High Temperature Electronic Structure with KKR

The AiiDA-KKR plugin and its application to high-throughput impurity embedding into a topological insulator

The ever increasing availability of supercomputing resources led computer-based materials science into a new era of high-throughput calculations. Recently, Pizzi et al. [Comp. Mat. Sci. 111, 218 (2016)] introduced the AiiDA framework that provides a way to automate calculations while allowing to store the full provenance of complex workflows in a database. We present the development of the AiiDA-KKR plugin that allows to perform a large number of ab initio impurity embedding calculations based on the relativistic full-potential Korringa-Kohn-Rostoker Green function method. The capabilities of …

Multiple Scattering Theory for Dense Plasmas

Dense plasmas occur in stars, giant planets and in inertial fusion experiments. Accurate modeling of the electronic structure of these plasmas allows for prediction of material properties that can in turn be used to simulate these astrophysical objects and terrestrial experiments. But modeling them remains a challenge. Here we explore the Korringa-Kohn-Rostoker Green's function (KKR-GF) method for this purpose. We find that it is able to predict equation of state in good agreement with other state of the art methods, where they are accurate and viable. In addition, it is shown that the computa…

akaitools: 用于解析和分析AkaiKKR电子结构计算的Python包

akaitools: A Python package for parsing and analyzing AkaiKKR electronic structure calculations

针对AkaiKKR输出无结构化的问题，开发Python包akaitools，解析SCF、态密度和Bloch谱函数为类型注解的NumPy对象，支持单位转换、Pandas导出和绘图，并提供命令行接口与输入文件生成器。

Temperature dependence of electronic heat capacity in Holstein model

The dynamics of charge migration was modeled to calculate temperature dependencies of its thermodynamic equilibrium values such as energy and electronic heat capacity in homogeneous adenine fragments. The energy varies from nearly polaron one at T~0 to midpoint of the conductivity band at high temperatures. The peak on the graph of electronic heat capacity is observed at the polaron decay temperature.

机器学习跨温度条件下物质的电子结构

Machine learning the electronic structure of matter across temperatures

本文提出基于神经网络并由 DFT 数据训练的模型，通过直接预测 LDOS 并分别处理电子与离子温度，实现宽温域材料电子结构及相关能量效应的准确预测。

高压下铁的电子温度驱动相稳定性与结构演化

Electronic Temperature-Driven Phase Stability and Structural Evolution of Iron at High Pressure

本文通过有限温度密度泛函理论计算铁的吉布斯自由能相图，揭示高压下由电子温度驱动的hcp到bcc相变，并解释了200 GPa以上bcc相稳定性的实验观测。