arXiv subjects

Xian Lin

Publications and source records attributed to Xian Lin.

13 recordsLinked to original sources

arXiv2024

Observation of Transient Trion Induced by Ultrafast Charge Transfer in Graphene/MoS2 Heterostructure

Van der Waals (Vdw) heterostructures constructed from TMDCs provide an ideal platform for exploring various quasiparticle behaviors, with trion-composed of neutral exciton and charged carrier-being a notable example. There are typically three methods to generate trion: electrical doping, chemical doping, and direct optical doping. The first two methods generate static trion, while the last gives rise to transient trion. Here, we present an indirect optical doping approach to generate transient trion via ultrafast charge transfer (CT) and achieve control over the trion-to-exciton ratio by adjusting CT in Gr/MoS2 heterostructure. Furthermore, we demonstrated that dynamics of the transient trion generated with this method, which shows slightly longer lifetime than that of exciton accounted for the Coulomb interactions between trion and charged defect. This study provides fresh perspectives on the construction of new quasiparticles, dynamical characterization and the control of the many-body interaction in two-dimensional structure.

cond-mat.mes-hall↗

arXiv2024

SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts

Segment anything model (SAM), a foundation model with superior versatility and generalization across diverse segmentation tasks, has attracted widespread attention in medical imaging. However, it has been proved that SAM would encounter severe performance degradation due to the lack of medical knowledge in training and local feature encoding. Though several SAM-based models have been proposed for tuning SAM in medical imaging, they still suffer from insufficient feature extraction and highly rely on high-quality prompts. In this paper, we construct a large CT dataset consisting of 1.1M CT images and 5M masks from public datasets and propose a powerful foundation model SAMCT allowing labor-free prompts. Specifically, based on SAM, SAMCT is further equipped with a U-shaped CNN image encoder, a cross-branch interaction module, and a task-indicator prompt encoder. The U-shaped CNN image encoder works in parallel with the ViT image encoder in SAM to supplement local features. Cross-branch interaction enhances the feature expression capability of the CNN image encoder and the ViT image encoder by exchanging global perception and local features from one to the other. The task-indicator prompt encoder is a plug-and-play component to effortlessly encode task-related indicators into prompt embeddings. In this way, SAMCT can work in an automatic manner in addition to the semi-automatic interactive strategy in SAM. Extensive experiments demonstrate the superiority of SAMCT against the state-of-the-art task-specific and SAM-based medical foundation models on various tasks. The code, data, and models are released at https://github.com/xianlin7/SAMCT.

cs.CV↗

arXiv2023

Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting

End-to-end medical image segmentation is of great value for computer-aided diagnosis dominated by task-specific models, usually suffering from poor generalization. With recent breakthroughs brought by the segment anything model (SAM) for universal image segmentation, extensive efforts have been made to adapt SAM for medical imaging but still encounter two major issues: 1) severe performance degradation and limited generalization without proper adaptation, and 2) semi-automatic segmentation relying on accurate manual prompts for interaction. In this work, we propose SAMUS as a universal model tailored for ultrasound image segmentation and further enable it to work in an end-to-end manner denoted as AutoSAMUS. Specifically, in SAMUS, a parallel CNN branch is introduced to supplement local information through cross-branch attention, and a feature adapter and a position adapter are jointly used to adapt SAM from natural to ultrasound domains while reducing training complexity. AutoSAMUS is realized by introducing an auto prompt generator (APG) to replace the manual prompt encoder of SAMUS to automatically generate prompt embeddings. A comprehensive ultrasound dataset, comprising about 30k images and 69k masks and covering six object categories, is collected for verification. Extensive comparison experiments demonstrate the superiority of SAMUS and AutoSAMUS against the state-of-the-art task-specific and SAM-based foundation models. We believe the auto-prompted SAM-based model has the potential to become a new paradigm for end-to-end medical image segmentation and deserves more exploration. Code and data are available at https://github.com/xianlin7/SAMUS.

cs.CV↗

arXiv2023

ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation

Transformers have been extensively studied in medical image segmentation to build pairwise long-range dependence. Yet, relatively limited well-annotated medical image data makes transformers struggle to extract diverse global features, resulting in attention collapse where attention maps become similar or even identical. Comparatively, convolutional neural networks (CNNs) have better convergence properties on small-scale training data but suffer from limited receptive fields. Existing works are dedicated to exploring the combinations of CNN and transformers while ignoring attention collapse, leaving the potential of transformers under-explored. In this paper, we propose to build CNN-style Transformers (ConvFormer) to promote better attention convergence and thus better segmentation performance. Specifically, ConvFormer consists of pooling, CNN-style self-attention (CSA), and convolutional feed-forward network (CFFN) corresponding to tokenization, self-attention, and feed-forward network in vanilla vision transformers. In contrast to positional embedding and tokenization, ConvFormer adopts 2D convolution and max-pooling for both position information preservation and feature size reduction. In this way, CSA takes 2D feature maps as inputs and establishes long-range dependency by constructing self-attention matrices as convolution kernels with adaptive sizes. Following CSA, 2D convolution is utilized for feature refinement through CFFN. Experimental results on multiple datasets demonstrate the effectiveness of ConvFormer working as a plug-and-play module for consistent performance improvement of transformer-based frameworks. Code is available at https://github.com/xianlin7/ConvFormer.

