arXiv subjects

Xiaohui Qiu

Publications and source records attributed to Xiaohui Qiu.

8 recordsLinked to original sources

arXiv2026

Synthesis of single-layered fluorographdiyne nanosheets via selective on-surface 2D covalent polymerization

Two-dimensional conjugated polymers (2DCPs) are significant macromolecular materials with intriguing and tunable physicochemical properties that depend on their geometries. Graphdiyne and its derivatives are exemplary 2DCPs featuring sp-sp2 hybridized skeletons. However, achieving single-layered, large-domain/regular graphdiyne and its derivatives on surfaces remains a formidable challenge due to the lack of selective 2D covalent polymerization methods. Here, we report a selective on-surface 2D covalent polymerization method via the combination of cobalt catalysis and coronene templating, achieving the synthesis of single-layered fluorographdiyne nanosheets up to 60*60 nm2 on Au(111) surface. Using scanning probe techniques, we visualize the sequential polymerization process and characterize cobalt-activated coupling intermediates at the atomic level. Experimental and theoretical analyses suggest that strong d-{\pi} coupling between cobalt and alkynyl transforms a robust Csp-Au bond into a weaker Csp2-Au bond, thereby facilitating the demetallization C-C coupling. Besides, the templating effect of coronene suppresses kinetically trapped defects and improves the selectivity of hexagonal-ring formation in the complex 2D covalent polymerization process.

cond-mat.mtrl-sci↗

arXiv2025

Engineering Graphene Nanoribbons via Periodically Embedding Oxygen Atoms

Heteroatom doping is an important method for engineering graphene nanoribbons (GNRs) because of its ability to modify electronic properties by introducing extra electrons or vacancies. However, precisely integrating oxygen atoms into the lattice of GNRs is unexplored, and the resulting electronic properties remain elusive. Here, we achieve the precise embedding of oxygen atoms into the lattice of GNRs via in situ formation of pyrans, synthesizing two types of oxygen-doped GNRs (O-doped chevron-GNR and O-doped chiral (2,1)-GNR). Using scanning tunneling microscopy, non-contact atomic force microscopy, and density functional theory calculations, the atomic structures and electronic properties of O-doped GNRs are determined, demonstrating that both GNRs are direct bandgap semiconductors with different sensitivities to oxygen dopants. Oxygen dopants have a minor impact on the bandgap of chevron-GNR but a significant effect on the bandgap of chiral (2,1)-GNR, which is attributed to the difference in density of states near the Fermi level between substituted intrinsic carbon atoms and their pristine counterparts. Compared with the pristine chiral (2,1)-GNR, the band structure of O-doped chiral (2,1)-GNR exhibits unexpected band edges transition, which is ascribed to sp2-hybridized oxygen atoms which introduces additional electrons to the conduction band of chiral (2,1)-GNR, leading to the upward shift of Fermi surface.

cond-mat.mtrl-sci↗

arXiv2024

Many-body hybrid Excitons in Organic-Inorganic van der Waals Heterostructures

The coherent many-body interaction at the organic-inorganic interface can give rise to intriguing hybrid excitons that combine the advantages of the Wannier-Mott and Frenkel excitons simultaneously. Unlike the 2D inorganic heterostructures that suffer from moment mismatch, the hybrid excitons formed at the organic-inorganic interface have a momentum-direct nature, which have yet to be explored. Here, we report hybrid excitons at the copper phthalocyanine/molybdenum diselenide (CuPc/MoSe2) interface with strong molecular orientation dependence using low-temperature photoluminescence spectroscopy. The new emission peaks observed in the CuPc/MoSe2 heterostructure indicate the formation of interfacial hybrid excitons. The density functional theory (DFT) calculation confirms the strong hybridization between the lowest unoccupied molecular orbital (LUMO) of CuPc and the conduction band minimum (CBM) of MoSe2, suggesting that the hybrid excitons consist of electrons extended in both layers and holes confined in individual layers. The temperature-dependent measurements show that the hybrid excitons can gain the signatures of the Frenkel excitons of CuPc and the Wannier-Mott excitons of MoSe2 simultaneously. The out-of-plane molecular orientation is used to tailor the interfacial hybrid exciton states. Our results reveal the hybrid excitons at the CuPc/MoSe2 interface with tunability by molecular orientation, which suggests that the emerging organic-inorganic heterostructure can be a promising platform for many-body exciton physics.

physics.optics↗

arXiv2021

Automated assessment of disease severity of COVID-19 using artificial intelligence with synthetic chest CT

