arXiv subjects

Yu Song

Publications and source records attributed to Yu Song.

At least 127 records · Page 7Linked to original sources

arXiv2021

Spin dynamics in NaFeAs and NaFe$_{0.53}$Cu$_{0.47}$As probed by resonant inelastic X-ray scattering

The parent compounds of iron-based superconductors are magnetically-ordered bad metals, with superconductivity appearing near a putative magnetic quantum critical point. The presence of both Hubbard repulsion and Hund's coupling leads to rich physics in these multiorbital systems, and motivated descriptions of magnetism in terms of itinerant electrons or localized spins. The NaFe$_{1-x}$Cu$_x$As series consists of magnetically-ordered bad metal ($x=0$), superconducting ($x\approx0.02$) and magnetically-ordered semiconducing/insulating ($x\approx0.5$) phases, providing a platform to investigate the connection between superconductivity, magnetism and electronic correlations. Here we use X-ray absorption spectroscopy and resonant inelastic X-ray scattering to study the valence state of Fe and spin dynamics in two NaFe$_{1-x}$Cu$_x$As compounds ($x=0$ and 0.47). We find that magnetism in both compounds arises from Fe$^{2+}$ atoms, and exhibits underdamped dispersive spin waves in their respective ordered states. The dispersion of spin excitations in NaFe$_{0.53}$Cu$_{0.47}$As is consistent with being quasi-one-dimensional. Compared to NaFeAs, the band top of spin waves in NaFe$_{0.53}$Cu$_{0.47}$As is slightly softened with significantly more spectral weight of the spin excitations. Our results indicate the spin dynamics in NaFe$_{0.53}$Cu$_{0.47}$As arise from localized magnetic moments and suggest the iron-based superconductors are proximate to a correlated insulating state with localized iron moments.

cond-mat.str-el↗

arXiv2020

Short-range nematic fluctuations in Sr1-xNaxFe2As2 superconductors

Interactions between nematic fluctuations, magnetic order and superconductivity are central to the physics of iron-based superconductors. Here we report on in-plane transverse acoustic phonons in hole-doped Sr$_{1-x}$Na$_x$Fe$_2$As$_2$ measured via inelastic X-ray scattering, and extract both the nematic susceptibility and the nematic correlation length. By a self-contained method of analysis, for the underdoped ($x=0.36$) sample, which harbors a magnetically-ordered tetragonal phase, we find it hosts a short nematic correlation length $ξ$ ~ 10 $Å$ and a large nematic susceptibility $χ_{\rm nem}$. The optimal-doped ($x=0.55$) sample exhibits weaker phonon softening effects, indicative of both reduced $ξ$ and $χ_{\rm nem}$. Our results suggest short-range nematic fluctuations may favor superconductivity, placing emphasis on the nematic correlation length for understanding the iron-based superconductors.

cond-mat.supr-con↗

arXiv2020

Origin of Irradiation Synergistic Effects in Silicon Bipolar Transistors: a Review

The practical damage of silicon bipolar devices subjected to mixed ionization and displacement irradiations is usually evaluated by the sum of separated ionization and displacement damages. However, recent experiments show clear difference between the practical and summed damages, indicating significant irradiation synergistic effects (ISEs). Understanding the behaviors and mechanisms of ISEs is essential to predict the practical damages. In this work, we first make a brief review on the state of the art, critically emphasizing on the difficulty encountered in previous models to understand the dose rate dependence of the ISEs. We then introduce in detail our models explaining this basic phenomenon, which can be described as follows. Firstly, we show our experimental works on PNP and NPN transistors. A variable neutron fluence and $γ$-ray dose setup is adopted. Fluence-dependent `tick'-like and sublinear dose profiles are observed for PNP and NPN transistors, respectively. Secondly, we describe our theoretical investigations on the positive ISE in NPN transistors. We propose an atomistic model of transformation and annihilation of $\rm V_2$ displacement defects in p-type silicon under ionization irradiation, which is totally different from the traditional picture of Coulomb interaction of oxide trapped charges in silica on charge carriers in irradiated silicon. The predicted novel dose and fluence dependences are fully verified by the experimental data. Thirdly, the mechanism of the observed negative ISE in PNP transistors is investigated in a similar way as in the NPN transistor case. The difference is that in n-type silicon, VO displacement defects also undergo an ionization-induced transformation and annihilation process. Our results show that, the evolution of displacement defects due to carrier-enhanced defect diffusion and reaction is the dominating mechanism of the ISEs.

