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Qian Tao

Qian Tao appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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cond-mat.supr-concond-mat.str-elcond-mat.mtrl-sciComputer Visioneess.IVMachine LearningHuman-Computer Interactionphysics.flu-dyn

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Published work

30 published item(s)

preprint2026arXiv

Field-induced magnetic phase transitions and transport anomalies in GdAlSi

Magnetic topological materials hosting non-zero Berry curvature have emerged as a focus of intensive research due to their exceptional magnetoelectric coupling phenomena and potential applications in next-generation spintronic devices. In this work, we successfully synthesized high-quality GdAlSi single crystals, a prototypical member of RAlX (R = rare earth elements; X = Si/Ge) family that has been theoretically predicted to sustain a non-trivial Weyl semimetal state. Through systematic investigations of magnetic and transport properties, we identified two successive antiferromagnetic transitions at critical temperatures TN1 31.9 K and TN2 31.1 K, as evidenced by temperature-dependent resistivity, magnetic susceptibility, and specific heat measurements. Notably, applied magnetic fields exceeding 8 T induce a third magnetic transition (TN3), generating a cascade of metamagnetic transitions that collectively form a dendritic phase diagram. This complex magnetic behavior is attributed to the interplay between localized Gd-4f moments and itinerant conduction electrons, possibly mediated by Dzyaloshinskii-Moriya interactions. Transport measurements revealed striking stepwise anomalies in magnetoresistance when crossing phase boundaries, accompanied by pronounced hysteresis loops arising from magnetic moment flopping processes. Our results not only establish GdAlSi as a rich platform for investigating correlated topological states, but also demonstrate its potential for engineering topological phase transitions through magnetic symmetry manipulation in Weyl semimetals.

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preprint2026arXiv

Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges

Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the Learn2Reg 2020-2023 challenges have released several complementary datasets and established metrics for evaluations. Building on this foundation, the 2024 edition expands the challenge's scope to cover a wider range of registration scenarios, particularly in terms of modality diversity and task complexity, by introducing three new tasks, including large-scale multi-modal registration and unsupervised inter-subject brain registration, as well as the first microscopy-focused benchmark within Learn2Reg. The new datasets also inspired new method developments, including invertibility constraints, pyramid features, keypoints alignment and instance optimisation. Visit Learn2Reg at https://learn2reg.grand-challenge.org.

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preprint2026arXiv

Set-Based Groupwise Registration for Variable-Length, Variable-Contrast Cardiac MRI

Quantitative cardiac magnetic resonance imaging (MRI) enables non-invasive myocardial tissue characterization but relies on robust motion correction within these variable-length, variable-contrast image sequences. Groupwise registration, which simultaneously aligns all images, has shown greater robustness than pairwise registration for motion correction. However, current deep-learning-based groupwise registration methods cannot generalize across MRI sequences: the architecture typically encodes input data as a fixed-length channel stack, which rigidly couples network design to protocol-specific sequence length, input ordering, and contrast dynamics. At inference time, any change in imaging protocols will render the network unusable. In this work, we introduce \emph{\AnyTwoReg}, a new set-based groupwise registration framework that takes a quantitative MRI sequence as an unordered set. This set formulation fundamentally decouples network design from sequence length and input ordering. By utilizing a shared encoder and correlation-guided feature aggregation, \emph{\AnyTwoReg} constructs a permutation-invariant canonical reference for registration, and learns a permutation-equivariant mapping from images to deformation fields. Additionally, we extract contrast-insensitive image features from an existing foundation model to handle extreme contrast variations. Trained exclusively on a single public $T_1$ mapping dataset (STONE, sequence length $L=11$), \AnyTwoReg generalizes to two unseen quantitative MRI datasets (MOLLI, ASL) with variable lengths ($L \in [11, 60]$) and different contrast dynamics. It achieves strong cross-protocol generalization in a zero-shot manner, and consistently improves downstream quantitative mapping quality. Notably, while designed for quantitative MRI sequences, our framework is directly applicable to Cine MRI sequences for inter-cardiac-phase registration.

