arXiv subjects

Xiaolong Zou

Publications and source records attributed to Xiaolong Zou.

32 records · Page 2Linked to original sources

arXiv2021

Pressure-enhanced ferromagnetism in layered CrSiTe3 flakes

The research on van der Waals (vdW) layered ferromagnets have promoted the development of nanoscale spintronics and applications. However, low-temperature ferromagnetic properties of these materials greatly hinder their applications. Here, we report pressure-enhanced ferromagnetic behaviours in layered CrSiTe3 flakes revealed by high-pressure magnetic circular dichroism (MCD) measurement. At ambient pressure, CrSiTe3 undergoes a paramagnetic-to-ferromagnetic phase transition at 32.8 K, with a negligible hysteresis loop, indicating a soft ferromagnetic behaviour. Under 4.6 GPa pressure, the soft ferromagnet changes into hard one, signalled by a rectangular hysteretic loop with remnant magnetization at zero field. Interestingly, with further increasing pressure, the coercive field (H_c) dramatically increases from 0.02 T at 4.6 GPa to 0.17 T at 7.8 GPa, and the Curie temperature (T_c^h: the temperature for closing the hysteresis loop) also increases from ~36 K at 4.6 GPa to ~138 K at 7.8 GPa. The influences of pressure on exchange interactions are further investigated by density functional theory calculations, which reveal that the in-plane nearest-neighbor exchange interaction and magneto-crystalline anisotropy increase simultaneously as pressure increases, leading to increased H_c and T_c^h in experiments. The effective interaction between magnetic couplings and external pressure offers new opportunities for both searching room-temperature layered ferromagnets and designing pressure-sensitive magnetic functional devices.

cond-mat.mtrl-sci↗

arXiv2020

Modulating Electronic Structure of Monolayer Transition Metal Dichalcogenides by Substitutional Nb-Doping

Modulating electronic structure of monolayer transition metal dichalcogenides (TMDCs) is important for many applications and doping is an effective way towards this goal, yet is challenging to control. Here we report the in-situ substitutional doping of niobium (Nb) into TMDCs with tunable concentrations during chemical vapour deposition. Taking monolayer WS2 as an example, doping Nb into its lattice leads to bandgap changes in the range 1.98 eV to 1.65 eV. Noteworthy, electrical transport measurements and density functional theory calculations show that the 4d electron orbitals of the Nb dopants contribute to the density of states of Nb-doped WS2 around the Fermi level, resulting in an n to p-type conversion. Nb-doping also reduces the energy barrier of hydrogen absorption in WS2, leading to an improved electrocatalytic hydrogen evolution performance. These results highlight the effectiveness of controlled doping in modulating the electronic structure of TMDCs and their use in electronic related applications.

cond-mat.mtrl-sci↗

arXiv2020

Vision at A Glance: Interplay between Fine and Coarse Information Processing Pathways

Object recognition is often viewed as a feedforward, bottom-up process in machine learning, but in real neural systems, object recognition is a complicated process which involves the interplay between two signal pathways. One is the parvocellular pathway (P-pathway), which is slow and extracts fine features of objects; the other is the magnocellular pathway (M-pathway), which is fast and extracts coarse features of objects. It has been suggested that the interplay between the two pathways endows the neural system with the capacity of processing visual information rapidly, adaptively, and robustly. However, the underlying computational mechanisms remain largely unknown. In this study, we build a computational model to elucidate the computational advantages associated with the interactions between two pathways. Our model consists of two convolution neural networks: one mimics the P-pathway, referred to as FineNet, which is deep, has small-size kernels, and receives detailed visual inputs; the other mimics the M-pathway, referred to as CoarseNet, which is shallow, has large-size kernels, and receives low-pass filtered or binarized visual inputs. The two pathways interact with each other via a Restricted Boltzmann Machine. We find that: 1) FineNet can teach CoarseNet through imitation and improve its performance considerably; 2) CoarseNet can improve the noise robustness of FineNet through association; 3) the output of CoarseNet can serve as a cognitive bias to improve the performance of FineNet. We hope that this study will provide insight into understanding visual information processing and inspire the development of new object recognition architectures.

cs.CV↗

arXiv2020

Synthesis of ultrahigh-quality monolayer molybdenum disulfide through in-situ defect healing with thiol molecules

