Enhanced high harmonic efficiency through phonon-assisted photodoping effect

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Jin Zhang, Ofer Neufeld, Nicolas Tancogne-Dejean, I-Te Lu, Hannes Hübener, Umberto De Giovannini, Angel Rubio
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Abstract

High-harmonic generation (HHG) has emerged as a central technique in attosecond science and strong-field physics, providing a tool for investigating ultrafast dynamics. However, the microscopic mechanism of HHG in solids is still under debate, and it is unclear how it is modified in the ubiquitous presence of phonons. Here we theoretically investigate the role of collectively coherent vibrations in HHG in a wide range of solids (e.g., hBN, graphite, 2H-MoS2, and diamond). We predict that phonon-assisted high harmonic yields can be significantly enhanced, compared to the phonon-free case – up to a factor of ~20 for a transverse optical phonon in bulk hBN. We also show that the emitted harmonics strongly depend on the character of the pumped vibrational modes. Through state-of-the-art ab initio calculations, we elucidate the physical origin of the HHG yield enhancement – phonon-assisted photoinduced carrier doping, which plays a paramount role in both intraband and interband electron dynamics. Our research illuminates a clear pathway toward comprehending phonon-mediated nonlinear optical processes within materials, offering a powerful tool to deliberately engineer and govern solid-state high harmonics.

Abstract Image

通过声子辅助光掺杂效应提高高次谐波效率
高次谐波发生(HHG)已成为阿秒科学和强场物理学的核心技术,为研究超快动力学提供了一种工具。然而,高次谐波发生在固体中的微观机制仍在争论之中,目前还不清楚它是如何在声子无处不在的情况下发生改变的。在此,我们从理论上研究了各种固体(如氢化硼、石墨、2H-MoS2 和金刚石)中集体相干振动在 HHG 中的作用。我们预测,与无声子的情况相比,声子辅助的高次谐波产率会显著提高--对于块状氢化硼中的横向光学声子而言,可提高约 20 倍。我们还表明,发射的谐波与泵浦振动模式的特性密切相关。通过最先进的 ab initio 计算,我们阐明了 HHG 产率增强的物理来源--声子辅助光诱导载流子掺杂,它在带内和带间电子动力学中发挥着至关重要的作用。我们的研究为理解材料内部声子介导的非线性光学过程指明了一条清晰的道路,为有意设计和治理固态高次谐波提供了强有力的工具。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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