arXiv subjects

Li Lin

Publications and source records attributed to Li Lin.

118 records · Page 7Linked to original sources

arXiv2018

Charge transport and electron-hole asymmetry in low-mobility graphene/hexagonal boron nitride heterostructures

Graphene/hexagonal boron nitride (G/$h$-BN) heterostructures offer an excellent platform for developing nanoelectronic devices and for exploring correlated states in graphene under modulation by a periodic superlattice potential. Here, we report on transport measurements of nearly $0^{\circ}$-twisted G/$h$-BN heterostructures. The heterostructures investigated are prepared by dry transfer and thermally annealing processes and are in the low mobility regime (approximately $3000~\mathrm{cm}^{2}\mathrm{V}^{-1}\mathrm{s}^{-1}$ at 1.9 K). The replica Dirac spectra and Hofstadter butterfly spectra are observed on the hole transport side, but not on the electron transport side, of the heterostructures. We associate the observed electron-hole asymmetry to the presences of a large difference between the opened gaps in the conduction and valence bands and a strong enhancement in the interband contribution to the conductivity on the electron transport side in the low-mobility G/$h$-BN heterostructures. We also show that the gaps opened at the central Dirac point and the hole-branch secondary Dirac point are large, suggesting the presence of strong graphene-substrate interaction and electron-electron interaction in our G/$h$-BN heterostructures. Our results provide additional helpful insight into the transport mechanism in G/$h$-BN heterostructures.

cond-mat.mes-hall↗

arXiv2017

Joint Hierarchical Category Structure Learning and Large-Scale Image Classification

We investigate the scalable image classification problem with a large number of categories. Hierarchical visual data structures are helpful for improving the efficiency and performance of large-scale multi-class classification. We propose a novel image classification method based on learning hierarchical inter-class structures. Specifically, we first design a fast algorithm to compute the similarity metric between categories, based on which a visual tree is constructed by hierarchical spectral clustering. Using the learned visual tree, a test sample label is efficiently predicted by searching for the best path over the entire tree. The proposed method is extensively evaluated on the ILSVRC2010 and Caltech 256 benchmark datasets. Experimental results show that our method obtains significantly better category hierarchies than other state-of-the-art visual tree-based methods and, therefore, much more accurate classification.

cs.CV↗

arXiv2017

Ultrafast Epitaxial Growth of Metre-Sized Single-Crystal Graphene on Industrial Cu Foil

A foundation of the modern technology that uses single-crystal silicon has been the growth of high-quality single-crystal Si ingots with diameters up to 12 inches or larger. For many applications of graphene, large-area high-quality (ideally of single-crystal) material will be enabling. Since the first growth on copper foil a decade ago, inch-sized single-crystal graphene has been achieved. We present here the growth, in 20 minutes, of a graphene film of 5 x 50 cm2 dimension with > 99% ultra-highly oriented grains. This growth was achieved by: (i) synthesis of sub-metre-sized single-crystal Cu(111) foil as substrate; (ii) epitaxial growth of graphene islands on the Cu(111) surface; (iii) seamless merging of such graphene islands into a graphene film with high single crystallinity and (iv) the ultrafast growth of graphene film. These achievements were realized by a temperature-driven annealing technique to produce single-crystal Cu(111) from industrial polycrystalline Cu foil and the marvellous effects of a continuous oxygen supply from an adjacent oxide. The as-synthesized graphene film, with very few misoriented grains (if any), has a mobility up to ~ 23,000 cm2V-1s-1 at 4 K and room temperature sheet resistance of ~ 230 ohm/square. It is very likely that this approach can be scaled up to achieve exceptionally large and high-quality graphene films with single crystallinity, and thus realize various industrial-level applications at a low cost.

cond-mat.mtrl-sci↗

arXiv2017

Electron-Hole Symmetry Breaking in Charge Transport in Nitrogen-Doped Graphene

Graphitic nitrogen-doped graphene is an excellent platform to study scattering processes of massless Dirac fermions by charged impurities, in which high mobility can be preserved due to the absence of lattice defects through direct substitution of carbon atoms in the graphene lattice by nitrogen atoms. In this work, we report on electrical and magnetotransport measurements of high-quality graphitic nitrogen-doped graphene. We show that the substitutional nitrogen dopants in graphene introduce atomically sharp scatters for electrons but long-range Coulomb scatters for holes and, thus, graphitic nitrogen-doped graphene exhibits clear electron-hole asymmetry in transport properties. Dominant scattering processes of charge carriers in graphitic nitrogen-doped graphene are analyzed. It is shown that the electron-hole asymmetry originates from a distinct difference in intervalley scattering of electrons and holes. We have also carried out the magnetotransport measurements of graphitic nitrogen-doped graphene at different temperatures and the temperature dependences of intervalley scattering, intravalley scattering and phase coherent scattering rates are extracted and discussed. Our results provide an evidence for the electron-hole asymmetry in the intervalley scattering induced by substitutional nitrogen dopants in graphene and shine a light on versatile and potential applications of graphitic nitrogen-doped graphene in electronic and valleytronic devices.

cond-mat.mes-hall↗

arXiv2016

Effects of cold atmospheric plasma generated in deionized water in cell cancer therapy

