Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W
Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W
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DOI：
10.1103/physrevmaterials.5.103803
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发表时间：
2021-10-21
影响因子：
3.4
通讯作者：
Marinica, Mihai-Cosmin
中科院分区：
文献类型：
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作者：
Goryaeva, Alexandra M.;Deres, Julien;Marinica, Mihai-Cosmin
数据驱动或机器学习(ML)方法已经成为构建原子间势的半经验方法的可行替代方法，因为如果仔细选择原子结构的训练数据库和描述符表示，它们能够准确地从第一性原理模拟中内插和外推。在这里，我们提出了高精度的原子间相互作用势，适用于研究体心立方铁和钨中的位错、点缺陷和它们的团簇，由描述符空间的线性或二次输入输出映射构成。所提出的二次形式，称为二次噪声ML，不同于以往的方法，它是由线性解强烈地预条件的。所开发的势与现有的广泛的ML势和半经验势进行了比较，并被证明具有足够的精度来区分基础参考数据中交换相关泛函或赝势的变化，同时保持良好的可转移性。基本方法的灵活性能够针对传统方法几乎无法获得的性质，例如W中的负双空位结合能或这两种金属中1/2<；111>；螺型位错的Peierls势垒的形状和大小。我们还展示了如何使用所开发的势来针对需要用第一原理方法无法达到的大时空尺度的重要可观测对象，尽管我们强调了深思熟虑的数据库设计和描述符空间的非线性程度的重要性，以实现信息的适当传递到大规模计算。作为演示，我们对Fe中1/2<；111>；位错环和三维C15团簇的相对稳定性进行了直接的原子计算，发现这两类间隙缺陷的形成能在大约40个自间隙原子处发生交叉。我们还计算了Fe和W中1/2<；111>；螺旋位错的扭结对形成能，发现与间接测量这些量的密度泛函理论提供的线张力模型符合得很好。最后，我们利用优良的有限温度性质计算了热振动中具有完全非谐性的空位形成自由能。因此，提出的势能为系统地研究缺陷的自由能图景开辟了许多途径，并具有从头算的准确性。
Data-driven, or machine learning (ML), approaches have become viable alternatives to semiempirical methods to construct interatomic potentials, due to their capacity to accurately interpolate and extrapolate from first-principles simulations if the training database and descriptor representation of atomic structures are carefully chosen. Here, we present highly accurate interatomic potentials suitable for the study of dislocations, point defects, and their clusters in bcc iron and tungsten, constructed using a linear or quadratic input-output mapping from descriptor space. The proposed quadratic formulation, called quadratic noise ML, differs from previous approaches, being strongly preconditioned by the linear solution. The developed potentials are compared to a wide range of existing ML and semiempirical potentials, and are shown to have sufficient accuracy to distinguish changes in the exchange-correlation functional or pseudopotential in the underlying reference data, while retaining excellent transferability. The flexibility of the underlying approach is able to target properties almost unattainable by traditional methods, such as the negative divacancy binding energy in W or the shape and the magnitude of the Peierls barrier of the 1/2 < 111 > screw dislocation in both metals. We also show how the developed potentials can be used to target important observables that require large time-and-space scales unattainable with first-principles methods, though we emphasize the importance of thoughtful database design and degrees of nonlinearity of the descriptor space to achieve the appropriate passage of information to large-scale calculations. As a demonstration, we perform direct atomistic calculations of the relative stability of 1/2 < 111 > dislocations loops and three-dimensional C15 clusters in Fe and find the crossover between the formation energies of the two classes of interstitial defects occurs at around 40 self-interstitial atoms. We also compute the kink-pair formation energy of the 1/2 < 111 > screw dislocation in Fe and W, finding good agreement with density functional theory informed line tension models that indirectly measure those quantities. Finally, we exploit the excellent finite-temperature properties to compute vacancy formation free energies with full anharmonicity in thermal vibrations. The presented potentials thus open up many avenues for systematic investigation of free-energy landscape of defects with ab initio accuracy.