A Game of Order Parameters

秩序参数的游戏

• 批准号: 2214130
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2214130
• 关键词: Game; Order; Parameters

Brief description of the context of the research including potential impactPredicting if, how and when ice crystals will form in clouds (and our own cells!) is important to atmospheric science (and cryopreservation!) and the manufacture of pharmaceuticals. Preventing crystals from nucleating is desirable instead in our brains (where aggregates of proteins can lead to neurological diseases) and for the oil industry (where water-based crystals can block pipelines). Computer modelling can, in principle, design strategies for optimal control over these processes: in fact, advanced atomistic simulation techniques are now able to calculate key properties such as crystal nucleation rates. Unfortunately, the comparison of these rates against experimental data is subject to uncertainties yet to be rigorously quantified. Specifically, the choice of the particular mathematical object we use to identify atoms as part of a crystalline nucleus (the so-called "order parameter") has a major impact. We will use formal uncertainty quantification (which form part of the core HETSYS training) to rectify this, initially using simple models - for which accurate results are available, and then moving onto scenarios of great practical importance - such as the formation of ice. Aims and objectivesThis project seeks to establish what is the uncertainty associated with the choice of a particular order parameter when computing crystal nucleation rate by means of computer simulations. Aside from quantitative results, we also aim to develop a reliable methodology that will allow us to estimate said uncertainty in a robust and reproducible fashion, so as to provide the community with a reliable tool to make sense of computationally obtained nucleation rates. In addition, we intend to move from relatively simple model systems to realistic scenarios such as the heterogeneous formation of ice, which is a hotly debated issue with countless practical reverberations across fields as diverse as atmospheric science and cryopreservation.Novelty of the research methodologyComputing crystal nucleation rates is a challenging task for molecular simulations: as such, very little is known about the uncertainty related to these rates, and the field is presently lacking a robust approach tackle this pitfall. In this project we will leverage an extensive array of different order parameters to systematically investigate their effect on crystal nucleation rates. On top of relatively standard techniques (such as committor analysis) to probe the reliability of these order parameters, we will harness Bayesian inference to provide quantitative, unprecedented estimates of the error associated with the choice of a specific order parameter.Alignment to EPSRC's strategies and research areasThis project fits very well within Computational and Theoretical Chemistry and Surface Science EPSRC Areas. Given the far-reaching implications of this research in the context of ice nucleation and growth, we believe the project has the potential to make a concrete impact with respect to the Healthy Nation prosperity outcome highlighted in the EPSRC strategy for the physical sciences.Any companies or collaborators involvedThe project leverages an extensive network of collaboration, some of which directly involved with the recently awarded "Crystallization in the Real World" EPSRC Program Grant, encompassing several UK institutions; Leeds, Sheffield, UCL as well as Warwick. The supervisors can both boast a large network of existing collaborations directly connected to ice and crystallization, which are bound to maximise the impact of the proposed research.

预测冰晶是否、如何以及何时会在云（和我们自己的细胞！）中形成，对大气科学（和低温保存！）和药品制造非常重要。相反，防止晶体成核在我们的大脑（蛋白质聚集会导致神经系统疾病）和石油工业（水基晶体会堵塞管道）中是可取的。原则上，计算机建模可以设计出对这些过程进行最优控制的策略：事实上，先进的原子模拟技术现在能够计算出晶体成核速率等关键属性。不幸的是，这些速率与实验数据的比较受到不确定性的影响，但尚未严格量化。具体来说，我们用来识别作为晶核一部分的原子的特定数学对象的选择（所谓的“顺序参数”）具有重大影响。我们将使用正式的不确定性量化（这是核心HETSYS培训的一部分）来纠正这一点，首先使用简单的模型-可以获得准确的结果，然后转移到具有重要实际意义的场景-例如冰的形成。目的和目标本项目旨在通过计算机模拟计算晶体成核速率时，确定与选择特定顺序参数相关的不确定性。除了定量结果，我们还旨在开发一种可靠的方法，使我们能够以稳健和可重复的方式估计所述不确定性，从而为社区提供可靠的工具来理解计算获得的成核速率。此外，我们打算从相对简单的模型系统转向现实的场景，如冰的非均质形成，这是一个热议的问题，在大气科学和低温保存等不同领域有无数的实际反响。研究方法的新颖性计算晶体成核速率对于分子模拟来说是一项具有挑战性的任务：因此，对这些速率相关的不确定性知之甚少，并且该领域目前缺乏一种强大的方法来解决这个陷阱。在这个项目中，我们将利用一系列不同的有序参数来系统地研究它们对晶体成核速率的影响。在相对标准的技术（如提交者分析）的基础上，我们将利用贝叶斯推理来提供与选择特定顺序参数相关的错误的定量的、前所未有的估计。与EPSRC的战略和研究领域保持一致该项目非常适合EPSRC计算和理论化学和表面科学领域。鉴于这项研究在冰核和生长方面的深远影响，我们相信该项目有可能对EPSRC物理科学战略中强调的健康国家繁荣成果产生具体影响。该项目利用了广泛的合作网络，其中一些直接参与了最近获得的“现实世界中的结晶”EPSRC项目资助，包括几个英国机构；利兹，谢菲尔德，伦敦大学学院，还有沃里克。两位导师都拥有一个与冰和结晶直接相关的大型现有合作网络，这必然会最大化拟议研究的影响。