Monolayer transition metal dichalcogenides (TMDCs) are two-dimensional (2D) materials with many potential applications. Chemical vapour deposition (CVD) is a promising method to synthesize these materials. However, CVD-grown materials generally have poorer quality than mechanically exfoliated ones and contain more defects due to the difficulties in controlling precursors' distribution and concentration during growth where solid precursors are used. Here, we propose to use thiol as a liquid precursor for CVD growth of high quality and uniform 2D MoS2. Atomic-resolved structure characterizations indicate that the concentration of sulfur vacancies in the MoS2 grown from thiol is the lowest among all reported CVD samples. Low temperature spectroscopic characterization further reveals the ultrahigh optical quality of the grown MoS2. Density functional theory simulations indicate that thiol molecules could interact with sulfur vacancies in MoS2 and repair these defects during the growth of MoS2, resulting in high quality MoS2. This work provides a facile and controllable method for the growth of high-quality 2D materials with ultralow sulfur vacancies and high optical quality, which will benefit their optoelectronic applications.

cond-mat.mtrl-sci↗

arXiv2020

Unsaturated Single Atoms on Monolayer Transition Metal Dichalcogenides for Ultrafast Hydrogen Evolution

Large scale implementation of electrochemical water splitting for hydrogen evolution requires cheap and efficient catalysts to replace expensive platinum. Molybdenum disulfide is one of the most promising alternative catalysts but its intrinsic activity is still inferior to platinum. There is therefore a need to explore new active site origins in molybdenum disulfide with ultrafast reaction kinetics and to understand their mechanisms. Here, we report a universal cold hydrogen plasma reduction method for synthesizing different single atoms sitting on two-dimensional monolayers. In case of molybdenum disulfide, we design and identify a new type of active site, i.e., unsaturated Mo single atoms on cogenetic monolayer molybdenum disulfide. The catalyst shows exceptional intrinsic activity with a Tafel slope of 35.1 mV dec-1 and a turnover frequency of ~10^3 s-1 at 100 mV, based on single flake microcell measurements. Theoretical studies indicate that coordinately unsaturated Mo single atoms sitting on molybdenum disulfide increase the bond strength between adsorbed hydrogen atoms and the substrates through hybridization, leading to fast hydrogen adsorption/desorption kinetics and superior hydrogen evolution activity. This work shines fresh light on preparing highly-efficient electrocatalysts for water splitting and other electrochemical processes, as well as provides a general method to synthesize single atoms on two-dimensional monolayers.

cond-mat.mtrl-sci↗

arXiv2020

Mass Production of Two-Dimensional Materials by Intermediate-Assisted Grinding Exfoliation

The scalable and high-efficiency production of two-dimensional (2D) materials is a prerequisite to their commercial use. Currently, only graphene and graphene oxide can be produced on a ton scale, and the inability to produce other 2D materials on such a large scale hinders their technological applications. Here we report a grinding exfoliation method that uses micro-particles as force intermediates to resolve applied compressive forces into a multitude of small shear forces, inducing the highly-efficient exfoliation of layer materials. The method, referred to as intermediate-assisted grinding exfoliation (iMAGE), can be used for the large-scale production of many 2D materials. As an example, we have exfoliated bulk h-BN into 2D h-BN with large flake sizes, high quality and structural integrity, with a high exfoliation yield of 67%, a high production rate of 0.3 g h-1 and a low energy consumption of 3.01x10^6 J g-1. The production rate and energy consumption are one to two orders of magnitude better than previous results. Besides h-BN, this iMAGE technology has been used to exfoliate various layer materials such as graphite, black phosphorus, transition metal dichalcogenides, and metal oxides, proving its universality. Molybdenite concentrate, a natural low-cost and abundant mineral, was used as a demo for the large-scale exfoliation production of 2D MoS2 flakes. Our work indicates the huge potential of the iMAGE method to produce large amounts of various 2D materials, which paves the way for their commercial application.