eess.IV↗

arXiv2023

Spectroscopic Evidence for Interfacial Charge Separation and Recombination in Graphene-MoS2 Vertical Heterostructures

Vertical van der Waals (vdW) heterostructures consisting of graphene (Gr) and transition metal dichalcogenides (TMDs) have created a fascinating platform for exploring optical and electronic properties in the two-dimensional limit. Previous study has revealed the ultrafast formation of interfacial excitons and the exciton dynamics in the Gr/MoS2 heterostructure. However, a fully understanding of interfacial charge separation and the subsequent dynamics in graphene-based heterostructures remains elusive. Here, we investigate the carrier dynamics of Gr-MoS2 (including Gr/MoS2 and MoS2/Gr stacking sequences) heterostructures under different photoexcitation energies and stacking sequences by comprehensive ultrafast means, including time-resolved terahertz spectroscopy (TRTS), terahertz emission spectroscopy (TES) and transient absorption spectroscopy (TAS). We demonstrate that the Gr/MoS2 heterostructure generates hot electron injection from graphene into the MoS2 layer with photoexcitation of sub-A-exciton of MoS2, while the interfacial charge separation in the MoS2/Gr could be partially blocked by the electric field of substrate. Charge transfer (CT) occurs in same directions for the Gr-MoS2 heterostructures with opposite stacking order, resulting in the opposite orientations of the interfacial photocurrent, as directly demonstrated by the terahertz (THz) emission. Moreover, we demonstrate that the recombination time of interfacial charges after CT is on a timescale of 18 ps to 1 ns, depending on the density of defect states in MoS2 layer. This work provides a comprehensive and unambiguous picture of the interfacial charge dynamics of graphene-based heterostructures, which is essential for developing Gr/TMDs based optoelectronic devices.

physics.optics↗

arXiv2022

BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image Segmentation

Objective: Transformers, born to remedy the inadequate receptive fields of CNNs, have drawn explosive attention recently. However, the daunting computational complexity of global representation learning, together with rigid window partitioning, hinders their deployment in medical image segmentation. This work aims to address the above two issues in transformers for better medical image segmentation. Methods: We propose a boundary-aware lightweight transformer (BATFormer) that can build cross-scale global interaction with lower computational complexity and generate windows flexibly under the guidance of entropy. Specifically, to fully explore the benefits of transformers in long-range dependency establishment, a cross-scale global transformer (CGT) module is introduced to jointly utilize multiple small-scale feature maps for richer global features with lower computational complexity. Given the importance of shape modeling in medical image segmentation, a boundary-aware local transformer (BLT) module is constructed. Different from rigid window partitioning in vanilla transformers which would produce boundary distortion, BLT adopts an adaptive window partitioning scheme under the guidance of entropy for both computational complexity reduction and shape preservation. Results: BATFormer achieves the best performance in Dice of 92.84%, 91.97%, 90.26%, and 96.30% for the average, right ventricle, myocardium, and left ventricle respectively on the ACDC dataset and the best performance in Dice, IoU, and ACC of 90.76%, 84.64%, and 96.76% respectively on the ISIC 2018 dataset. More importantly, BATFormer requires the least amount of model parameters and the lowest computational complexity compared to the state-of-the-art approaches. Conclusion and Significance: Our results demonstrate the necessity of developing customized transformers for efficient and better medical image segmentation.

