点缺陷光电特性信息学软件栈：沥青项目
An Informatics Software Stack for Point Defect-Derived Opto-Electronic Properties: The Asphalt Project
摘要：
通过高通量筛选和机器学习方法对基于性能指标的材料发现进行计算加速正变得越来越普遍。然而，依赖于新材料中点缺陷的稀浓度的光电特性的开发和优化并没有从这些进展中显著受益。在这里，我们提出了一个信息学和模拟套件，以计算加速这些过程。这将使更快和更基础的材料研究成为可能，并减少与材料开发周期相关的成本和时间。类似于当前基于第一性原理的属性数据库所带来的新途径，这种类型的框架将随着其扩散而开辟全新的研究前沿。
英文摘要：
Computational acceleration of performance-metric-based materials discovery via high-throughput screening and machine learning methods is becoming widespread. Nevertheless, development and optimization of the opto-electronic properties that depend on dilute concentrations of point defects in new materials have not significantly benefited from these advances. Here, we present an informatics and simulation suite to computationally accelerate these processes. This will enable faster and more fundamental materials research, and reduce the cost and time associated with the materials development cycle. Analogous to the new avenues enabled by current first-principles-based property databases, this type of framework will open entire new research frontiers as it proliferates.
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