physics.app-ph↗

arXiv2020

Pressure-dependent Intermediate Magnetic Phase in Thin Fe$_3$GeTe$_2$ Flakes

We investigated the evolution of ferromagnetism in layered Fe$_3$GeTe$_2$ flakes under different pressures and temperatures using in situ magnetic circular dichroism (MCD) spectroscopy. We found that the rectangle shape of hysteretic loop under an out-of-plane magnetic field sweep can sustain below 7 GPa. Above that pressure, an intermediate state appears at low temperature region signaled by an 8-shaped skew hysteretic loop. Meanwhile, the coercive field and Curie temperature decrease with increasing pressures, implying the decrease of the exchange interaction and the magneto-crystalline anisotropy under pressures. The intermediate phase has a labyrinthine domain structure, which is attributed to the increase of ratio of exchange interaction to magneto-crystalline anisotropy based on Jagla's theory. Moreover, our calculation results reveal a weak structural transition around 6 GPa, which leads to a drop of the magnetic momentum of Fe ions.

cond-mat.mes-hall↗

arXiv2019

Unsupervised Few-shot Learning via Self-supervised Training

Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community. However, current few-shot learners are mostly supervised and rely heavily on a large amount of labeled examples. Unsupervised learning is a more natural procedure for cognitive mammals and has produced promising results in many machine learning tasks. In the current study, we develop a method to learn an unsupervised few-shot learner via self-supervised training (UFLST), which can effectively generalize to novel but related classes. The proposed model consists of two alternate processes, progressive clustering and episodic training. The former generates pseudo-labeled training examples for constructing episodic tasks; and the later trains the few-shot learner using the generated episodic tasks which further optimizes the feature representations of data. The two processes facilitate with each other, and eventually produce a high quality few-shot learner. Using the benchmark dataset Omniglot and Mini-ImageNet, we show that our model outperforms other unsupervised few-shot learning methods. Using the benchmark dataset Market1501, we further demonstrate the feasibility of our model to a real-world application on person re-identification.

cs.CV↗

arXiv2019

Anisotropic Moiré Optical Transitions in Twisted Monolayer/bilayer Phosphorene Heterostructures

Moiré superlattices of van der Waals heterostructures provide a powerful new way to engineer the electronic structures of two-dimensional (2D) materials. Many novel quantum phenomena have emerged in different moiré heterostructures, such as correlated insulators, superconductors, and Chern insulators in graphene systems and moiré excitons in transition metal dichalcogenide (TMDC) systems. Twisted phosphorene offers another attractive system to explore moiré physics because phosphorene features an anisotropic rectangular lattice, different from the isotropic hexagonal lattice in graphene and TMDC. Here we report emerging anisotropic moiré optical transitions in twisted monolayer/bilayer phosphorene. The optical resonances in phosphorene moiré superlattice depend sensitively on the twist angle between the monolayer and bilayer. Surprisingly, even for a twist angle as large as 19° the moiré heterostructure exhibits optical resonances completely different from those in the constituent monolayer and bilayer phosphorene. The new moiré optical resonances exhibit strong linear polarization, with the principal axis lying close to but different from the optical axis of bilayer phosphorene. Our ab initio calculations reveal that the Γ-point direct bandgap and the rectangular lattice of phosphorene, unlike the K-point bandgap of hexagonal lattice in graphene and TMDC, give rise to the remarkably strong moiré physics in large-twist-angle phosphorene heterostructures. Our results highlight the exciting opportunities to explore moiré physics in phosphorene and other van der Waals heterostructures with different lattice configurations.

cond-mat.mes-hall↗

arXiv2019

Spatiotemporal Information Processing with a Reservoir Decision-making Network

Spatiotemporal information processing is fundamental to brain functions. The present study investigates a canonic neural network model for spatiotemporal pattern recognition. Specifically, the model consists of two modules, a reservoir subnetwork and a decision-making subnetwork. The former projects complex spatiotemporal patterns into spatially separated neural representations, and the latter reads out these neural representations via integrating information over time; the two modules are combined together via supervised-learning using known examples. We elucidate the working mechanism of the model and demonstrate its feasibility for discriminating complex spatiotemporal patterns. Our model reproduces the phenomenon of recognizing looming patterns in the neural system, and can learn to discriminate gait with very few training examples. We hope this study gives us insight into understanding how spatiotemporal information is processed in the brain and helps us to develop brain-inspired application algorithms.