physics.app-ph↗

arXiv2020

Ultra-Slow Dynamic Annealing of Neutron-induced Defects in n-type Silicon: Role of Charge Carriers

Neutron bombardments with equivalent fluence (1$\times$10$^{10}$ cm$^{-2}$) and different fluxes ($2.5\times$10$^5$ cm$^{-2}$s$^{-1}$ to $1\times$10$^7$ cm$^{-2}$s$^{-1}$) have been performed on three kinds of bipolar devices with n-type silicon as active regions. The measured increase of base currents and input bias currents are found to decrease with increasing neutron flux, implying that the strength of the dynamic annealing of divacancy defects in n-type silicon follows a positive flux dependence. Such a flux dependence is the same as that observed in ions implantation using protons, but the evident flux sensitivity in our experiment is 4 orders of magnitude lower than that of proton bombardment, despite the similarity in the masses and energies of the two particles. The huge discrepancy of flux range is attributed to the presence of vast charge carriers in proton bombardments, which strongly accelerate the dynamic annealing of defects by enhancing the diffusion velocity of Si interstitials and dissociation rate of defect clusters. Our work would contribute to the understanding of the defect annealing processes in silicon.

cond-mat.mtrl-sci↗

arXiv2020

In-plane uniaxial pressure-induced out-of-plane antiferromagnetic moment and critical fluctuations in BaFe$_2$As$_2$

A small in-plane external uniaxial pressure has been widely used as an effective method to acquire single domain iron pnictide BaFe$_2$As$_2$, which exhibits twin-domains without uniaxial strain below the tetragonal-to-orthorhombic structural (nematic) transition temperature $T_s$. Although it is generally assumed that such a pressure will not affect the intrinsic electronic/magnetic properties of the system, it is known to enhance the antiferromagnetic (AF) ordering temperature $T_N$ ($<T_s$) and create in-plane resistivity anisotropy above $T_s$. Here we use neutron polarization analysis to show that such a strain on BaFe$_2$As$_2$ also induces a static or quasi-static out-of-plane ($c$-axis) AF order and its associated critical spin fluctuations near $T_N/T_s$. Therefore, uniaxial pressure necessary to detwin single crystals of BaFe$_2$As$_2$ actually rotates the easy axis of the collinear AF order near $T_N/T_s$, and such effect due to spin-orbit coupling must be taken into account to unveil the intrinsic electronic/magnetic properties of the system.

cond-mat.supr-con↗

arXiv2020

Deep Learning-Based Automated Image Segmentation for Concrete Petrographic Analysis

The standard petrography test method for measuring air voids in concrete (ASTM C457) requires a meticulous and long examination of sample phase composition under a stereomicroscope. The high expertise and specialized equipment discourage this test for routine concrete quality control. Though the task can be alleviated with the aid of color-based image segmentation, additional surface color treatment is required. Recently, deep learning algorithms using convolutional neural networks (CNN) have achieved unprecedented segmentation performance on image testing benchmarks. In this study, we investigated the feasibility of using CNN to conduct concrete segmentation without the use of color treatment. The CNN demonstrated a strong potential to process a wide range of concretes, including those not involved in model training. The experimental results showed that CNN outperforms the color-based segmentation by a considerable margin, and has comparable accuracy to human experts. Furthermore, the segmentation time is reduced to mere seconds.

cs.CV↗

arXiv2020

Nature of the spin resonance mode in CeCoIn$_5$

Spin-fluctuation-mediated unconventional superconductivity can emerge at the border of magnetism, featuring a superconducting order parameter that changes sign in momentum space. Detection of such a sign-change is experimentally challenging, since most probes are not phase-sensitive. The observation of a spin resonance mode (SRM) from inelastic neutron scattering is often seen as strong phase-sensitive evidence for a sign-changing superconducting order parameter, by assuming the SRM is a spin-excitonic bound state. Here, we show that for the heavy fermion superconductor CeCoIn$_5$, its SRM defies expectations for a spin-excitonic bound state, and is not a manifestation of sign-changing superconductivity. Instead, the SRM in CeCoIn$_5$ likely arises from a reduction of damping to a magnon-like mode in the superconducting state, due to its proximity to magnetic quantum criticality. Our findings emphasize the need for more stringent tests of whether SRMs are spin-excitonic, when using their presence to evidence sign-changing superconductivity.

