arXiv subjects

Kuan Li

Publications and source records attributed to Kuan Li.

At least 55 records · Page 3Linked to original sources

arXiv2024

Revealing the nontrivial topological surface states of catalysts for effective photochemical carbon dioxide conversion

Topological semimetals with protected surface states mark a new paradigm of research beyond the early landmarks of band-structure engineering, allowing fabrication of efficient catalyst to harness the rich metallic surface states to activate specific chemical processes. Herein, we demonstrate a facile solid-phase method for in-situ doping of Ir at the Os sites in the Os3Sn7, an alloy with topological states, which significantly improves the photocatalytic performance for the reduction of CO2 to CO and CH4. Experimental evidence combined with theoretical calculations reveal that the nontrivial topological surface states greatly accelerate charge-separation/electron-enrichment and adsorption/activation of CO2 molecules, rendering highly efficient reaction channels to stimulate the formation of *COOH and *CO, as well CHO*. This work shows the promise of achieving high photocatalytic performances with synthesizing topological catalysts and provides hints on the design of novel topological catalysts with superior photoactivity towards the CO2 reduction reaction.

cond-mat.mtrl-sci↗

arXiv2024

Structural and Superconducting Properties in the Te-doped Spinel CuRh2Se4

In this paper, we discuss the impact of tellurium (Te) doping on the spinel superconductor CuRh2Se4. We conducted a comprehensive evaluation of the structural and superconducting properties of the system using various techniques, including X-ray diffraction (XRD), resistivity, magnetization, and specific heat measurements. Based on our XRD analysis, we found that the spinel superconductor CuRh2Se4-xTex crystallizes in the space group Fd3m(227) with x in the region of 0 to 0.28, while the layered compound CuRh2Se4-xTex crystallizes in the space group P3m1 (164) with x in the region of 2.8 to 4.0. The upper critical magnetic field can be increased from 0.95(2) T for CuRh2Se4 to 3.44(1) T for CuRh2Se3.72Te0.28 by doping with elemental Te. However, the layered compound CuRh2Se4-xTex did not exhibit superconducting properties. Besides, the specific heat measurements of CuRh2Se4-xTex (x = 0, 0.1, 0.28) indicate that the Te element doping affects the electronic structure and interactions of the material and breaks the stability of the superconducting pairing, which leads to a decrease in the Tc. Finally, we show the electronic phase diagram of Tc with Te doping to summarise our findings.

cond-mat.supr-con↗

arXiv2024

Superconductivity of the New Medium-Entropy Alloy V4Ti2W with a Body-Centered Cubic Structure

Medium- and high-entropy alloy (MEA and HEA) superconductors have attracted considerable interest since their discovery. This paper reports the superconducting properties of ternary tungsten-containing MEA V4Ti2W for the first time. V4Ti2W is a type II superconductor with a body-centered cubic (BCC) structure. Experimental results of resistivity, magnetization, and heat capacity indicate that the superconducting transition temperature of the MEA V4Ti2W is roughly 5.0 K. The critical magnetic fields at the upper and lower ends are 9.93(2) T and 40.7(3) mT, respectively. Interestingly, few BCC MEA superconductors with VEC greater than 4.8 have been found. The addition of tungsten leads to a VEC of 4.83 e/a for V4Ti2W, which is rarely higher than the 4.8 value. Adding tungsten element expands the variety of MEA alloys, which may improve the microstructure and mechanical properties of materials and even superconducting properties. This material could potentially offer a new platform for the investigation of innovative MEA and HEA superconductors.

cond-mat.supr-con↗

arXiv2023

Superconductivity in the high-entropy ceramics Ti0.2Zr0.2Nb0.2Mo0.2Ta0.2Cx with possible nontrivial band topology

Topological superconductors have drawn significant interest from the scientific community due to the accompanying Majorana fermions. Here, we report the discovery of electronic structure and superconductivity in high-entropy ceramics Ti0.2Zr0.2Nb0.2Mo0.2Ta0.2Cx (x = 1 and 0.8) combined with experiments and first-principles calculations. The Ti0.2Zr0.2Nb0.2Mo0.2Ta0.2Cx high-entropy ceramics show bulk type-II superconductivity with Tc about 4.00 K (x = 1) and 2.65 K (x = 0.8), respectively. The specific heat jump is equal to 1.45 (x = 1) and 1.52 (x = 0.8), close to the expected value of 1.43 for the BCS superconductor in the weak coupling limit. The high-pressure resistance measurements show that a robust superconductivity against high physical pressure in Ti0.2Zr0.2Nb0.2Mo0.2Ta0.2C, with a slight Tc variation of 0.3 K within 82.5 GPa. Furthermore, the first-principles calculations indicate that the Dirac-like point exists in the electronic band structures of Ti0.2Zr0.2Nb0.2Mo0.2Ta0.2C, which is potentially a topological superconductor. The Dirac-like point is mainly contributed by the d orbitals of transition metals M and the p orbitals of C. The high-entropy ceramics provide an excellent platform for the fabrication of novel quantum devices, and our study may spark significant future physics investigations in this intriguing material.