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preprint2023arXiv

Giant Nernst effect in the crossover between Fermi liquid and strange metal

The strange-metal state is a crucial problem in condensed matter physics highlighted by its ubiquity in almost all major correlated systems[1-7]. Its understanding could provide important insight into high-Tc superconductivity[2] and quantum criticality[8]. However, with the Fermi liquid theory failing in strange metals, understanding the highly unconventional behaviors has been a long-standing challenge. Fundamental aspects of strange metals remain elusive, including the nature of their charge carriers[1]. Here, we report the observation of a giant Nernst response in the strange-metal state in a two-dimensional superconductor 2M-WS2. A giant Nernst coefficient comparable to the vortex Nernst signal in superconducting cuprates, and its high sensitivity to carrier mobility, are found when the system enters the strange-metal state from the Fermi liquid state. The temperature and magnetic field dependence of the giant Nernst peak rule out the relevance of both Landau quasiparticles and superconductivity. Instead, the giant Nernst peak at the crossover indicates a dramatic change in carrier entropy when entering the strange-metal state. The presence of such an anomalous Nernst response is further confirmed in other iconic strange metals, suggesting its universality and places stringent experimental constraints on the mechanism of strange metals.

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preprint2022arXiv

Deep Recursive Embedding for High-Dimensional Data

Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this paper, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by well-established objectives such as Kullback-Leibler (KL) divergence minimization. We further propose a recursive strategy, called deep recursive embedding (DRE), to make use of the latent data representations for boosted embedding performance. We exemplify the flexibility of DRE by different architectures and loss functions, and benchmarked our method against the two most popular embedding methods, namely, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). The proposed DRE method can map out-of-sample data and scale to extremely large datasets. Experiments on a range of public datasets demonstrated improved embedding performance in terms of local and global structure preservation, compared with other state-of-the-art embedding methods.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Deep Recursive Embedding for High-Dimensional Data

t-distributed stochastic neighbor embedding (t-SNE) is a well-established visualization method for complex high-dimensional data. However, the original t-SNE method is nonparametric, stochastic, and often cannot well prevserve the global structure of data as it emphasizes local neighborhood. With t-SNE as a reference, we propose to combine the deep neural network (DNN) with the mathematical-grounded embedding rules for high-dimensional data embedding. We first introduce a deep embedding network (DEN) framework, which can learn a parametric mapping from high-dimensional space to low-dimensional embedding. DEN has a flexible architecture that can accommodate different input data (vector, image, or tensor) and loss functions. To improve the embedding performance, a recursive training strategy is proposed to make use of the latent representations extracted by DEN. Finally, we propose a two-stage loss function combining the advantages of two popular embedding methods, namely, t-SNE and uniform manifold approximation and projection (UMAP), for optimal visualization effect. We name the proposed method Deep Recursive Embedding (DRE), which optimizes DEN with a recursive training strategy and two-stage losse. Our experiments demonstrated the excellent performance of the proposed DRE method on high-dimensional data embedding, across a variety of public databases. Remarkably, our comparative results suggested that our proposed DRE could lead to improved global structure preservation.

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preprint2022arXiv

Density-Aware Hyper-Graph Neural Networks for Graph-based Semi-supervised Node Classification

Graph-based semi-supervised learning, which can exploit the connectivity relationship between labeled and unlabeled data, has been shown to outperform the state-of-the-art in many artificial intelligence applications. One of the most challenging problems for graph-based semi-supervised node classification is how to use the implicit information among various data to improve the performance of classifying. Traditional studies on graph-based semi-supervised learning have focused on the pairwise connections among data. However, the data correlation in real applications could be beyond pairwise and more complicated. The density information has been demonstrated to be an important clue, but it is rarely explored in depth among existing graph-based semi-supervised node classification methods. To develop a flexible and effective model for graph-based semi-supervised node classification, we propose a novel Density-Aware Hyper-Graph Neural Networks (DA-HGNN). In our proposed approach, hyper-graph is provided to explore the high-order semantic correlation among data, and a density-aware hyper-graph attention network is presented to explore the high-order connection relationship. Extensive experiments are conducted in various benchmark datasets, and the results demonstrate the effectiveness of the proposed approach.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Two-dimensional superconductivity at the surfaces of KTaO3 gated with ionic liquid