Background: Triage of patients is important to control the pandemic of coronavirus disease 2019 (COVID-19), especially during the peak of the pandemic when clinical resources become extremely limited. Purpose: To develop a method that automatically segments and quantifies lung and pneumonia lesions with synthetic chest CT and assess disease severity in COVID-19 patients. Materials and Methods: In this study, we incorporated data augmentation to generate synthetic chest CT images using public available datasets (285 datasets from "Lung Nodule Analysis 2016"). The synthetic images and masks were used to train a 2D U-net neural network and tested on 203 COVID-19 datasets to generate lung and lesion segmentations. Disease severity scores (DL: damage load; DS: damage score) were calculated based on the segmentations. Correlations between DL/DS and clinical lab tests were evaluated using Pearson's method. A p-value < 0.05 was considered as statistical significant. Results: Automatic lung and lesion segmentations were compared with manual annotations. For lung segmentation, the median values of dice similarity coefficient, Jaccard index and average surface distance, were 98.56%, 97.15% and 0.49 mm, respectively. The same metrics for lesion segmentation were 76.95%, 62.54% and 2.36 mm, respectively. Significant (p << 0.05) correlations were found between DL/DS and percentage lymphocytes tests, with r-values of -0.561 and -0.501, respectively. Conclusion: An AI system that based on thoracic radiographic and data augmentation was proposed to segment lung and lesions in COVID-19 patients. Correlations between imaging findings and clinical lab tests suggested the value of this system as a potential tool to assess disease severity of COVID-19.

eess.IV↗

arXiv2021

Unsupervised COVID-19 Lesion Segmentation in CT Using Cycle Consistent Generative Adversarial Network

COVID-19 has become a global pandemic and is still posing a severe health risk to the public. Accurate and efficient segmentation of pneumonia lesions in CT scans is vital for treatment decision-making. We proposed a novel unsupervised approach using cycle consistent generative adversarial network (cycle-GAN) which automates and accelerates the process of lesion delineation. The workflow includes lung volume segmentation, "synthetic" healthy lung generation, infected and healthy image subtraction, and binary lesion mask creation. The lung volume volume was firstly delineated using a pre-trained U-net and worked as the input for the later network. The cycle-GAN was developed to generate synthetic "healthy" lung CT images from infected lung images. After that, the pneumonia lesions are extracted by subtracting the synthetic "healthy" lung CT images from the "infected" lung CT images. A median filter and K-means clustering were then applied to contour the lesions. The auto segmentation approach was validated on two public datasets (Coronacases and Radiopedia). The Dice coefficients reached 0.748 and 0.730, respectively, for the Coronacases and Radiopedia datasets. Meanwhile, the precision and sensitivity for lesion segmentationdetection are 0.813 and 0.735 for the Coronacases dataset, and 0.773 and 0.726 for the Radiopedia dataset. The performance is comparable to existing supervised segmentation networks and outperforms previous unsupervised ones. The proposed unsupervised segmentation method achieved high accuracy and efficiency in automatic COVID-19 lesion delineation. The segmentation result can serve as a baseline for further manual modification and a quality assurance tool for lesion diagnosis. Furthermore, due to its unsupervised nature, the result is not influenced by physicians' experience which otherwise is crucial for supervised methods.

eess.IV↗

arXiv2021

Josephson junctions in double nanowires bridged by in-situ deposited superconductors

We characterize parallel double quantum dot Josephson junctions based on closely-grown double nanowires bridged by in-situ deposited superconductors. The parallel double dot behavior occurs despite the closeness of the nanowires and the potential risk of nanowire clamping during growth. By tuning the charge filling and lead couplings, we map out the simplest parallel double quantum dot Yu-Shiba-Rusinov phase diagram. Our quasi-independent two-wire hybrids show promise for the realization of exotic topological phases.

cond-mat.mes-hall↗

arXiv2018

Room Temperature Continuous-wave Excited Biexciton Emission in CsPbBr3 Nanocrystals

Biexcitons are a manifestation of many-body excitonic interactions crucial for quantum information and quantum computation in the construction of coherent combinations of quantum states. However, due to their small binding energy and low transition efficiency, most biexcitons in conventional semiconductors exist either at cryogenic temperature or under femtosecond pulse laser excitation. Here we demonstrate room temperature, continuous wave driven biexciton states in CsPbBr3 perovskite nanocrystals through coupling with a plasmonic nanogap. The room temperature CsPbBr3 biexciton excitation fluence (~100 mW/cm2) is reduced by ~10^13 times in the Ag nanowire-film nanogaps. The giant enhancement of biexciton emission is driven by coherent biexciton-plasmon Fano interference. These results provide new pathways to develop high efficiency non-blinking single photon sources, entangled light sources and lasers based on biexciton states.

cond-mat.mes-hall↗

arXiv2014

Quasi-freestanding monolayer heterostructure of graphene and hexagonal boron nitride on Ir(111) with a chiral boundary

Monolayer lateral heterostructure of graphene and hexagonal boron nitride (h-BNC) has attracted a growing attention mainly due to its tunable band-gap character and unique physical properties at interface. Hereby, we reported the first-time synthesis of a nearly freestanding h-BNC hybrid on a weakly coupled substrate of Ir (111), where graphene and h-BN possessing different surface heights and corrugations formed a perfect monolayer hybrid. With the aid of scanning tunneling microscopy/spectroscopy (STM/STS), we demonstrated that h-BN can patch alongside the boundary of pre-deposited graphene domains and vice versa to form a seamless monolayer hybrid, with the realization of predominant zigzag type chiral boundaries at the interface. Density-functional theory calculations and STM/STS measurements aided us to reveal that this interface between graphene and h-BN were atomically sharp in aspects of the chemical bonding as well as the local electronic property from both theoretical and experimental points of view.

physics.chem-ph↗