cond-mat.supr-con↗

arXiv2023

Superconductivity in the cobalt-doped V3Si A15 intermetallic compound

The A15 structure of superconductors is a prototypical type-II superconductor that has generated considerable interest since the early history of superconducting materials. This paper discusses the superconducting properties of previously unreported V3-xCoxSi alloys. It is found that the lattice parameter decreases with increasing cobalt-doped content and leads to an increased residual resistivity ratio (RRR) value of the V3-xCoxSi system. Meanwhile, the superconducting transition temperature (Tc) cobalt-doped content. Furthermore, the fitted data show that the increase of cobalt-doped content also reduces the lower/upper critical fields of the V3-xCoxSi system. Type-II superconductivity is demonstrated on all V3-xCoxSi samples. With higher Co-doped content, V3-xCoxSi alloys may have superconducting and structural phase transitions at low-temperature regions. As the electron/atom (e/a) ratio increases, the Tc variation trend of V3Si is as pronounced as in crystalline alloys and monotonically follows the trend observed for amorphous superconductors.

cond-mat.supr-con↗

arXiv2023

Superconductivity in the bcc-type High-entropy Alloy TiHfNbTaMo

X-ray powder diffraction, electrical resistivity, magnetization, and thermodynamic measurements were conducted to investigate the structure and superconducting properties of TiHfNbTaMo, a novel high-entropy alloy possessing a valence electron count (VEC) of 4.8. The TiHfNbTaMo HEA was discovered to have a body-centered cubic structure and a microscopically homogeneous distribution of the constituent elements. This material shows type-II superconductivity with Tc = 3.42 K, lower critical field with 22.8 mT, and upper critical field with 3.95 T. Low-temperature specific heat measurements show that the alloy is a conventional s-wave type with a moderately coupled superconductor. First-principles calculations show that the density of states (DOS) of the TiHfNbTaMo alloy is dominated by hybrid d orbitals of these five metal elements. Additionally, the TiHfNbTaMo HEA exhibits three van Hove singularities. Furthermore, the VEC and the composition of the elements (especially the Nb elemental content) affect the Tc of the bcc-type HEA.

cond-mat.supr-con↗

arXiv2023

MS-UNet-v2: Adaptive Denoising Method and Training Strategy for Medical Image Segmentation with Small Training Data

Models based on U-like structures have improved the performance of medical image segmentation. However, the single-layer decoder structure of U-Net is too "thin" to exploit enough information, resulting in large semantic differences between the encoder and decoder parts. Things get worse if the number of training sets of data is not sufficiently large, which is common in medical image processing tasks where annotated data are more difficult to obtain than other tasks. Based on this observation, we propose a novel U-Net model named MS-UNet for the medical image segmentation task in this study. Instead of the single-layer U-Net decoder structure used in Swin-UNet and TransUnet, we specifically design a multi-scale nested decoder based on the Swin Transformer for U-Net. The proposed multi-scale nested decoder structure allows the feature mapping between the decoder and encoder to be semantically closer, thus enabling the network to learn more detailed features. In addition, we propose a novel edge loss and a plug-and-play fine-tuning Denoising module, which not only effectively improves the segmentation performance of MS-UNet, but could also be applied to other models individually. Experimental results show that MS-UNet could effectively improve the network performance with more efficient feature learning capability and exhibit more advanced performance, especially in the extreme case with a small amount of training data, and the proposed Edge loss and Denoising module could significantly enhance the segmentation performance of MS-UNet.

eess.IV↗

arXiv2023

Superconductivity in the medium-entropy alloy TiVNbTa with a body-centered cubic structure

Here we report the TiVNbTa medium-entropy alloy (MEA) superconductor with the mixed 3d - 5d elements synthesized by an arc-melting method. The TiVNbTa material has a body-centered cubic structure. The superconducting properties of TiVNbTa were studied by resistivity, magnetic susceptibility, and specific heat measurements. The experimental results show that the bulk superconducting phase transition temperature of TiVNbTa is about 4.65 K, and the upper and lower critical fields are 49.3(4) mT and 5.9(5) T, respectively, which indicates TiVNbTa is a type-II superconductor. First-principles calculations show that the d electrons of Ti, V, Nb, and Ta atoms play a significant role near the Fermi level. The results show TiVNbTa is a traditional s-wave superconductor.

cond-mat.supr-con↗

arXiv2023

Extremely strong coupling s-wave superconductivity in the medium-entropy alloy TiHfNbTa

