Multiscale modeling of (bio)catalytic systems

（生物）催化系统的多尺度建模

• 批准号: RGPIN-2019-03976
• 负责人: Salahub, Dennis
• 金额: $ 3.5万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=748076
• 关键词: Multiscale; modeling; bio; catalytic; systems

The modeling of complex systems in chemistry, physics, biology, materials science and related interdisciplines has taken great strides in recent years. In the areas of interest to this proposal, advances in quantum chemistry, in molecular mechanics and molecular dynamics, in statistical and stochastic methodologies, in the treatment of kinetic networks and in machine learning are merging. And an embryonic systems approach is emerging. Some of the most interesting frontier work is interdisciplinary and integrative in nature and requires theories and methodologies that span large ranges on spatial and temporal scales. The long-term goal of my research program is to contribute to the development of such multi-scale modeling methodologies, to their implementation in efficient computer codes, and their application to catalytically-driven processes in complex biological and energy-related environments. Success would lead to better understanding of biological systems, of how biochemical reactions are coupled to larger scale properties of cellular components and of how they work together. The methods can also be used to understand petroleum chemistry under realistic conditions, such as those in heavy oil deposits or in the oil sands. New ultradispersed catalysts will be designed by a combined computational-experimental approach so that some of the important chemistry can be done underground, with less impact on the environment. The proposed research will extend the capabilities of modeling methodologies and associated software in the area of complex catalytic systems. Our efforts will be guided by the belief that the most promising opportunities will involve an interdisciplinary, integrative, modular, multi-scale and multi-technique approach, in the spirit of systems science. Success will lead to a far more powerful suite of multiscale modeling methodologies and software, ready to address ever more realistic questions from the natural world and from industry.

近年来，在化学、物理、生物、材料科学和相关交叉学科中，复杂系统的建模取得了长足的进步。在这一建议感兴趣的领域，量子化学、分子力学和分子动力学、统计和随机方法学、动力学网络处理和机器学习方面的进展正在融合。一种萌芽的系统方法正在出现。一些最有趣的前沿工作本质上是跨学科和综合性的，需要在空间和时间尺度上跨越大范围的理论和方法。我的研究计划的长期目标是促进这种多尺度建模方法的发展，在有效的计算机代码中实现它们，并将其应用于复杂生物和能源相关环境中的催化驱动过程。成功将导致更好地理解生物系统，生物化学反应如何与细胞成分的更大规模特性相结合，以及它们如何协同工作。 这些方法也可用于了解实际条件下的石油化学，例如重油矿床或油砂中的石油化学。新的超分散催化剂将通过计算-实验相结合的方法设计，以便一些重要的化学反应可以在地下进行，对环境的影响较小。拟议的研究将扩展复杂催化系统领域的建模方法和相关软件的能力。我们的努力将以这样一种信念为指导，即最有希望的机会将涉及本着系统科学的精神采取跨学科、综合、模块化、多规模和多技术的方法。成功将带来一套更强大的多尺度建模方法和软件，准备好解决来自自然世界和工业的更现实的问题。