The recent observation of superconductivity at the interfaces between KTaO3 and EuO (or LaAlO3) offers a new example of emergent phenomena at oxide interfaces. This superconductivity exhibits an unusual strong dependence on the crystalline orientation of KTaO3 and its superconducting transition temperature Tc is nearly one order of magnitude higher than that of the seminal LaAlO3/SrTiO3 interface. To understand its mechanism, it is crucial to address if the formation of oxide interfaces is indispensable for the presence of superconductivity. Here, by exploiting ionic liquid (IL) gating, we obtain superconductivity at KTaO3 (111) and (110) surfaces with Tc up to 2.0 K and 1.0 K, respectively. This oxide-interface-free superconductivity gives a clear experimental evidence that the essential physics of KTaO3 interface superconductivity lies in the KTaO3 surfaces doped with electrons. Moreover, the ability to control superconductivity at surfaces with IL provides a simple way to study the intrinsic superconductivity in KTaO3.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging

Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac structures, is a crucial first step for clinical diagnosis and treatment. However, direct segmentation of LGE-MRIs is challenging due to its attenuated contrast. Since most clinical studies have relied on manual and labor-intensive approaches, automatic methods are of high interest, particularly optimized machine learning approaches. To address this, we organized the "2018 Left Atrium Segmentation Challenge" using 154 3D LGE-MRIs, currently the world's largest cardiac LGE-MRI dataset, and associated labels of the left atrium segmented by three medical experts, ultimately attracting the participation of 27 international teams. In this paper, extensive analysis of the submitted algorithms using technical and biological metrics was performed by undergoing subgroup analysis and conducting hyper-parameter analysis, offering an overall picture of the major design choices of convolutional neural networks (CNNs) and practical considerations for achieving state-of-the-art left atrium segmentation. Results show the top method achieved a dice score of 93.2% and a mean surface to a surface distance of 0.7 mm, significantly outperforming prior state-of-the-art. Particularly, our analysis demonstrated that double, sequentially used CNNs, in which a first CNN is used for automatic region-of-interest localization and a subsequent CNN is used for refined regional segmentation, achieved far superior results than traditional methods and pipelines containing single CNNs. This large-scale benchmarking study makes a significant step towards much-improved segmentation methods for cardiac LGE-MRIs, and will serve as an important benchmark for evaluating and comparing the future works in the field.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Frozen Patterns of Impacted Droplets: From Conical Tips to Toroidal Shapes

We report frozen patterns for the water droplets impacting on a cold substrate through fast-speed images. These patterns can be manipulated by several physical parameters (the droplet size, falling height, and substrate temperature), and the scaling analysis has a remarkable agreement with the phase diagram. The observed double-concentric toroidal shape is attributed to the correlation between the impacting dynamics and freezing process, as confirmed by the spatiotemporal evolution of the droplet temperature, the identified timescale associated with the morphology and solidification ($t_{inn}\simeq τ_{sol}$), and the ice front-advection model. These results for frozen patterns provide insight into the complex interplay of the rapid impacting hydrodynamics, the transient heat transfer, and the intricate solidification process.

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preprint2020arXiv

Type-I superconductivity in noncentrosymmetric NbGe$_{2}$

Single crystals of NbGe$_{2}$ which crystallize in a noncentrosymmetric hexagonal structure with chirality are synthesized and their superconductivity is investigated. Type-I superconductivity is confirmed by dc magnetization, field-induced second-to first-order phase transition in specific heat, and a small Ginzburg-Landau parameter $κ_{GL}=0.12$. The isothermal magnetization measurements show that there is a crossover from type-I to type-II/1 superconductivity with decreasing temperature and an unusually enhanced surface superconducting critical field ($H_{c3}$) is discovered. The band structure calculations indicate the presence of Kramer-Weyl nodes near the Fermi level. These observations demonstrate that NbGe$_{2}$ is an interesting and rare example involving the possible interplay of type-I superconductivity, noncentrosymmetric structure and topological properties.

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preprint2016arXiv

A New Ferromagnetic Superconductor: CsEuFe$_4$As$_4$

Superconductivity (SC) and ferromagnetism (FM) are in general antagonistic, which makes their coexistence very rare. Following our recent discovery of robust coexistence of SC and FM in RbEuFe$_4$As$_4$ [Y. Liu et al., arXiv: 1605.04396 (2016)], here we report another example of such a coexistence in its sister compound CsEuFe$_4$As$_4$, synthesized for the first time. The new material exhibits bulk SC at 35.2 K and Eu$^{2+}$-spin ferromagnetic ordering at 15.5 K, demonstrating that it is a new robust ferromagnetic superconductor.