Here we report a TiHfNbTa bulk medium-entropy alloy (MEA) superconductor crystallized in the body-centered cubic structure, which is synthesized by an arc melting method. Superconducting properties of the TiHfNbTa are studied by employing magnetic susceptibility, resistivity, and specific heat measurements. Experimental results show a bulk superconducting transition temperature (Tc) of around 6.75 K. The lower and upper crit-ical fields for TiHfNbTa are 45.8 mT and 10.46 T, respectively. First-principles calculations show that the d electron of Ti, Hf, Nb, and Ta is the main contribution near the Fermi level. Our results indicate that the superconductivity is a conven-tional s-wave type with extremely strong coupling. The extremely strong coupling behavior in the s-wave type TiHfNbTa MEA superconductor is unusual because it generally happens in cuprates, pnictides, and other unconventional superconductors.

cond-mat.supr-con↗

arXiv2023

Discovery of the high-entropy carbide ceramic topological superconductor candidate (Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C

High-entropy ceramics (HECs) are solid solutions of inorganic compounds with one or more Wyckoff sites shared by equal or near-equal atomic ratios of multi-principal elements. Material design and property tailoring possibilities emerge from this new class of materials. Here, we report the discovery of superconductivity around 2.35 K and topological properties in the (Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C high-entropy carbide ceramic (HECC), which has not been observed before in any of the investigated HECC. Density functional theory calculations showed that six type-II Dirac points exist in (Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C, which mainly contributed from the t2g orbitals of transition metals and the p orbitals of C. Due to the stability of the structure, we also observed robust superconductivity under pressure in this HEC superconductor. This study expands the physical properties of HECs, which may become a new material platform for superconductivity research, especially for studying the coupling between superconductivity and topological physics.

cond-mat.supr-con↗

arXiv2023

Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN

Benefiting from the message passing mechanism, Graph Neural Networks (GNNs) have been successful on flourish tasks over graph data. However, recent studies have shown that attackers can catastrophically degrade the performance of GNNs by maliciously modifying the graph structure. A straightforward solution to remedy this issue is to model the edge weights by learning a metric function between pairwise representations of two end nodes, which attempts to assign low weights to adversarial edges. The existing methods use either raw features or representations learned by supervised GNNs to model the edge weights. However, both strategies are faced with some immediate problems: raw features cannot represent various properties of nodes (e.g., structure information), and representations learned by supervised GNN may suffer from the poor performance of the classifier on the poisoned graph. We need representations that carry both feature information and as mush correct structure information as possible and are insensitive to structural perturbations. To this end, we propose an unsupervised pipeline, named STABLE, to optimize the graph structure. Finally, we input the well-refined graph into a downstream classifier. For this part, we design an advanced GCN that significantly enhances the robustness of vanilla GCN without increasing the time complexity. Extensive experiments on four real-world graph benchmarks demonstrate that STABLE outperforms the state-of-the-art methods and successfully defends against various attacks.

cs.LG↗

arXiv2023

Direct statistical simulation of Lorenz96 system in model reduction approaches

Direct statistical simulation (DSS) of nonlinear dynamical systems bypasses the traditional route of accumulating statistics by lengthy direct numerical simulations (DNS) by solving the equations that govern the statistics themselves. DSS suffers, however, from the curse of dimensionality as the statistics (such as correlations) generally have higher dimension than the underlying dynamical variables. Here we investigate two approaches to reduce the dimensionality of DSS, illustrating each method with numerical experiments with the Lorenz-96 dynamical system. The forms of DSS chosen here involve approximate closures at second and third order in the equal time cumulants. We demonstrate significant reduction in computational effort that can be achieved without sacrificing the accuracy of DSS. The methods developed here can be applied to turbulent fluid and magnetohydrodynamical systems.

physics.flu-dyn↗

arXiv2022

Ta4CoSi: a Tantalum-rich superconductor with a honeycomb network structure

The crystal structure of solid-state materials with unique lattices is considered one of the main factors determining physical properties, including superconductivity. Materials with honeycomb lattices have inspired intense research interest for their novel properties. A previously unknown compound, Ta4CoSi, are discussed herein and its crystal structure and superconducting properties. It crystallizes in a CuAl2-type structure (space group P4/mcm, No. 124) with the lattice parameters a = b = 6.17755(7)Å and c = 4.98443(8) Å, featuring honeycomb networks of Ta-Ta in (110) plane. Superconductivity is observed below the critical temperature of 2.45 K, while lower and upper critical magnetic fields are 9.86 mT and 0.84 T, respectively. Experiments and theoretical calculations show that the honeycomb lattices significantly influence the superconducting properties. This material may thus provide a new platform for investigating the exotic superconductivity of honeycomb networks.

cond-mat.supr-con↗

arXiv2022

Negative Chemical Pressure Effect on Superconductivity and Charge Density Wave of Cu0.5Ir1-xZrxTe2