cond-mat.supr-con↗

arXiv2020

Learning from Sparse Datasets: Predicting Concrete's Strength by Machine Learning

Despite enormous efforts over the last decades to establish the relationship between concrete proportioning and strength, a robust knowledge-based model for accurate concrete strength predictions is still lacking. As an alternative to physical or chemical-based models, data-driven machine learning (ML) methods offer a new solution to this problem. Although this approach is promising for handling the complex, non-linear, non-additive relationship between concrete mixture proportions and strength, a major limitation of ML lies in the fact that large datasets are needed for model training. This is a concern as reliable, consistent strength data is rather limited, especially for realistic industrial concretes. Here, based on the analysis of a large dataset (>10,000 observations) of measured compressive strengths from industrially-produced concretes, we compare the ability of select ML algorithms to "learn" how to reliably predict concrete strength as a function of the size of the dataset. Based on these results, we discuss the competition between how accurate a given model can eventually be (when trained on a large dataset) and how much data is actually required to train this model.

cs.LG↗

arXiv2020

Stripe Antiferromagnetism and Disorder in the Mott Insulator NaFe$_{1-x}$Cu$_{x}$As ($x \lesssim 0.5$)

Neutron scattering measurements have demonstrated that the heavily Cu-doped NaFe$_{1-x}$Cu$_{x}$As compound behaves like a Mott insulator exhibiting both real space Fe-Cu stripes, as well as antiferromagnetism below a Néel temperature for $x\lesssim 0.5$. We have investigated evolution of structural and magnetic ordering using $^{23}$Na and $^{75}$As NMR for single crystals ($x$ = 0.39 and 0.48), confirming antiferromagnetism in the form of magnetic stripes. We show that end-chain defects in these stripes are the principal source of magnetic disorder and are responsible for cluster spin-glass transitions in both compounds, in the latter case coexistent with antiferromagnetism. Aided by our numerical simulation of the $^{75}$As spectra, we show that a staggered magnetization at the Fe sites is induced by non-magnetic Cu dopants.

cond-mat.str-el↗

arXiv2019

Invariant Cubature Kalman Filter for Monocular Visual Inertial Odometry with Line Features

To achieve robust and accurate state estimation for robot navigation, we propose a novel Visual Inertial Odometry(VIO) algorithm with line features upon the theory of invariant Kalman filtering and Cubature Kalman Filter (CKF). In contrast with conventional CKF, the state of the filter is constructed by a high dimensional Matrix Lie group and the uncertainty is represented using Lie algebra. To improve the robustness of system in challenging scenes, e.g. low-texture or illumination changing environments, line features are brought into the state variable. In the proposed algorithm, exponential mapping of Lie algebra is used to construct the cubature points and the re-projection errors of lines are built as observation function for updating the state. This method accurately describes the system uncertainty in rotation and reduces the linearization error of system, which extends traditional CKF from Euclidean space to manifold. It not only inherits the advantages of invariant filtering in consistency, but also avoids the complex Jacobian calculation of high-dimensional matrix. To demonstrate the effectiveness of the proposed algorithm, we compare it with the state-of-the-art filtering-based VIO algorithms on Euroc datasets. And the results show that the proposed algorithm is effective in improving accuracy and robustness of estimation.

cs.RO↗

arXiv2019

Strain-induced spin-nematic state and nematic susceptibility arising from $2\times2$ Fe clusters in KFe$_{0.8}$Ag$_{1.2}$Te$_2$

