arXiv subjects

Zhongzhen Luo

Publications and source records attributed to Zhongzhen Luo.

4 recordsLinked to original sources

arXiv2026

Photoinduced phase heterogeneity and charge localization in SnSe

Time-resolved multi-terahertz (THz) spectroscopy is used to observe pump fluence-dependent dynamics in the optical conductivity of photoexcited tin selenide (SnSe) over an ultrabroadband spectral range of 0.5 - 11 THz at fluences from 0.1 - 7.5 mJ/cm$^2$. A free carrier Drude spectrum is observed at pump fluences below 3 mJ/cm$^2$, with optical phonons well described by the equilibrium Pnma structural phase. With increasing fluence, a suppression of the DC photoconductivity is observed, indicating an interruption of long range transport due to phase disorder. Concomitantly, the optical phonons exhibit features that can no longer be explained by a pure Pnma phase, with a frequency shift and narrowing of the $B^2_{1u}$ mode and a new mode appearing at $\sim$3.0 THz consistent with a transition to a higher-symmetry structure. At an intermediate fluence of 3.1 mJ/cm$^2$, a high frequency Lorentzian component consistent with phase heterogeneity appears that rapidly redshifts after 2 ps and whose amplitude exponentially decays on a 90 ps time scale. Our experimental measurements and theoretical calculations provide evidence for a non-thermal, photo-induced nucleation of higher symmetry, semi-metallic phase domains in SnSe appearing within 200 fs.

cond-mat.mtrl-sci↗

arXiv2024

Ultrafast Photo-induced Phase Change in SnSe

Time-resolved multi-terahertz (THz) spectroscopy is used to observe an ultrafast, non-thermal electronic phase change in SnSe driven by interband photoexcitation with 1.55 eV pump photons. The transient THz photoconductivity spectrum is found to be Lorentzian-like, indicating charge localization and phase segregation. The rise of photoconductivity is bimodal in nature, with both a fast and slow component due to excitation into multiple bands and subsequent intervalley scattering. The THz conductivity magnitude, dynamics, and spectra show a drastic change in character at a critical excitation fluence of approximately 6 mJ/cm^2 due to a photo-induced phase segregation and a macroscopic collapse of the band gap.

cond-mat.mtrl-sci↗

arXiv2021

Direct visualization of polaron formation in the thermoelectric SnSe

SnSe is a layered material that currently holds the record for bulk thermoelectric efficiency. The primary determinant of this high efficiency is thought to be the anomalously low thermal conductivity resulting from strong anharmonic coupling within the phonon system. Here we show that the nature of the carrier system in SnSe is also determined by strong coupling to phonons by directly visualizing polaron formation in the material. We employ ultrafast electron diffraction and diffuse scattering to track the response of phonons in both momentum and time to the photodoping of free carriers across the bandgap, observing the bimodal and anisotropic lattice distortions that drive carrier localization. Relatively large (\SI{18.7}{\angstrom}), quasi-1D polarons are formed on the \SI{300}{\femto\second} timescale with smaller (\SI{4.2}{\angstrom}) 3D polarons taking an order of magnitude longer (\SI{4}{\pico\second}) to form. This difference appears to be a consequence of the profoundly anisotropic electron-phonon coupling in SnSe, with strong Fröhlich coupling only to zone center polar optical phonons. These results demonstrate that carriers in SnSe at optimal doping levels results in a high polaron density and that strong electron-phonon coupling is also critical to the thermoelectric performance of this benchmark material and potentially high-performance thermoelectrics more generally.

cond-mat.mtrl-sci↗

arXiv2021

Self-Guided Instance-Aware Network for Depth Completion and Enhancement

Depth completion aims at inferring a dense depth image from sparse depth measurement since glossy, transparent or distant surface cannot be scanned properly by the sensor. Most of existing methods directly interpolate the missing depth measurements based on pixel-wise image content and the corresponding neighboring depth values. Consequently, this leads to blurred boundaries or inaccurate structure of object. To address these problems, we propose a novel self-guided instance-aware network (SG-IANet) that: (1) utilize self-guided mechanism to extract instance-level features that is needed for depth restoration, (2) exploit the geometric and context information into network learning to conform to the underlying constraints for edge clarity and structure consistency, (3) regularize the depth estimation and mitigate the impact of noise by instance-aware learning, and (4) train with synthetic data only by domain randomization to bridge the reality gap. Extensive experiments on synthetic and real world dataset demonstrate that our proposed method outperforms previous works. Further ablation studies give more insights into the proposed method and demonstrate the generalization capability of our model.

cs.CV↗