This study demonstrates the design and synthesis of Cu0.5Ir1-xZrxTe2 system by partial substitution of Ir with Zr acting as a negative chemical pressure. With the doping of Zr, the cell parameters significantly expand, signifying an effective negative chemical pressure. The experimental results found evidence that the charge density wave (CDW)-like order is immediately quenched by subtle Zr substitution for Ir and a classical dome-shape Tc(x) that peaked at 2.80 K can be observed. The optimal Cu0.5Ir0.95Zr0.05Te2 compound is a BCS-type superconductor and exhibits type-II SC. However, high Zr concentration can provoke disorder, inducing the reappearance of CDW order. The present study shows that the Cu0.5Ir1-xZrxTe2 system may provide a new platform for further understanding of multiple electronic orders in transition metal dichalcogenides.

cond-mat.supr-con↗

arXiv2022

Superconductivity with the enhanced upper critical field in the Pt-Doping CuRh2Se4 spinel

We report the effect of Pt doping on the superconductivity in CuRh2Se4 spinel using a combined experimental and theoretical study. Our XRD results reveal that the Cu(Rh1-xPtx)2Se4 crystallizes in the structure with a space group of Fd3-m (No. 227), and the lattice parameter a increases with Pt doping. The resistivity and magnetic susceptibility measurement results verify that the superconducting transition temperature (Tc) forms a dome-like shape with a maximum value of 3.84 K at x = 0.06. It is also observed that the Pt-doping slightly reduces the lower critical magnetic field from 220 Oe in CuRh2Se4 to 168 Oe in Cu(Rh0.94Pt0.06)2Se4, while it significantly enhances the upper critical magnetic field, reaching the maximum of 4.93 T in the Cu(Rh0.94Pt0.06)2Se4 sample. The heat capacity result indicates that the sample Cu(Rh0.91Pt0.09)2Se4 is a bulk superconductor. First-principles calculations suggest that the Pt-doping leads to a red-shift of a density of state peak near the Fermi level, consistent with the dome-like Tc observed experimentally.

cond-mat.supr-con↗

arXiv2021

Can neural networks predict dynamics they have never seen?

Neural networks have proven to be remarkably successful for a wide range of complicated tasks, from image recognition and object detection to speech recognition and machine translation. One of their successes is the skill in prediction of future dynamics given a suitable training set of data. Previous studies have shown how Echo State Networks (ESNs), a subset of Recurrent Neural Networks, can successfully predict even chaotic systems for times longer than the Lyapunov time. This study shows that, remarkably, ESNs can successfully predict dynamical behavior that is qualitatively different from any behavior contained in the training set. Evidence is provided for a fluid dynamics problem where the flow can transition between laminar (ordered) and turbulent (disordered) regimes. Despite being trained on the turbulent regime only, ESNs are found to predict laminar behavior. Moreover, the statistics of turbulent-to-laminar and laminar-to-turbulent transitions are also predicted successfully, and the utility of ESNs in acting as an early-warning system for transition is discussed. These results are expected to be widely applicable to data-driven modelling of temporal behaviour in a range of physical, climate, biological, ecological and finance models characterized by the presence of tipping points and sudden transitions between several competing states.

cs.LG↗

arXiv2021

Direct statistical simulation of the Lorenz63 system

We use direct statistical simulation (DSS) to find the low-order statistics of the well-known dynamical system, the Lorenz63 model. Instead of accumulating statistics from numerical simulation of the dynamical systems, we solve the equations of motion for the statistics themselves after closing them by making several different choices for the truncation. Fixed points of the statistics are obtained either by time evolving, or by iterative methods. Statistics so obtained are compared to those found by the traditional approach.

cond-mat.stat-mech↗

arXiv2021

Direct statistical simulation of low-order dynamo systems

In this paper we investigate the effectiveness of direct statistical simulation (DSS) for two low-order models of dynamo action. The first model, which is a simple model of solar and stellar dynamo action, is third-order and has cubic nonlinearities whilst the second has only quadratic nonlinearities and describes the interaction of convection and an aperiodically reversing magnetic field. We show how DSS can be utilised to solve for the statistics of these systems of equations both in the presence and the absence of stochastic terms, by truncating the cumulant hierarchy at either second or third order. We compare two different techniques for solving for the statistics, timestepping -- which is able to locate only stable solutions of the equations for the statistics and direct detection of the fixed points. We develop a complete methodology and symbolic package in Python for deriving the statistical equations governing the Low-order dynamic systems in cumulant expansions. We demonstrate that although direct detection of the fixed points is efficient and accurate for DSS truncated at second order, the addition of higher order terms leads to the inclusion of many unstable fixed points that may be found by direct detection of the fixed point by iterative methods. In those cases timestepping is a more robust protocol for finding meaninful solutions to DSS.

astro-ph.SR↗