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preprint2016arXiv

Non-monotonic anisotropy in charge conduction induced by antiferrodistortive transition in metallic SrTiO$_{3}$

Cubic SrTiO$_{3}$ becomes tetragonal below 105 K. The antiferrodistortive (AFD) distortion leads to clockwise and counter-clockwise rotation of adjacent TiO$_{6}$ octahedra. This insulator becomes a metal upon the introduction of extremely low concentration of n-type dopants. However, signatures of the structural phase transition in charge conduction have remained elusive. Employing the Montgomery technique, we succeed in resolving the anisotropy of charge conductivity induced by the AFD transition, in the presence of different types of dopants. We find that the slight lattice distortion ($<6 \times 10^{-4}$) gives rise to a twenty percent anisotropy in charge conductivity, in agreement with the expectations of band calculations. Application of uniaxial strain amplifies the detectable anisotropy by disfavoring one of the three possible tetragonal domains. In contrast with all other known anisotropic Fermi liquids, the anisotropy has opposite signs for elastic and inelastic scattering. Increasing the concentration of dopants leads to a drastic shift in the temperature of the AFD transition either upward or downward. The latter result puts strong constraints on any hypothetical role played by the AFD soft mode in the formation of Cooper pairs and the emergence of superconductivity in SrTiO$_3$.

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preprint2016arXiv

Superconductivity and Ferromagnetism in Hole-Doped RbEuFe$_4$As$_4$

We discover a robust coexistence of superconductivity and ferromagnetism in an iron arsenide RbEuFe$_4$As$_4$. The new material crystallizes in an intergrowth structure of RbFe$_2$As$_2$ and EuFe$_2$As$_2$, such that the Eu sublattice turns out to be primitive instead of being body-centered in EuFe$_2$As$_2$. The FeAs layers, featured by asymmetric As coordinations, are hole doped due to charge homogenization. Our combined measurements of electrical transport, magnetization and heat capacity unambiguously and consistently indicate bulk superconductivity at 36.5 K in the FeAs layers and ferromagnetism at 15 K in the Eu sublattice. Interestingly, the Eu-spin ferromagnetic ordering belongs to a rare third-order transition, according to the Ehrenfest classification of phase transition. We also identify an additional anomaly at $\sim$ 5 K, which is possibly associated with the interplay between superconductivity and ferromagnetism.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Quantum oscillations, thermoelectric coefficients and the Fermi surface of semi-metallic WTe2

We present a study of angle-resolved quantum oscillations of electric and thermoelectric transport coefficients in semi-metallic WTe$_{2}$, which has the particularity of displaying a large B$^{2}$ magneto-resistance. The Fermi surface consists of two pairs of electron-like and hole-like pockets of equal volumes in a "Russian doll" structure. Carrier density, Fermi energy, mobility and the mean-free-path of the system are quantified. An additional frequency is observed above a threshold field and attributed to magnetic breakdown across two orbits. In contrast to all other dilute metals, the Nernst signal remains linear in magnetic field even in the high-field ($ω_cτ\gg 1$) regime. Surprisingly, none of the pockets extend across the c-axis of the first Brillouin zone, making the system a three-dimensional metal with moderate anisotropy in Fermi velocity yet a large anisotropy in mean-free-path.

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preprint2014arXiv

Anomalous Eu Valence State and Superconductivity in Undoped Eu3Bi2S4F4

We have synthesized a novel europium bismuth sulfofluoride, Eu3Bi2S4F4, by solid-state reactions in sealed evacuated quartz ampoules. The compound crystallizes in a tetragonal lattice (space group I4/mmm, a = 4.0771(1) A, c = 32.4330(6) A, and Z = 2), in which CaF2-type Eu3F4 layers and NaCl-like BiS2 bilayers stack alternately along the crystallographic c axis. There are two crystallographically distinct Eu sites, Eu(1) and Eu(2) at the Wyckoff positions 4e and 2a, respectively. Our bond-valence-sum calculation, based on the refined structural data, indicates that Eu(1) is essentially divalent, whilst Eu(2) has an average valence of +2.64(5). This anomalous Eu valence state is further confirmed and supported, respectively, by Mossbauer and magnetization measurements. The Eu3+ components donate electrons into the conduction bands that are mainly composed of Bi- 6px and 6py states. Consequently, the material itself shows metallic conduction, and superconducts at 1.5 K without extrinsic chemical doping.

