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.

拟议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。这是与原子武器研究所合作的。我们建议开发一种工作流程，可以轻松适应任意材料并且几乎不需要人工干预。该方案将以适度的计算成本提供所需的热力学性质，同时保留从头计算的准确性，并严格量化任何不确定性。为了实现这一要求，我们建议在工作流程中包含用于从头计算的替代原子间势模型。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、完善和验证此类模型后，将使用热力学积分和嵌套采样方法 [2,3] 计算自由能，从而推导任何平衡热力学性质。更详细地说，我们提出以下建议工作流程。对于从头计算，我们计划使用密度泛函理论（DFT），因为它已被确立为研究金属系统和合金的可靠、可转移和准确的第一原理方法。1.生成原子构型数据库。 MLIP 通常安装在原子构型数据库上，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，这些不一定可以提前获得。因此，我们建议使用从头算随机结构搜索（AIRSS）[4,5]方法，该方法在广泛且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定的晶体多晶型物。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着较低的计算成本实现第一原理的准确性。使用生成的数据库，将拟合并验证 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。为了获得大范围温度和压力下相稳定性的总体情况，我们首先建议使用 GAP 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热力学稳定相并生成相图。为了精炼从 NS 获得的热力学信息，将使用爱因斯坦晶体作为参考、GAP 作为终点进行热力学积分计算。将确定是否需要额外的自由能扰动计算来实现 DFT 精度。热力学性质，如熔线、状态方程、潜热、温度相关的弹性性质将从自由能中导出。