cs.CV↗

arXiv2022

The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning

Vision transformers have recently set off a new wave in the field of medical image analysis due to their remarkable performance on various computer vision tasks. However, recent hybrid-/transformer-based approaches mainly focus on the benefits of transformers in capturing long-range dependency while ignoring the issues of their daunting computational complexity, high training costs, and redundant dependency. In this paper, we propose to employ adaptive pruning to transformers for medical image segmentation and propose a lightweight and effective hybrid network APFormer. To our best knowledge, this is the first work on transformer pruning for medical image analysis tasks. The key features of APFormer mainly are self-supervised self-attention (SSA) to improve the convergence of dependency establishment, Gaussian-prior relative position embedding (GRPE) to foster the learning of position information, and adaptive pruning to eliminate redundant computations and perception information. Specifically, SSA and GRPE consider the well-converged dependency distribution and the Gaussian heatmap distribution separately as the prior knowledge of self-attention and position embedding to ease the training of transformers and lay a solid foundation for the following pruning operation. Then, adaptive transformer pruning, both query-wise and dependency-wise, is performed by adjusting the gate control parameters for both complexity reduction and performance improvement. Extensive experiments on two widely-used datasets demonstrate the prominent segmentation performance of APFormer against the state-of-the-art methods with much fewer parameters and lower GFLOPs. More importantly, we prove, through ablation studies, that adaptive pruning can work as a plug-n-play module for performance improvement on other hybrid-/transformer-based methods. Code is available at https://github.com/xianlin7/APFormer.

cs.CV↗

arXiv2022

Semiconductor-like photocarrier dynamics in Dirac Semimetal Cd3As2 film Probed with transient Terahertz Spectroscopy

The topological three-dimensional Dirac semimetal Cd3As2 has drawn great attention for the novel physics and promising applications in optoelectronic devices operating in the infrared and THz regimes. Among the extensive studies in the past decades, one intriguing debate is the underlined mechanism that governing the nonequilibrium carrier dynamics following photoexcitation. In this study, the temperature dependent photocarrier dynamics in Cd3As2 film has been investigated with time-resolved terahertz spectroscopy. The experimental results demonstrate that photoexcitation results in abrupt increase in THz photoconductivity, and the subsequent relaxation shows a single exponential relaxation for various temperatures and pump fluences. The relaxation time increase from 4.7 ps at 5 K to 7.5 ps at 220 K, while the lifetime remains almost constant of ~7.5 ps with temperature above 220 K. A Rothwarf-Taylor model was employed to fit the temperature dependent relaxation time, and a narrow energy gap of ~35 meV is obtained, which occurs around the Dirac node. Our THz spectroscopy results demonstrate that the photocarrier relaxation in Cd3As2 shows a semiconductor-like behavior, rather than hot carrier scatterings in graphene and most of metals.

cond-mat.str-el↗

arXiv2022

Observation of Ultrafast Interfacial Exciton Formation and Recombination in Graphene/MoS2 Heterostructure

In this study,we combined time-resolved terahertz spectroscopy along with transient absorption spectroscopy to revisit the interlayer non-equilibrium carrier dynamics in largely lateral size Gr/MoS2 heterostructure fabricated with chemical vapor deposition method. Our experimental results reveal that, with photon-energy below the A-exciton of MoS2 monolayer, hot electrons transfer from graphene to MoS2 takes place in time scale of less than 0.5 ps, resulting in ultrafast formation of interfacial exciton in the heterostructure, subsequently, recombination relaxation of the interfacial exciton occurs in time scale of ~18 ps. A new model considering carrier heating and photogating effect in graphene is proposed to estimate the amount of carrier transfer in the heterostructure, which shows a good agreement with experimental result. Moreover, when the photon-energy is on-resonance with the A-exciton of MoS2, photogenerated holes in MoS2 are transferred to graphene layer within 0.5 ps, leading to the formation of interfacial exciton, the subsequent photoconductivity (PC) relaxation of graphene and bleaching recovery of A-exciton in MoS2 take place around ~10 ps time scale, ascribing to the interfacial exciton recombination. The faster recombination time of interfacial exciton with on-resonance excitation could come from the reduced interface barrier caused by bandgap renormalization effect. Our study provides deep insight into the understanding of interfacial charge transfer as well as the relaxation dynamics in graphene-based heterostructures, which are promising for the applications of graphene-based optoelectronic devices.

physics.optics↗

arXiv2022

Ultrafast Dynamics of Defect-Assisted Auger process in PdSe2 films: Synergistic Interaction Between Defect Trapping and Auger Effect

Strong Coulomb interactions in two-dimensional systems, together with quantum confinement, make many-body processes particularly effective for carrier dynamics, which plays a crucial role in determining carrier lifetime, photoconductivity, and emission yield of the materials. Hereby, by using optical pump and terahertz probe spectroscopy, we have investigated the photocarrier dynamics in the PdSe2 films with different thickness. The experimental results reveal that the photocarrier relaxation consists of two components: a fast component of 2.5 ps that shows the layer-thickness independence, and a slow component has typical lifetime of 7.3 ps decreasing with the layer thickness. Surprisingly, the relaxation times for both fast and slow components are exhibited both pump fluence and temperature independence, which suggests that synergistic interactions between defect trapping and Auger effect dominate the photocarrier dynamics in PdSe2 films. A model involving defect-assisted Auger process is proposed, which can reproduce the experimental results well. The fitting results reveal that the layer dependent lifetime is determined by the defect density rather than carrier occupancy rate after photoexcitation. Our results underscore the interplay between Auger process and defects in two-dimensional semiconductors.

