标题： 通过机器学习编码的原子位点信息高效绘制混合空位有序钙钛矿的空间 显示英文标题

标题： Efficiently charting the space of mixed vacancy-ordered perovskites by machine-learning encoded atomic-site information

摘要： 空位有序双钙钛矿（VODPs）是用于光电和光伏应用的三维铅卤化物钙钛矿的有前途的替代品。 混合这些材料会创建一个广阔的成分空间，使得电子和光学性质高度可调。 然而，广泛的化学环境给高效筛选具有目标特性的候选材料带来了重大挑战。 在本研究中，我们展示了混合VODPs中电子和光学特性的多样性以及非线性混合效应对电子结构的影响。 对于局部环境选择有限的混合系统，原子位点占据的信息原则上决定了结构构型和所有基本性质。 基于这一概念，我们开发了一个模型，该模型结合了数据增强方案和受变压器启发的图神经网络（GNN），能够从混合系统中编码原子位点信息。 这种方法使我们能够准确预测测试样品的带隙和形成能，分别达到21 meV和3.9 meV/原子的均方根误差（RMSE）。 使用包含（最多）三元混合系统和少于72个原子的超晶胞的数据集进行训练，我们的模型可以推广到中等和高熵混合VODPs（含4至6种主要混合元素）以及包含超过200个原子的大超晶胞。 此外，我们的模型成功再现了锡基混合VODPs中实验观察到的带隙弯曲，并揭示了一种非常规的混合效应，可能导致比原始系统中发现的带隙更小。 显示英文摘要

摘要： Vacancy-ordered double perovskites (VODPs) are promising alternatives to three-dimensional lead halide perovskites for optoelectronic and photovoltaic applications. Mixing these materials creates a vast compositional space, allowing for highly tunable electronic and optical properties. However, the extensive chemical landscape poses significant challenges in efficiently screening candidates with target properties. In this study, we illustrate the diversity of electronic and optical characteristics as well as the nonlinear mixing effects on electronic structures within mixed VODPs. For mixed systems with limited local environment options, the information regarding atomic-site occupation in-principle determines both structural configurations and all essential properties. Building upon this concept, we have developed a model that integrates a data-augmentation scheme with a transformer-inspired graph neural network (GNN), which encodes atomic-site information from mixed systems. This approach enables us to accurately predict band gaps and formation energies for test samples, achieving Root Mean Square Errors (RMSE) of 21 meV and 3.9 meV/atom, respectively. Trained with datasets that include (up to) ternary mixed systems and supercells with less than 72 atoms, our model can be generalized to medium- and high-entropy mixed VODPs (with 4 to 6 principal mixing elements) and large supercells containing more than 200 atoms. Furthermore, our model successfully reproduces experimentally observed bandgap bowing in Sn-based mixed VODPs and reveals an unconventional mixing effect that can result in smaller band gaps compared to those found in pristine systems.