q-bio.NC↗

arXiv2015

Selective doping Barlowite for quantum spin liquid: a first-principles study

Barlowite $Cu_4(OH)_6FBr$ is a newly found mineral containing $Cu^{2+}$ kagome planes. Despite similarities in many aspects to Herbertsmithite $Cu_3Zn(OH)_6Cl_2$, the well-known quantum spin liquid (QSL) candidate, intrinsic Barlowite turns out not to be a QSL, possibly due to the presence of $Cu^{2+}$ ions in between kagome planes that induce interkagome magnetic interaction [PRL, 113, 227203 (2014)]. Using first-principles calculation, we systematically study the feasibility of selective substitution of the interkagome Cu ions with isovalent nonmagnetic ions. Unlike previous speculation of using larger dopants, such as $Cd^{2+}$ and $Ca^{2+}$, we identify the most ideal stoichiometric doping elements to be Mg and Zn in forming $Cu_3Mg(OH)_6FBr$ and $Cu_3Zn(OH)_6FBr$ with the highest site selectivity and smallest lattice distortion. The equilibirium anti-site disorder in Mg/Zn- doped Barlowite is estimated to be one order of magnitude lower than that in Herbertsmithite. The single-electron band structure and orbital component analysis show that the proposed selective doping effectively mitigates the difference between Barlowite and Herbertsmithite.

cond-mat.mtrl-sci↗

arXiv2013

Intrinsic Magnetism of Grain Boundaries in Two-dimensional Metal Dichalcogenides

Grain boundaries (GBs) are structural imperfections that typically degrade the performance of materials. Here we show that dislocations and GBs in two-dimensional (2D) metal dichalcogenides MX2 (M = Mo, W; X = S, Se) can actually improve the material by giving it a qualitatively new physical property: magnetism. The dislocations studied all have a substantial magnetic moment of ~1 Bohr magneton. In contrast, dislocations in other well-studied 2D materials are typically non-magnetic. GBs composed of pentagon-heptagon pairs interact ferromagnetically and transition from semiconductor to half-metal or metal as a function of tilt angle and/or doping level. When the tilt angle exceeds 47° the structural energetics favor square-octagon pairs and the GB becomes an antiferromagnetic semiconductor. These exceptional magnetic properties arise from an interplay of dislocation-induced localized states, doping, and locally unbalanced stoichiometry. Purposeful engineering of topological GBs may be able to convert MX2 into a promising 2D magnetic semiconductor.

cond-mat.mtrl-sci↗

arXiv2013

Vapor Phase Growth and Grain Boundary Structure of Molybdenum Disulfide Atomic Layers

Single layered molybdenum disulfide with a direct bandgap is a promising two-dimensional material that goes beyond graphene for next generation nanoelectronics. Here, we report the controlled vapor phase synthesis of molybdenum disulfide atomic layers and elucidate a fundamental mechanism for the nucleation, growth, and grain boundary formation in its crystalline monolayers. Furthermore, a nucleation-controlled strategy is established to systematically promote the formation of large-area single- and few-layered films. The atomic structure and morphology of the grains and their boundaries in the polycrystalline molybdenum disulfide atomic layers are examined and first-principles calculations are applied to investigate their energy landscape. The electrical properties of the atomic layers are examined and the role of grain boundaries is evaluated. The uniformity in thickness, large grain sizes, and excellent electrical performance of these materials signify the high quality and scalable synthesis of the molybdenum disulfide atomic layers.

cond-mat.mtrl-sci↗

arXiv2012

Dislocations and Grain Boundaries in Two-Dimensional Boron Nitride

A new dislocation structure-square-octagon pair (4|8) is discovered in two-dimensional boron nitride (h-BN), via first-principles calculations. It has lower energy than corresponding pentagon-heptagon pairs (5|7), which contain unfavorable homo-elemental bonds. Based on the structures of dislocations, grain boundaries (GB) in BN are investigated. Depending on the tilt angle of grains, GB can be either polar (B-rich or N-rich), constituted by 5|7s, or un-polar, composed of 4|8s. The polar GBs carry net charges, positive at B-rich and negative at N-rich ones. In contrast to GBs in graphene which generally impede the electronic transport, polar GBs have smaller bandgap compared to perfect BN, which may suggest interesting electronic and optic applications.

cond-mat.mtrl-sci↗