Complete thermodynamic description of alloys to extreme pressure and temperature

极端压力和温度下合金的完整热力学描述

• 批准号: 2739627
• 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: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2739627
• 关键词: Complete; thermodynamic; description; alloys; extreme

The aim of the proposed PhD is to develop a first-principles theoretical and computational scheme that provides a complete thermodynamic description of alloys from ambient to extreme conditions. This is in collaboration with the Atomic Weapons Establishment. We propose to develop a workflow that will be easily adaptable to arbitrary materials and require little human intervention. The scheme will deliver the required thermodynamic properties at a modest computational cost while retaining ab initio accuracy, with any uncertainties strictly quantified. In order to realise this requirement, we propose to include surrogate interatomic potential models for ab initio calculations in the workflow. This can be achieved in the form of using machine learning interatomic potentials (MLIP). After the generation, refinement and validation of such models, the calculation of free energies will follow, using thermodynamic integration and the nested sampling method [2,3], allowing the derivation of any equilibrium thermodynamic properties.In more detail, we propose the following workflow. For the ab initio calculations, we plan to use Density Functional Theory (DFT), as it has been established as a reliable, transferable and accurate first principles methodology to study metallic systems and alloys.1.Generation of a database of atomic configurations. MLIPs are typically fitted on a database of atomic configurations, which includes ab initio energetics, such as total energies, forces and stresses. When the stable phases of a material are known, these can be used to "bootstrap" the database, but in a general case, and especially at extreme conditions, these are not necessarily available in advance. Therefore, we propose to use the Ab Initio Random Structure Search (AIRSS) [4,5] method, which automatically generates stable and metastable crystalline polymorphs in an unbiased way at broad and tuneable range of pressure conditions.2.Fitting a MLIP. We propose to use the Gaussian Approximation Potential (GAP) framework, which has been shown to achieve first principles accuracy at a significantly lower computational cost. Using the generated database, a GAP model will be fitted and validated. It is anticipated that the database will need to be extended in an iterative, or "active learning" fashion, especially to provide an adequate coverage of high-temperature crystalline and disordered phases.3.Calculation of the temperature-pressure phase diagram. To obtain a general picture of phase stability at a broad range of temperature and pressures, we first propose to run a series of nested sampling (NS) calculations using the GAP model. NS has been shown to be able to automatically identify thermodynamically stable phases and generate phase diagrams. In order to refine the thermodynamic information obtained from NS, thermodynamic integration calculations will be performed using the Einstein crystal as the reference and GAP as the endpoint. It will be established if additional free energy perturbation calculations are required to achieve DFT accuracy. Thermodynamic properties such as the melting line, equation of state, latent heat, temperature-dependent elastic properties will be derived from the free-energies.

该博士学位的目的是开发第一原理理论和计算方案，提供从环境到极端条件下合金的完整热力学描述。这是与原子武器机构合作进行的。我们建议开发一个工作流程，将很容易适应任意材料，需要很少的人为干预。该方案将提供所需的热力学性质在一个温和的计算成本，同时保持从头算的准确性，与任何不确定性严格量化。为了实现这一要求，我们建议在工作流程中包括从头计算的代理原子间势模型。这可以通过使用机器学习原子间势（MLIP）的形式来实现。在生成、细化和验证这些模型之后，将使用热力学积分和嵌套采样方法[2，3]计算自由能，从而推导出任何平衡热力学性质。更详细地说，我们提出了以下工作流程。对于从头计算，我们计划使用密度泛函理论（DFT），因为它已经被建立为一个可靠的，可转移的和准确的第一性原理方法来研究金属系统和合金。1.生成原子构型的数据库。MLIP通常适合于原子构型的数据库，其中包括从头算能量学，例如总能量，力和应力。当材料的稳定相已知时，这些可以用于“引导”数据库，但在一般情况下，特别是在极端条件下，这些不一定提前可用。因此，我们建议使用从头算随机结构搜索（AIRSS）[4，5]方法，该方法可以在广泛和可调的压力条件范围内以无偏的方式自动生成稳定和亚稳的结晶多晶型物。2.拟合MLIP。我们建议使用高斯近似势（GAP）框架，该框架已被证明可以以显著较低的计算成本实现第一原理精度。使用生成的数据库，将拟合和验证GAP模型。预计该数据库将需要以迭代或“主动学习”的方式进行扩展，特别是为了提供高温结晶相和无序相的足够覆盖。3.温度-压力相图的计算。为了获得在宽的温度和压力范围内的相稳定性的一般图片，我们首先建议使用差距模型运行一系列嵌套采样（NS）计算。NS已被证明能够自动识别化学稳定相并生成相图。为了改进从NS获得的热力学信息，将使用爱因斯坦晶体作为参考和GAP作为终点来执行热力学积分计算。将确定是否需要额外的自由能微扰计算来实现DFT精度。热力学性质，如熔点线，状态方程，潜热，温度依赖的弹性性能将来自自由能。