problems related to energy and sustainability. New catalysts, new gas storage media, and new sorbents for separations are all urgently sought. In the transportation sector, there is a significant effort by the major automakers to develop hydrogen-powered fuel cells as a long-term alternative to internal combustion engines, which burn fossil fuels. One of the biggest hurdles for hydrogen-powered vehicles is the challenge of storing enough hydrogen on the vehicle within the constraints of weight, volume, and safety. The solution to this storage problem will require the development of new storage materials.The objectives of this project are to1. Develop a high-throughput computational screening approach for the development of nanoporous materials for various applications, using gas storage as a particular example.2. Demonstrate how this computational approach, when used in close interaction with experiment, can vastly accelerate the discovery of new and useful materials.3. Discover new sorbents that can store hydrogen for mobile applications.The project will focus on metal-organic frameworks (MOFs). These nanoporous materials are synthesized in a building-block approach from metal nodes and organic linkers. The building-block approach to MOF synthesis opens up the possibility to synthesize an almost unlimited number of materials. This clearly creates exciting possibilities, but it also creates the following challenge: how does one identify the most promising structures, among the millions of possibilities, for a particular application? In this project, we will generate millions of MOFs on the computer and test their properties for gas storage applications. These computational methods can be extended in a straightforward manner to other applications, and the materials discovered may find uses in a variety of other applications, including catalysis and separation of gas mixtures. A related problem is how to extract insight and understanding from the resulting deluge of information. Powerful data mining strategies, developed in other fields, will be harnessed and tested for this task.In the long term, hydrogen produced from clean energy sources such as wind or solar may play an important role as a green energy carrier in a variety of scenarios. If hydrogen can be used for transportation, it would lead to a reduction in U.S. petroleum imports and have a significant impact on the economy, the environment, national energy security, and sustainability. However, hydrogen storage is widely regarded as the most difficult problem preventing the development of hydrogen-powered vehicles. Beyond gas storage, the materials developed in this work - particularly those with highly coordinatively unsaturated metal sites - may be valuable in applications such as separations and catalysis. The computational methods can also be applied to other problems. In addition, a searchable database of millions of hypothetical MOFs discovered in this project will be made publicly available, so that other researchers may search and analyze it to discover materials for other problems. Graduate students, undergraduates, and high school teachers will be educated in a highly interdisciplinary research environment. Web-based education and outreach activities (developed with the high school teachers) will reach a wider audience.Non-Technical SummaryHydrogen-powered vehicles could be a significant advance toward more sustainable transportation. Hydrogen produced by solar, wind, or other green energy sources is an attractive fuel because its only by-product when burned is water. There is a significant effort by the major automakers to develop hydrogen-powered fuel cells as a long-term alternative to internal combustion engines, which burn fossil fuels. Because hydrogen is a gas, one of the biggest hurdles for hydrogen-powered vehicles is the challenge of storing enough hydrogen on the vehicle within the constraints of weight, volume, and safety. The solution to this storage problem will require the development of new storage materials. The objectives of this project are to1. Develop a high-throughput computational screening approach for the development of nanoporous materials for various applications, using hydrogen storage as a particular example.2. Demonstrate how this computational approach, when used in close interaction with experiment, can vastly accelerate the discovery of new and useful materials.3. Discover new porous materials that can store hydrogen for mobile applications.The project will focus on a new class of materials known as metal-organic frameworks (MOFs). These materials have incredibly high internal surface area and are promising for gas storage. The project will develop and use advanced computational methods to discover new MOFs for hydrogen storage. The computational methods can also be applied to other problems in the future. In addition, a searchable database of millions of hypothetical MOFs discovered in this project will be made publicly available, so that other researchers may search and analyze it to discover materials for other problems. Graduate students, undergraduates, and high school teachers will be educated in a highly interdisciplinary research environment. Web-based education and outreach activities will reach a wider audience.

技术摘要新型纳米多孔材料的开发对于解决与能源和可持续性相关的许多问题至关重要。 新的催化剂、新的气体储存介质和新的分离吸附剂都是迫切需要的。 在运输部门，主要汽车制造商正在大力开发氢动力燃料电池，作为燃烧化石燃料的内燃机的长期替代品。 氢动力汽车的最大障碍之一是在重量，体积和安全性的限制下在车辆上储存足够的氢。 要解决这一储存问题，就需要开发新的储存材料。开发一种高通量的计算筛选方法，用于开发各种应用的纳米多孔材料，使用气体存储作为一个特定的例子。演示这种计算方法如何在与实验密切互动时，可以大大加速新的有用材料的发现。发现可用于移动的应用的新型储氢吸附剂。该项目将侧重于金属有机框架（MOFs）。 这些纳米多孔材料是由金属节点和有机连接体以积木方式合成的。 MOF合成的构建块方法开辟了合成几乎无限数量的材料的可能性。 这显然创造了令人兴奋的可能性，但也带来了以下挑战：如何在数百万种可能性中识别出最有前途的结构，用于特定应用？ 在这个项目中，我们将在计算机上生成数百万个MOFs，并测试它们在气体存储应用中的性能。 这些计算方法可以直接扩展到其他应用，所发现的材料可以在各种其他应用中找到用途，包括催化和气体混合物的分离。 一个相关的问题是如何从由此产生的信息洪流中提取洞察力和理解力。 在其他领域开发的强大的数据挖掘策略将被利用并测试用于这一任务。从长远来看，从风能或太阳能等清洁能源生产的氢气可能在各种场景中作为绿色能源载体发挥重要作用。 如果氢可以用于运输，将导致美国石油进口减少，并对经济，环境，国家能源安全和可持续性产生重大影响。 然而，氢储存被广泛认为是阻碍氢动力汽车发展的最大难题。 除了气体储存，这项工作中开发的材料-特别是那些具有高度配位不饱和金属位点的材料-可能在分离和催化等应用中有价值。 计算方法也可应用于其它问题。 此外，该项目中发现的数百万个假设MOFs的可搜索数据库将公开提供，以便其他研究人员可以搜索和分析它，以发现其他问题的材料。 研究生，本科生和高中教师将在一个高度跨学科的研究环境中接受教育。 基于网络的教育和推广活动（与高中教师一起开发）将覆盖更广泛的受众。非技术摘要氢动力车辆可能是迈向更可持续交通的重大进步。 由太阳能、风能或其他绿色能源产生的氢是一种有吸引力的燃料，因为其燃烧时唯一的副产品是水。 主要汽车制造商正在努力开发氢动力燃料电池，作为燃烧化石燃料的内燃机的长期替代品。 由于氢是一种气体，氢动力汽车的最大障碍之一是在重量，体积和安全性的限制下在车辆上储存足够的氢。 解决这一储存问题需要开发新的储存材料。 这个项目的目标是1。开发一种高通量的计算筛选方法，用于开发各种应用的纳米多孔材料，以储氢为例。演示这种计算方法如何在与实验密切互动时，可以大大加速新的有用材料的发现。发现可用于移动的应用的新型多孔材料。该项目将重点关注一类称为金属有机框架（MOFs）的新材料。 这些材料具有令人难以置信的高内表面积，并且有希望用于气体储存。 该项目将开发和使用先进的计算方法来发现用于储氢的新MOF。 该计算方法也可应用于其它问题。 此外，该项目中发现的数百万个假设MOFs的可搜索数据库将公开提供，以便其他研究人员可以搜索和分析它，以发现其他问题的材料。 研究生，本科生和高中教师将在一个高度跨学科的研究环境中接受教育。 网络教育和外联活动将覆盖更广泛的受众。