论文标题
从头静脉冻结 - phonon方法的电子音波耦合强度
Electron-phonon coupling strength from ab initio frozen-phonon approach
论文作者
论文摘要
我们提出了一种快速筛查潜在超导材料的快速方法。该方法基于计算区域中心声子模式的金属筛选,该筛选为电子 - 音波耦合强度提供了准确的估计。该方法与最近提出的刚性松饼锡(RMT)方法互补,该方法等于在整个Brillouin区域(与区域中心相反)中整合了电子偶联,但相对较低。我们通过将其应用于MGB $ _ \ text {2} $来说明使用此方法的使用,其中已知高温超导性主要由区域中心模式驱动,并将其与姐妹化合物Alb $ _ \ $ _ \ text {2} $进行比较。我们通过筛选大量二进制氢化物来进一步说明该描述符的用法,该二进制氢化物的准确计算是对电子 - phonon耦合的准确计算。与RMT描述符一起,此方法开辟了一种通过机器学习或数据挖掘来搜索常规超导体的初始高通量筛选的方法。
We propose a fast method for high-throughput screening of potential superconducting materials. The method is based on calculating metallic screening of zone-center phonon modes, which provides an accurate estimate for the electron-phonon coupling strength. This method is complementary to the recently proposed Rigid Muffin Tin (RMT) method, which amounts to integrating the electron-phonon coupling over the entire Brillouin zone (as opposed to the zone center), but in a relatively inferior approximation. We illustrate the use of this method by applying it to MgB$_\text{2}$, where the high-temperature superconductivity is known to be driven largely by the zone-center modes, and compare it to a sister compound AlB$_\text{2}$. We further illustrate the usage of this descriptor by screening a large number of binary hydrides, for which accurate first-principle calculations of electron-phonon coupling have been recently published. Together with the RMT descriptor, this method opens a way to perform initial high-throughput screening in search of conventional superconductors via machine learning or data mining.