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preprint2014arXiv

Charge-density wave, superconductivity and $f$-electron valence instability in EuBiS$_2$F

Superconductivity (SC) and charge-density wave (CDW) are two contrasting yet relevant collective electronic states which have received sustained interest for decades. Here we report that, in a layered europium bismuth sulfofluoride, EuBiS$_2$F, a CDW-like transition occurs at 280 K, below which SC emerges at 0.3 K, without any extrinsic doping. The Eu ions were found to exhibit an anomalously temperature-independent mixed valence of about +2.2, associated with the formation of CDW. The mixed valence of Eu gives rise to self electron doping into the conduction bands mainly consisting of the in-plane Bi-6$p$ states, which in turn brings about the CDW and SC. In particular, the electronic specific-heat coefficient is enhanced by ~ 50 times, owing to the significant hybridizations between Eu-4$f$ and Bi-6$p$ electrons, as verified by band-structure calculations. Thus, EuBiS$_2$F manifests itself as an unprecedented material that simultaneously accommodates SC, CDW and $f$-electron valence instability.

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preprint2014arXiv

Electronic phase diagram in the new BiS2-based Sr1-xLaxFBiS2 system

In this paper, we systematically study the electron doping effect in a new BiS2-based system Sr1-xLaxFBiS2(0<x<0.7) through multiple techniques of X-ray diffraction, electrical transport, magnetic susceptibility, and Hall effect measurements. The parent compound SrFBiS2 is found to possess a semiconducting-like ground state, with thermally activation energy Eg=38 meV. By the partial substitution of La for Sr, superconductivity emerges when x > 0.3, reaching its maximal superconducting transition temperature Tc=3.5 K at x=0.55. In the normal state of superconducting samples, it is clearly seen that there exists a crossover from metallic to semiconducting state below a temperature Tmin, which shifts to lower temperatures with increasing La content. Based on these measurements, the associated electronic phase diagram of Sr1-xLaxFBiS2 system has thus been established.

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preprint2014arXiv

Possible spin frustration in Nd$_2$Ti$_2$O$_7$ probed by muon spin relaxation

Muon spin relaxation on Nd$_2$Ti$_2$O$_7$ (NTO) and NdLaTi$_2$O$_7$ (NLTO) compounds are presented. The time spectra for both compounds are as expected for the paramagnetic state at high temperatures, but deviate from the exponential function below about 100 K. The muon spin relaxation rate increases with decreasing temperature firstly, and then levels off below about 10 K, which is reminiscent of the frustrated systems. An enhancement of the relaxation rate by a longitudinal field in the paramagnetic state is observed for NTO, and eliminated by a magnetic dilution for the NLTO sample. This suggests that the spectral density is modified by a magnetic dilution and thus indicates that the spins behave cooperatively rather than individually. Zero-field measurement at 0.3 K indicates that the magnetic ground state for NTO is ferromagnetic.

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preprint2014arXiv

Sr$_{0.9}$K$_{0.1}$Zn$_{1.8}$Mn$_{0.2}$As$_{2}$: a ferromagnetic semiconductor with colossal magnetoresistance

A bulk diluted magnetic semiconductor (Sr,K)(Zn,Mn)$_{2}$As$_{2}$ was synthesized with decoupled charge and spin doping. It has a hexagonal CaAl$_{2}$Si$_{2}$-type structure with the (Zn,Mn)$_{2}$As$_{2}$ layer forming a honeycomb-like network. Magnetization measurements show that the sample undergoes a ferromagnetic transition with a Curie temperature of 12 K and \revision{magnetic moment reaches about 1.5 $μ_{B}$/Mn under $μ_0H$ = 5 T and $T$ = 2 K}. Surprisingly, a colossal negative magnetoresistance, defined as $[ρ(H)-ρ(0)]/ρ(0)$, up to $-$38\% under a low field of $μ_0H$ = 0.1 T and to $-$99.8\% under $μ_0H$ = 5 T, was observed at $T$ = 2 K. The colossal magnetoresistance can be explained based on the Anderson localization theory.

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preprint2014arXiv

Superconductivity in a Layered Ta4Pd3Te16 with PdTe2 Chains

Superconductivity in low-dimensional compounds has long attracted much interest. Here we report superconductivity in a low-dimensional ternary telluride Ta4Pd3Te16 in which the repeating layers contain edge-sharing octahedrally-coordinated PdTe2 chains along the crystallographic b axis. Measurements of electrical resistivity, magnetic susceptibility and specific heat on the Ta4Pd3Te16 crystals, grown via a self-flux method, consistently demonstrate bulk superconductivity at 4.6 K. Further analyses of the data indicate significant electron-electron interaction, which allows electronic Cooper pairing in the present system.