cond-mat.mes-hall↗

arXiv2021

Temperature-driven Emergence of Negative Photoconductivity in Semimetal MoTe2 Film Probed with Terahertz Spectroscopy

Layered two-dimensional (2D) materials MoTe2 have been paid special attention due to the rich optoelectronic properties with various phases. The nonequilibrium carrier dynamics as well as its temperature dependence in MoTe2 are of prime importance, as it can shed light on understanding the anomalous optical response and potential applications in far infrared (IR) photodetection. Hereby, we employ time-resolved terahertz (THz) spectroscopy to study the temperature dependent nonequilibrium carrier dynamics in MoTe2 films. After photoexcitation of 1.59 eV, the 1T'-phase MoTe2 at high temperature behaves only THz positive photoconductivity (PPC) with relaxation time of less than 1 ps. In contrast, the Td-phase MoTe2 at low temperature shows ultrafast THz PPC initially followed by emerging THz negative photoconductivity (NPC), and the THz NPC signal relaxes to the equilibrium state in hundreds of ps time scale. Small polaron formation induced by hot carrier has been proposed to be ascribed to the THz NPC in the polar semimetal MoTe2 at low temperature. The polaron formation time after photoexcitation increases slightly with temperature, which is determined to be ~0.4 ps at 5 K and 0.5 ps at 100 K. Our experimental result demonstrates for the first time the dynamical formation of small poalron in MoTe2 Weyl semimetal, this is fundamental importance on the understanding the temperature dependent electron-phonon coupling and quantum phase transition, as well as the designing the MoTe2-based far IR photodetector.

cond-mat.str-el↗

arXiv2020

Observation of Negative THz Photoconductivity in Large Area Type-II Dirac Semimetal PtTe2

As a newly emergent type-II Dirac semimetal, Platinum Telluride (PtTe2) stands out from other 2D noble-transition-metal dichalcogenides for the unique structure and novel physical properties, such as high carrier mobility, strong electron-phonon coupling and tunable bandgap, which make the PtTe2 a good candidate for applications in optoelectronics, valleytronics and far infrared detectors. Although the transport properties of PtTe2 have been studied extensively, the dynamics of the nonequilibrium carriers remain nearly uninvestigated. Herein we employ optical pump-terahertz (THz) probe spectroscopy (OPTP) to systematically study the photocarrier dynamics of PtTe2 thin films with varying pump fluence, temperature, and film thickness. Upon photoexcitation the THz photoconductivity (PC) of 5 nm PtTe2 film shows abrupt increase initially, while the THz PC changes into negative value in a subpicosecond time scale, followed by a prolonged recovery process that lasted hundreds of picoseconds (ps). This unusual THz PC response observed in the 5 nm PtTe2 film was found to be absent in a 2 nm PtTe2 film. We assign the unexpected negative THz PC as the small polaron formation due to the strong electron-Eg-mode phonon coupling, which is further substantiated by pump fluence- and temperature-dependent measurements as well as the Raman spectroscopy. Moreover, our investigations give a subpicosecond time scale of sequential carrier cooling and polaron formation. The present study provides deep insights into the underlying dynamics evolution mechanisms of photocarrier in type-II Dirac semimetal upon photoexcitation, which is fundamental importance for designing PtTe2-based optoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2019

Terahertz emission in the van der Waals magnet CrSiTe3

The van der Waals magnet CrSiTe3 (CST) has captured immense interest because it is capable of retaining the long-range ferromagnetic order even in its monolayer form, thus offering potential use in spintronic devices. Bulk CST crystal has inversion symmetry that is broken on the crystal surface. Here, by employing ultrafast terahertz (THz) emission spectroscopy and time resolved THz spectroscopy, the THz emission of the CST crystal was investigated, which shows a strong THz emission from the crystal surface under femtosecond (fs) pulse excitation at 800 nm. Theoretical analysis based on space symmetry of CST suggests the dominant role of shift current occurring on the surface with a thickness of a few quintuple layers in producing the THz emission, in consistence with the experimental observation that the emitted THz amplitude strongly depends on the azimuthal and pumping polarization angles. The present study offers a new efficient THz emitter as well as a better understanding of the nonlinear optical response of CST. It hopefully will open a window toward the investigation on the nonlinear optical response in the mono-/few-layer van der Waals crystals with low-dimensional magnetism.

physics.optics↗