Enhancing material efficiencies for catalysis and fuel cell applications via disorder engineering

尽管国际能源署预测，可再生能源在未来几十年将会增长，但能源生产产生的碳排放量将从100亿吨增加到2040年的360亿吨，这主要是受石油和天然气使用量增长的推动。为了在能源密集型工艺和应用中实现节能，具有更多功能的新型材料可以发挥重要作用。因此，为了实现全球可持续能源目标，我们需要研究创造力、思维突破和能够加快材料创新进程的先进工具。 计算材料研究领域为这样一个平台提供了先进的工具，能够取代耗时和昂贵的实验，并提供了从纳米到电子天平对材料和化学过程前所未有的理解。尽管如此，几十年来，计算材料的研究主要集中在原子有序排列的晶体材料上。然而，在现实中，晶体的完美并不存在于材料中。材料中总是存在结构缺陷，无论是小到点缺陷--只影响一小部分晶体材料，基本保持其固有性质不变，还是像非晶态材料一样严重--导致材料具有与其晶体对应物相比全新的性质。预测无序材料的性质是计算研究的一个具有挑战性的领域。然而，如果真实材料中存在的不可避免的无序能够被理解并以有利于我们的方式利用，它就可以解决当今世界最令人畏惧的问题，如气候变化。 在接下来的几年里，申请者将努力建立这样一个平台，其中将专门为催化和燃料电池应用设计负担得起的高效材料。通过使用尖端的计算技术，并通过超越材料科学、物理和化学的传统界限，申请者将 (A)开发现实的计算模型，以预测低成本无序材料的结构和电子性质； (B)开发一个高保真多尺度框架，将这些材料在不同长度、尺度和操作条件下的物理联系起来；以及 (C)提供优化设计原则和对无序材料的更深入了解，从而为使用廉价和丰富的材料进行可持续能源应用提供新的方向。 除了使先进能源材料的发现和开发过程更快、更便宜、更可预测外，申请者的研究还将有助于独特的计算可持续发展人才库的增长，同时积极为申请者的研究计划做出贡献，使加拿大在可持续能源研究领域处于国际领先地位。

Despite the forecast of the International Energy Agency that the renewable energy will grow in the coming decades, the carbon emissions from energy production are set to rise from 10 to 36 gigatonnes in 2040, mostly driven by growth in oil and gas use. To enable energy savings in energy-intensive processes and applications, novel materials with increased functionality can play a major role. Thus, in order to achieve global sustainable energy targets, we need research creativity, breakthrough in thinking, and advanced tools that can expedite the process of material innovation. The area of Computational Materials Research' provides such a platform with advanced tools capable of replacing the time-consuming and expensive experiments, and providing an unprecedented understanding of materials and chemical processes from nano- to electronic- scales. That being said for decades, computational materials research is mostly focused on crystalline materials having ordered arrangement of atoms. In reality, however, crystalline perfection does not exist in materials. There always exist structural faults in materials whether as small as point defects- which affect only a small portion of crystalline materials keeping its intrinsic properties mostly intact, or as severe as in amorphous materials- which result in materials having entirely new properties as compared to their crystalline counterparts. Predicting the properties of disordered materials is a challenging area of computational research. However, if the inevitable disorder present in the real materials can be understood and utilized in our favor, it can solve the most daunting problems, such as climate change, of today's world. In the coming years, the applicant endeavors to establish such a platform, where affordable and efficient materials will be designed, specifically, for catalysis and fuel cell applications. By using the leading-edge computational techniques and by transcending the traditional borders of materials science, physics, and chemistry, the applicant will (a) develop the realistic computational models to predict the structural, and electronic properties of the low-cost disordered materials; (b) develop a high fidelity multi-scale framework to connect the physics of these materials at different length scales and operating conditions; and (c) provide the optimized design principles and deeper understanding of the disordered materials, resulting in new directions to use inexpensive and abundant materials for sustainable energy applications. In addition to making the process of discovery and development of advanced energy materials faster, less expensive, and more predictable, the applicant's research will contribute to the growth of unique computational sustainability' talent pool which, along with actively contributing to the applicant's research program, will project Canada towards the international leadership in the field of sustainable energy research.