Cold atmospheric plasma (CAP) was shown to affect cells not only directly, but also indirectly by means of plasma pre-treated solution. This study investigated a new application of CAP generated in deionized (DI) water for the cancer therapy. In our experiments, the CAP solution was generated in DI water using helium as carrier gas. We report on the effects of this plasma solution in breast (MDA-MD-231) and gastric (NCI-N87) cancer cells. The results revealed that apoptosis efficiency was dependent on the plasma exposure time and on the levels of reactive oxygen and nitrogen species (ROS and RNS). The plasma solution that resulted from 30-minute treatment of DI water had the most significant effect in the rate of apoptosis.

physics.med-ph↗

arXiv2016

Cold Atmospheric Plasma discharged in Water and its Potential Use in Cancer Therapy

Cold atmospheric plasma (CAP) has been emerged as a novel technology for cancer treatment. CAP can directly treat cells and tissue but such direct application is limited to skin or can be invoked as a supplement during open surgery. In this study we report indirect plasma treatment using CAP discharged in DI water using three gases as carriers (argon, helium and nitrogen). Plasma stimulated water was applied to human breast cancer cell line (MDA-MB-231). MTT assay tests showed that using argon plasma had the strongest effect on inducing apoptosis in cultured human breast cancer cells. This result is attributed to the elevated production of the reactive oxygen species and reactive nitrogen species in water in the case of argon plasma.

physics.med-ph↗

arXiv2016

Treatment of gastric cancer cells with non-thermal atmospheric plasma generated in water

Non-thermal atmospheric plasma (NTAP) can be applied to living tissues and cells as a novel technology for cancer therapy. Even though studies report on the successful use of NTAP to directly irradiate cancer cells, this technology can cause cell death only in the upper 3-5 cell layers. We report on a NTAP argon solution generated in DI water for treating human gastric cancer cells (NCl-N87). Our findings showed that the plasma generated in DI water during a 30-minute treatment had the strongest affect in inducing apoptosis in cultured human gastric cancer cells. This result can be attributed to presence of reactive oxygen species (ROS) and reactive nitrogen species (RNS) produced in water during treatment. Furthermore, the data showed that elevated levels of RNS may play an even more significant role than ROS in the rate of apoptosis in gastric cancer cells.

q-bio.TO↗

arXiv2015

"Speculative Influence Network" during financial bubbles: application to Chinese Stock Markets

We introduce the Speculative Influence Network (SIN) to decipher the causal relationships between sectors (and/or firms) during financial bubbles. The SIN is constructed in two steps. First, we develop a Hidden Markov Model (HMM) of regime-switching between a normal market phase represented by a geometric Brownian motion (GBM) and a bubble regime represented by the stochastic super-exponential Sornette-Andersen (2002) bubble model. The calibration of the HMM provides the probability at each time for a given security to be in the bubble regime. Conditional on two assets being qualified in the bubble regime, we then use the transfer entropy to quantify the influence of the returns of one asset $i$ onto another asset $j$, from which we introduce the adjacency matrix of the SIN among securities. We apply our technology to the Chinese stock market during the period 2005-2008, during which a normal phase was followed by a spectacular bubble ending in a massive correction. We introduce the Net Speculative Influence Intensity (NSII) variable as the difference between the transfer entropies from $i$ to $j$ and from $j$ to $i$, which is used in a series of rank ordered regressions to predict the maximum loss (\%{MaxLoss}) endured during the crash. The sectors that influenced other sectors the most are found to have the largest losses. There is a clear prediction skill obtained by using the transfer entropy involving industrial sectors to explain the \%{MaxLoss} of financial institutions but not vice versa. We also show that the bubble state variable calibrated on the Chinese market data corresponds well to the regimes when the market exhibits a strong price acceleration followed by clear change of price regimes. Our results suggest that SIN may contribute significant skill to the development of general linkage-based systemic risks measures and early warning metrics.

q-fin.ST↗

arXiv2011

Statistical and dynamical fluctuations in the ratios of higher cumulants in relativistic heavy ion collisions

With the help of transport and statistical models, we find that the ratios of higher net-proton cumulants measured at RHIC are dominated by the statistical fluctuations. Future measurements should focus on the dynamical fluctuations, which are relevant to the underlying mechanisms of particle production, the critical phenomena in particular. We also demonstrate that a proton-antiproton correlation directly show if protons and antiprotons are emitted independently.

nucl-th↗

arXiv2009

Diagnostics of Rational Expectation Financial Bubbles with Stochastic Mean-Reverting Termination Times

We propose two rational expectation models of transient financial bubbles with heterogeneous arbitrageurs and positive feedbacks leading to self-reinforcing transient stochastic faster-than-exponential price dynamics. As a result of the nonlinear feedbacks, the termination of a bubble is found to be characterized by a finite-time singularity in the bubble price formation process ending at some potential critical time $\tilde{t}_c$, which follows a mean-reversing stationary dynamics. Because of the heterogeneity of the rational agents' expectations, there is a synchronization problem for the optimal exit times determined by these arbitrageurs, which leads to the survival of the bubble almost all the way to its theoretical end time. The explicit exact analytical solutions of the two models provide nonlinear transformations which allow us to develop novel tests for the presence of bubbles in financial time series. Avoiding the difficult problem of parameter estimation of the stochastic differential equation describing the price dynamics, the derived operational procedures allow us to diagnose bubbles that are in the making and to forecast their termination time. The tests performed on three financial markets, the US S&P500 index from 1 February 1980 to 31 October 2008, the US NASDAQ composite index from 1 January 1980 to 31 July 2008 and the Hong Kong Hang Seng index from 1 December 1986 to 30 November 2008, suggest the feasibility of advance bubble warning.

q-fin.GN↗