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preprint2013arXiv

K and Mn co-doped BaCd2As2: a hexagonal structured bulk diluted magnetic semiconductor with large magnetoresistance

A bulk diluted magnetic semiconductor was found in the K and Mn co-doped BaCd2As2 system. Different from recently reported tetragonal ThCr2Si2-structured II-II-V based(Ba,K)(Zn,Mn)2As2, the Ba1-yKyCd2-xMnxAs2 system has a hexagonal CaAl2Si2-type structure with the Cd2As2 layer forming a honeycomb-like network. The Mn concentration reaches up to its x ? 0.4. Magnetization measurements show that the samples undergo ferromagnetic transitions with Curie temperature up to 16 K. With low coercive field less than 10 Oe and large magnetoresistence of about -70%, the hexagonal structured Ba1-yKyCd2-xMnxAs2 can be served as a promising candidate for spin manipulations.

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preprint2013arXiv

Sr and Mn co-doped LaCuSO: A wide band gap oxide diluted magnetic semiconductor with TC around 200K

Here we report the synthesis of a bulk oxide diluted magnetic semiconductor (DMS) system La1-xSrxCu0.925Mn0.075SO (x=0, 0.025, 0.05, 0.075, and 0.1). As a wide band gap p-type oxide semiconductor, LaCuSO satisfies all the conditions forecasted theoretically to be a room temperature DMS. The Curie temperature (TC) is around 200K as x>0.05, which is among the highest TC record of known bulk DMS materials up to now. The system provides a rare example of oxide DMS system with p-type conduction, which is important for formation of high temperature spintronic devices.

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preprint2013arXiv

Superconductivity induced by La doping in Sr1-xLaxFBiS2 system

Through a combination of X-ray diffraction, electrical transport, magnetic susceptibility, and heat capacity measurements, we report the effect of La doping on Sr in the newly discovered SrFBiS2 system. Superconducting transition with critical temperature Tc of 2.8 K, developed from a semiconducting-like normal state, was found in Sr0.5La0.5FBiS2. A strong diamagnetic signal and a clear specific heat anomaly associated with this transition were observed, confirming bulk superconductivity. The upper critical field Hc2(0) was estimated to be 1 Tesla by using the Ginzburg-Landau approach. Our experiments therefore demonstrate that bulk superconductivity can be achieved by electron doping in the SrFBiS2 system.

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preprint2013arXiv

Superconductivity, charge- or spin-density wave, and metal-nonmetal transition in BaTi$_{2}$(Sb$_{1-x}$Bi$_{x}$)$_{2}$O

We have performed an isovalent substitution study in a layered titanium oxypnictide system BaTi$_{2}$(Sb$_{1-x}$Bi$_{x}$)$_{2}$O (0$\leq x\leq$ 0.40) by the measurements of x-ray diffraction, electrical resistivity and magnetic susceptibility. The parent compound BaTi$_{2}$Sb$_{2}$O is confirmed to exhibit superconductivity at 1.5 K as well as charge- or spin-density wave (CDW/SDW) ordering below 55 K. With the partial substitution of Sb by Bi, the lattice parameters $a$, $c$ and $c/a$ all increase monotonically, indicating negative chemical pressure and lattice distortion on the (super)conducting Ti$_2$Sb$_2$O-layers. The Bi doping elevates the superconducting transition temperature to its maximum $T_c$=3.7 K at $x=$0.17, and then $T_c$ decreases gradually with additional Bi doping. A metal-to-nonmetal transition takes place around $x$=0.3, and superconductivity at $\sim$1K exists at the nonmetal side. The CDW/SDW anomaly, in comparison, is rapidly suppressed by the Bi doping, and vanishes for $x\geq$0.17. The results are discussed in terms of negative chemical pressure and disorder effect.