Spin nematics break spin-rotational symmetry while maintaining time-reversal symmetry, analogous to liquid crystal nematics that break spatial rotational symmetry while maintaining translational symmetry. Although several candidate spin nematics have been proposed, the identification and characterization of such a state remain challenging because the spin-nematic order parameter does not couple directly to experimental probes. KFe$_{0.8}$Ag$_{1.2}$Te$_2$ (K$_5$Fe$_4$Ag$_6$Te$_{10}$, KFAT) is a local-moment magnet consisting of well-separated 2$\times$2 Fe clusters, and in its ground state the clusters order magnetically, breaking both spin-rotational and time-reversal symmetries. Using uniform magnetic susceptibility and neutron scattering measurements we find a small strain induces sizable spin anisotropy in the paramagnetic state of KFAT, manifestly breaking spin-rotational symmetry while retaining time-reversal symmetry, resulting in a strain-induced spin-nematic state in which the $2\times2$ clusters act as the spin analogue of molecules in a liquid crystal nematic. The strain-induced spin anisotropy in KFAT allows us to probe its nematic susceptibility, revealing a divergent-like increase upon cooling, indicating the ordered ground state is driven by a spin-orbital entangled nematic order parameter.

cond-mat.str-el↗

arXiv2019

Gloss, Color and Topography Scanning for Reproducing a Painting's Appearance using 3D printing

High fidelity reproductions of paintings provide new opportunities to museums in preserving and providing access to cultural heritage. This paper presents an integrated system which is able to capture and fabricate color, topography and gloss of a painting, of which gloss capturing forms the most important contribution. A 3D imaging system, using fringe-encoded stereo imaging, is extended to capture spatially-varying gloss, utilizing specular reflectance polarization. The gloss is measured by sampling the specular reflection around Brewster's angle, where these reflections are effectively polarized, and can be separated from the unpolarized, diffuse reflectance. Off-center gloss measurements are calibrated relative to the center measurement. Off-specular gloss measurements, following from local variation of the surface normal, are masked based on the height map and corrected. Shadowed regions, caused by the 3D relief, are treated similarly. The area of a single capture is approximately 180x90mm at a resolution of 25x25micron. Aligned color, height, and gloss tiles are stitched together, registering overlapping color areas. These maps are inputs for a 3D printer. Two paintings were reproduced to verify the effectiveness and efficiency of the proposed system. One painting was scanned four times, consecutively rotated by 90 degrees, to evaluate the influence of the scanning system geometric configuration on the gloss measurement. Experimental results show that the method is sufficiently fast for practical application. The results can well be used for the purpose of physical reproduction and other applications needing first-order estimates of the appearance. Our method to extend appearance scanning with gloss measurements is a valuable addition in the quest for realistic reproductions, in terms of its practical applicability and its perceptual added value, when added to color and topography.

cs.GR↗

arXiv2019

Flat band magnetism and helical magnetic order in Ni-doped SrCo$_2$As$_2$

A series of Sr(Co$_{1-x}$Ni$_x$)$_2$As$_2$ single crystals was synthesized allowing a comprehensive phase diagram with respect to field, temperature, and chemical substitution to be established. Our neutron diffraction experiments revealed a helimagnetic order with magnetic moments ferromagnetically (FM) aligned in the $ab$ plane and a helimagnetic wavevector of $q=(0,0,0.56)$ for $x$ = 0.1. The combination of neutron diffraction and angle-resolved photoemission spectroscopy (ARPES) measurements show that the tuning of a flat band with $d_{x^2-y^2}$ orbital character drives the helimagnetism and indicates the possibility of a quantum order-by-disorder mechanism.

cond-mat.str-el↗

arXiv2019

Enhanced low-flux sensitivity (ELFS) effect of neutron-induced displacement damage in bipolar devices: physical mechanism and parametric model

Similar to the enhanced low-dose-rate sensitivity (ELDRS) effect of ionization damage, an enhanced low-flux senstivity (ELFS) effect has been reported in ions/neutron irradiation on n-type silicon or PNP transistors. However, the existing mechanism and simulation dominated by the diffusion dynamics give much higher transition flux than the experimental observations. In this work, we develop a new model based on the annealing of defect clusters for the ELFS effect. Simulations considering Si-interstitial-mediated inter-cluster interactions during their annealing processes successfully reproduce the ELFS effect. The ratio of Si interstitials captured by defect clusters to those dissipating off on the sample edges or re-merging into the bulk is found as the key parameter dominating the enhancement factor (EF) of the ELFS effect. We also establish a compact parametric model based on the mechanism, which is found to provide a good quantitative description of the experimental results. The model predicts the existence of nonsensitive regions at sufficiently low and high fluxes as well as a non-trivial fluence and temperature dependence of the enhancement factor.

physics.space-ph↗

arXiv2019

Solar-Sail Deep Space Trajectory Optimization Using Successive Convex Programming

