arXiv subjects

Xufan Li

Publications and source records attributed to Xufan Li.

6 recordsLinked to original sources

arXiv2026

Direct observation of ultrafast defect-bound and free exciton dynamics in defect-engineered WS$_2$ monolayers

Defects in two-dimensional transition metal dichalcogenides (TMDCs) broadly affect their optical and electronic properties. Directly capturing the ultrafast processes of exciton trapping and defect-bound exciton formation is crucial for understanding and advancing defect-mediated optoelectronics and quantum technologies. However, the weak transient optical absorption of defect-bound excitons has limited their experimental observation to date. Here, we report the direct observation of the ultrafast dynamics of defect-bound excitons in monolayer WS$_2$ crystals with a high density of mono-sulfur vacancies (V$_S$) and W-site defect complexes (S$_W$V$_S$) resulting from synthesis by alkali metal halide-assisted chemical vapor deposition. The dynamics of excitons bound to these defects, along with their coherent interactions with free excitons, are elucidated using ultrafast optical spectroscopy. Using above band-edge photoexcitation, we find that both free and defect-bound excitons simultaneously form within 300 fs from hot carrier relaxation. The defect-bound excitons exhibit shorter lifetimes than free excitons, leading to a population difference of the corresponding excitonic states and free exciton trapping within a 1--100 ps window. Band-edge photoexcitation of free and defect-bound exciton states reveals ultrafast interconversion within ~150 fs (comparable to our temporal resolution), indicating possible coherent coupling between these states. We further demonstrate efficient up-conversion of defect-bound excitons to free excitons with photon energies up to ~300 meV below the free exciton resonance. These findings provide insights into the ultrafast dynamics of defect-bound excitons in TMDCs and their coupling with free excitons, which are relevant to defect-engineered optoelectronic, quantum photonic, and valleytronic applications.

physics.optics↗

arXiv2026

Spontaneous Polarization Suppression of Exciton-Exciton Annihilation in 3R-Stacked MoS$_2$ Bilayers

Rapid exciton-exciton annihilation (EEA) in two-dimensional semiconductors limits access to high-density excitonic regimes essential for efficient optoelectronic operation under strong excitation. Here, we show that EEA is suppressed by repulsive dipole-dipole interactions between interlayer excitons polarized by the spontaneous polarization intrinsic to rhombohedral (3R)-stacked MoS$_2$ bilayers. Using ultrafast pump-probe spectroscopy, we measure an EEA rate of $\gamma_{\rm EEA}=(5.03\pm0.99)\times10^{-3}$ cm$^2$ s$^{-1}$ in 3R bilayers, which is approximately 18.2-fold smaller than that in monolayers and 2.9-fold smaller than that in nonpolar 2H bilayers. Despite the higher exciton diffusivity recently reported for 3R relative to 2H bilayers, the reduced EEA rate in 3R indicates a rate-limited regime governed by the close-encounter annihilation probability rather than diffusion. A rate-limited annihilation model incorporating a dipole-dipole repulsive potential captures the observed ratio $\gamma_{{\rm EEA},3{\rm R}}/\gamma_{{\rm EEA},2{\rm H}}\approx0.35$ for an exciton-exciton encounter distance of $\sim$1.3 nm, consistent with the bilayer exciton Bohr radius. These results show that spontaneous polarization in 3R-stacked bilayers suppresses nonlinear excitonic losses and provides a route toward high-density excitonics.

cond-mat.mes-hall↗

arXiv2025

Exploring the mechanisms of transverse relaxation of copper(II)-phthalocyanine spin qubits

Molecular spin qubits are promising candidates for quantum technologies, but their performance is limited by decoherence arising from diverse mechanisms. The complexity of the environment makes it challenging to identify the main source of noise and target it for mitigation. Here we present a systematic experimental and theoretical framework for analyzing the mechanisms of transverse relaxation in copper(II) phthalocyanine (CuPc) diluted into diamagnetic phthalocyanine hosts. Using pulsed EPR spectroscopy together with first-principles cluster correlation expansion simulations, we quantitatively separate the contributions from hyperfine-coupled nuclear spins, spin--lattice relaxation, and electron--electron dipolar interactions. Our detailed modeling shows that both strongly and weakly coupled nuclei contribute negligibly to $T_2$, while longitudinal dipolar interactions with electronic spins, through instantaneous and spectral diffusion, constitute the main decoherence channel even at moderate spin densities. This conclusion is validated by direct comparison between simulated spin-echo dynamics and experimental data. By providing a robust modeling and experimental approach, our work identifies favorable values of the electron spin density for quantum applications, and provides a transferable methodology for predicting ensemble coherence times. These insights will guide the design and optimization of molecular spin qubits for scalable quantum devices.

physics.chem-ph↗

arXiv2025

Quantum Sensing of Copper-Phthalocyanine Electron Spins via NV Relaxometry

Molecular spin systems are promising candidates for quantum information processing and nanoscale sensing, yet their characterization at room temperature remains challenging due to fast spin decoherence. In this work, we use $T_1$ relaxometry of shallow nitrogen-vacancy (NV) centers in diamond to probe the electron spin ensemble of a polycrystalline copper phthalocyanine (CuPc) thin film. In addition to unequivocally identifying the NV-CuPc interaction thanks to its hyperfine spectrum, we further extract key parameters of the CuPc spin ensemble, including its correlation time and local lattice orientation, that cannot be measured in bulk electron resonance experiments. The analysis of our experimental results confirms that electron-electron interactions dominate the decoherence dynamics of CuPc at room temperature. Additionally, we demonstrate that the CuPc-enhanced NV relaxometry can serve as a robust method to estimate the NV depth with $\sim1$~nm precision. Our results establish NV centers as powerful probes for molecular spin systems, providing insights into molecular qubits, spin bath engineering, and hybrid quantum materials, and offering a potential pathway toward their applications such as molecular-scale quantum processors and spin-based quantum networks.

quant-ph↗

arXiv2018

Dynamics of liquid crystal on hexagonal lattice

Nematic liquid crystal (LC) molecules adsorbed on two dimensional materials are aligned along the crystal directions of the hexagonal lattice. It was demonstrated that short electric pulses can reorient the aligned LC molecules in the preferred armchair direction of hexagonal boron nitride (h-BN). Several states with a variety of colors were obtained by changing the direction and strength of the electric pulses. The ab initio calculations based on density functional theory was carried out to determine the favorable adsorption configurations of the LC molecules on the h-BN surface. A non-volatile display, in which pixel resolution can be determined by grains of hexagonal surface, is proposed, which can offer a pathway towards dynamic high-quality pixels with low power consumption, and could define a new paradigm for all non-volatile display applications.

cond-mat.soft↗

arXiv2018

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level precision. This progress has been accompanied by an exponential increase in the size and quality of datasets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large datasets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extract information from atomically resolved images including location of the atomic species and type of defects. We develop a 'weakly-supervised' approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular 'rotor'. This deep learning based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data.

cond-mat.mtrl-sci↗