论文标题

钡超水的高压合成:伪观bah12

High-Pressure Synthesis of Barium Superhydrides: Pseudocubic BaH12

论文作者

Chen, Wuhao, Semenok, Dmitrii V., Kvashnin, Alexander G., Kruglov, Ivan A., Galasso, Michele, Song, Hao, Huang, Xiaoli, Duan, Defang, Goncharov, Alexander F., Prakapenka, Vitali B., Oganov, Artem R., Cui, Tian

论文摘要

在LA-H系统中发现了高温超导性之后,在最近发现的FCC-LAH10中,获得了记录的临界温度TC = 250 K [Drozdov等,Nature,569,528(2019)和Somayazulu等人,物理。莱特牧师。 122,027001(2019)],我们研究了高达173 GPA的压力下钡液系统中新化合物的形成。我们使用NH3BH3的原位产生氢,我们将先前未知的超氢BAH12与假副观(FCC)BA sublattice合成,在四个独立实验中,在75至173 GPA的范围内观察到,这是在四个独立实验中观察到的。 DFT计算表示状态的理论和实验方程之间的一致性。除BAH12外,我们还确定了先前已知的P6/MMM BAH2,可能是BAH10和BAH6是样品中的杂质。从头开始计算表明,新发现的半金属BAH12包含H2,H3分子单元和分离的H12链。十二烷基氢化钡是一种具有金属电导率的独特分子氢化物,在140 GPA时表现出与计算(19-32 K)一致的20 K约20 k的超导过渡。由于开发了新的Python脚本,可以解释多相XRD数据,以便在进化搜索的结果后进行后处理。这些脚本有助于快速识别以最佳方式解释实验数据的理论结构。

Following the discovery of high-temperature superconductivity in the La-H system, where for the recently discovered fcc-LaH10 a record critical temperature Tc = 250 K was achieved [Drozdov et al., Nature, 569, 528 (2019) and Somayazulu et al., Phys. Rev. Lett. 122, 027001 (2019)], we studied the formation of new chemical compounds in the barium-hydrogen system at pressures up to 173 GPa. Using in situ generation of hydrogen from NH3BH3, we synthesized previously unknown superhydride BaH12 with a pseudocubic (fcc) Ba sublattice, which was observed in a wide range of pressures from 75 to 173 GPa in four independent experiments. DFT calculations indicate a close agreement between the theoretical and experimental equations of state. In addition to BaH12, we identified previously known P6/mmm BaH2 and possibly BaH10 and BaH6 as impurities in the samples. Ab initio calculations show that newly discovered semimetallic BaH12 contains H2, H3 molecular units and detached H12 chains. Barium dodecahydride is a unique molecular hydride with metallic conductivity which demonstrates a superconducting transition around 20 K at 140 GPa in agreement with calculations (19-32 K). The interpretation of the multiphase XRD data was possible thanks to the development of new Python scripts for postprocessing the results of evolutionary searches. These scripts help quickly identify the theoretical structures that explain the experimental data in the best way, among thousands of candidates.

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