This paper presents a novel methodology for solving the time-optimal trajectory optimization problem for interplanetary solar-sail missions using successive convex programming. Based on the non-convex problem, different convexification technologies, such as change of variables, successive linearization, trust regions and virtual control, are discussed to convert the original problem into the formulation of successive convex programming. Because of the free final-time, successive linearization is performed iteratively for the nonconvex terminal state constraints. After the convexification process, each of problems becomes a convex problem, which can be solved effectively. An augmented objective function is introduced to ensure the convergence performance and effectiveness of our algorithm. After that, algorithms are designed to solve the discrete sub-problems in a successive solution procedure. Finally, numerical results demonstrate the effectiveness and accuracy of our algorithms.

cs.CE↗

arXiv2019

Gradient-index Solar Sail and its Optimal Orbital Control

Solar sails with the capability of generating a tangential radiation pressure at the sun-pointing attitude, such as refractive sails can provide more efficient methods for attitude and orbital control of sailcraft. This paper presents the concept of gradient-index sail as an advanced class of refractive sail, which operates by guiding the solar radiation through a structure made of graded refractive index material. The design of the sail's refractive index distribution is performed by transformation optics, and the resultant index realized by the effective refractive index of non-resonant bulk metamaterials made of silica. The performance of the sail was evaluated by using ray tracing for a broad spectrum of solar radiation under the normal incidence angle, which showed an efficiency of 90.5% for generation of a tangential radiation pressure. We also studied the orbital control of the tangential-radiation-pressure-generating sails, and showed that the full orbital control, including the modification of orbital axes, eccentricity, and inclination can be applied by changing the attitude of the sail merely around the sun-sail axis, while the sail keeps the sun-pointing attitude at every point of the orbit.

physics.space-ph↗

arXiv2019

Mechanism of Synergistic Effects of Neutron- and Gamma-Ray-Radiated PNP Bipolar Transistors

The synergistic effects of neutron and gamma ray radiated PNP transistors are systematically investigated as functions of the neutron fluence, gamma ray dose, and dose rate. We find that the damages show a `tick'-like dependence on the gamma ray dose after the samples are radiated by neutrons. Two negative synergistic effects are derived, both of which have similar magnitudes as the ionization damage (ID) itself. The first one depends linearly on the gamma ray dose, whose slope depends quadratically on the initial displacement damage (DD) and can be attributed to the healing of neutron-radiation-induced defects in silicon. The second one has an exponential decay with the gamma ray dose, whose amplitude shows a rather strong enhanced low-dose-rate sensitivity (ELDRS) effect and can be attributed to the passivation of neutron-induced defects near the silica/silicon interface by the gamma-ray-generated protons in silica, which can penetrate the silica/silicon interface to passivate the neutron-induced defects in silicon. The simulated results based on the proposed model match the experimental data very well, but differ from previous model, which does not assume annihilation or passivation of the displacement defects. The unraveled defect annealing mechanism is important because it implies that displacement damages can be repaired by gamma ray radiation or proton diffusion, which can have important device applications in the space or other extreme environments.

physics.app-ph↗

arXiv2019

Impact of the first order antiferromagnetic phase transition on the paramagnetic spin excitations and nematic phase of SrFe$_2$As$_2$

Understanding the nature of the electronic nematic phase in iron pnictide superconductors is important for elucidating its impact on high-temperature superconductivity. Here we use transport and inelastic neutron scattering to study spin excitations and in-plane resistivity anisotropy in uniaxial pressure detwinned BaFe$_2$As$_2$ and SrFe$_2$As$_2$, the parent compounds of iron pnictide superconductors. While BaFe$_2$As$_2$ exhibits weakly first order tetragonal-to-orthorhombic structural and antiferromagnetic (AF) phase transitions below $T_s > T_N\approx 138$ K, SrFe$_2$As$_2$ has strongly coupled first order structural and AF transitions below $T_s= T_N\approx 210$ K. We find that the direct signatures of the nematic phase persist to lower temperatures above the phase transition in the case of SrFe$_2$As$_2$ compared to BaFe$_2$As$_2$. Our findings support the conclusion that the strongly first-order nature of the magnetic transition in SrFe$_2$As$_2$ weakens the nematic phase and resistivity anisotropy in the system.

cond-mat.supr-con↗