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preprint2012arXiv

Pressure tuning of Fermi surface topology of optimally doped BaFe$_{1.9}$Ni$_{0.1}$As$_{2}$

The superconducting, transport, and structural properties of optimally electron-doped BaFe$_{1.9}$Ni$_{0.1}$As$_{2}$ are investigated by combining the electrical resistance and synchrotron X-ray diffraction measurements at high pressures. The superconducting transition temperature of this system is found to decrease in a similar way of the axial ratio of $c/a$ with increasing pressure but vanishing at a critical pressure of 7.5 GPa where $c/a$ has a dip and an isostructural transformation from a tetragonal to a collapsed tetragonal phase takes place. The resistance is found to obey a linear temperature dependence, evidencing the antiferromagnetic spin-fluctuations transport mechanism. The pressure effects are interpreted within the framework of pressure-induced Fermi surface topology modification in which pressure suppresses both the quasiparticle effective mass and the strength of the antiferromagnetic spin fluctuations leading to the reduction of superconductivity, accordingly. The absent superconductivity in the collapsed tetragonal phase is suggested to result from the complete suppression of the antiferromagnetic spin fluctuations.

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preprint2010arXiv

Comparative study on the thermoelectric effect of parent oxypnictides La$T$AsO ($T$ = Fe, Ni)

The thermopower and Nernst effect were investigated for undoped parent compounds LaFeAsO and LaNiAsO. Both thermopower and Nernst signal in iron-based LaFeAsO are significantly larger than those in nickel-based LaNiAsO. Furthermore, abrupt changes in both thermopower and Nernst effect are observed below the structural phase transition temperature and spin-density wave (SDW) type antiferromagnetic (AFM) order temperature in Fe-based LaFeAsO. On the other hand, Nernst effect is very small in the Ni-based LaNiAsO and it is weakly temperature-dependent, reminiscent of the case in normal metals. We suggest that the effect of SDW order on the spin scattering rate should play an important role in the anomalous temperature dependence of Hall effect and Nernst effect in LaFeAsO. The contrast behavior between the LaFeAsO and LaNiAsO systems implies that the LaFeAsO system is fundamentally different from the LaNiAsO system and this may provide clues to the mechanism of high $T_c$ superconductivity in the Fe-based systems.

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preprint2010arXiv

Effect of a Zn impurity on T_c and its implication to pairing symmetry in LaFeAsO$_{1-x}$F$_x$

The effect of non-magnetic Zn impurity on superconductivity in LaFe$_{1-y}$Zn$_y$AsO$_{1-x}$F$_x$ system is studied systematically. In the presence of Zn impurity, the superconducting transition temperature increases in the under-doped regime, remains unchanged in the optimally doped regime, and is severely suppressed in the over-doped regime. Our results suggest a switch of the symmetry of the superconducting order parameters from a $s$-wave to $s_{\pm}$ or $d$-wave states as the charge carrier doping increases in FeAs-based superconductors.

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preprint2010arXiv

Suppression of $T_c$ by Zn impurity in the electron-type LaFe$_{0.925-y}$Co$_{0.075}$Zn$_y$AsO system

The effect of non-magnetic Zn impurity on superconductivity in electron-type pnictide superconductor LaFe$_{0.925-y}$Co$_{0.075}$Zn$_y$AsO is studied systematically. The optimally doped LaFe$_{0.925}$Co$_{0.075}$AsO without Zn impurity exhibits superconductivity at $T_c^{mid}$ of 13.2 K, where $T_c^{mid}$ is defiend as the mid-point in the resistive transition. In the presence of Zn impurity, the superconducting transition temperature, $T_c^{mid}$, is severely suppressed. The result is consistent with the theoretic prediction on the effect of non-magnetic impurity in the scenario of $s_{\pm}$ pairing, but it is in sharp contrast to the previous report on the effect of Zn impurity in the F-doped systems. The possible interpretation of the different effects of Zn impurity on superconductivity in different systems is discussed.

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preprint2009arXiv

Evidence of Magnetically Driven Structural Phase Transition in Parent Compounds RFeAsO (R = La, Sm, Gd, Tb): study of low-temperature X-ray diffraction

We report measurements of structural phase transition of four parent compounds $R$FeAsO ($R$ = La, Sm, Gd, and Tb) by means of low-temperature X-ray diffraction (XRD). Magnetic transition temperatures associated with Fe ions ($T_{N1}$) are also determined from the temperature dependence of resistivity. As $R$ is changed from La, through Sm and Gd, to Tb, both the c-axis and a-axis lattice constants decrease significantly. Meanwhile both the structural phase transition temperature ($T_S$) and $T_{N1}$ decrease monotonously. It is also found that the temperature gap between $T_S$ and $T_{N1}$ becomes smaller when the distance between FeAs layer becomes shorter. This result is consistent with magnetically driven structural phase transition and suggests that the dimensionality have an important effect on the AFM ordering.

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