Siew Ann Cheong

The influence of preparation conditions on the surface area of zirconia

Abstract The conditions for preparation of high surface area zirconia were studied. Samples were prepared by precipitation from aqueous solutions of zirconium chloride with ammonium hydroxide. The order of addition of the reactants was found to affect the surface area. Digestion of the hydrous zirconia is the key to high surface area zirconia without the necessity of adding other oxides or dopants. Both the temperature and the time of digestion are important parameters. Zirconia with surface area in excess of 220 m 2 /g after calcination at 500°C have been obtained. The materials maintained a surface area of >90 m 2 /g even after heat treatment at 900°C for 12 h. In addition, digestion led to the formation of the tetragonal allotrope of zirconia. Samples which had been digested for long times at 100°C are tetragonal and maintain this phase up to 1000°C. The effects of digestion seems to be related to a phase transformation of the hydrous precursor at around 80°C. A mechanism based on defect density is postulated to explain the phase stability.

Bound magnetic polarons and p-d exchange interaction in ferromagnetic insulating Cu-doped ZnO

A systematic study on the magnetic and electrical transport properties of single-phase wurtzite Zn1−xCuxO is performed. Efros variable range hopping dominates the conduction, which is accompanied by a ferromagnetic order up to 700 K for x>1%. Both the first-principles calculations and Cu/Al co-doping experiments suggest that the spontaneous spin polarization originates from the p-d exchange interaction between O 2p and Cu 3d orbitals. Furthermore, our results are consistent with the scenario that the intrinsic ferromagnetism is established through indirect interactions between bound magnetic polarons mediated by magnetic impurities.

Polaronic transport and magnetism in Ag-doped ZnO

Magnetic polarons have been proposed to play important roles in doped wide band gap oxides that exhibit weak room temperature ferromagnetism. Here, we report the experimental evidence supporting polaronic magnetism and transport in Ag-doped ZnO. Temperature dependent resistivity data suggest the conduction mechanism of Mott and Efros variable range hopping. The observed weak ferromagnetism and its temperature dependence are explained using the percolation-based model of partially ordered bound magnetic polarons.

Terahertz Conductivity of Twisted Bilayer Graphene

Using terahertz time-domain spectroscopy, the real part of optical conductivity [σ(1)(ω)] of twisted bilayer graphene was obtained at different temperatures (10-300 K) in the frequency range 0.3-3 THz. On top of a Drude-like response, we see a strong peak in σ(1)(ω) at ~2.7 THz. We analyze the overall Drude-like response using a disorder-dependent (unitary scattering) model, then attribute the peak at 2.7 THz to an enhanced density of states at that energy, which is caused by the presence of a van Hove singularity arising from a commensurate twisting of the two graphene layers.

Epidemic reemergence in adaptive complex networks

The dynamic nature of a system gives rise to dynamical features of epidemic spreading, such as oscillation and bistability. In this paper, by studying the epidemic spreading in growing networks, in which susceptible nodes may adaptively break the connections with infected ones yet avoid being isolated, we reveal a phenomenon, epidemic reemergence, where the number of infected nodes is incubated at a low level for a long time and then erupts for a short time. The process may repeat several times before the infection finally vanishes. Simulation results show that all three factors, namely the network growth, the connection breaking, and the isolation avoidance, are necessary for epidemic reemergence to happen. We present a simple theoretical analysis to explain the process of reemergence in detail. Our study may offer some useful insights, helping explain the phenomenon of repeated epidemic explosions.

Calculation of quantum tunneling for a spatially extended defect: the dislocation kink in copper has a low effective mass.

We calculate the widths, migration barriers, effective masses, and quantum tunneling rates of kinks and jogs in extended screw dislocations in copper, using an effective medium theory interatomic potential. The energy barriers and effective masses for moving a unit jog one lattice constant are close to typical atomic energies and masses: tunneling will be rare. The energy barriers and effective masses for the motion of kinks are unexpectedly small due to the spreading of the kinks over a large number of atoms. The effective masses of the kinks are so small that quantum fluctuations will be important. We discuss implications for quantum creep, kink--based tunneling centers, and Kondo resonances.

Equal Graph Partitioning on Estimated Infection Network as an Effective Epidemic Mitigation Measure

Controlling severe outbreaks remains the most important problem in infectious disease area. With time, this problem will only become more severe as population density in urban centers grows. Social interactions play a very important role in determining how infectious diseases spread, and organization of people along social lines gives rise to non-spatial networks in which the infections spread. Infection networks are different for diseases with different transmission modes, but are likely to be identical or highly similar for diseases that spread the same way. Hence, infection networks estimated from common infections can be useful to contain epidemics of a more severe disease with the same transmission mode. Here we present a proof-of-concept study demonstrating the effectiveness of epidemic mitigation based on such estimated infection networks. We first generate artificial social networks of different sizes and average degrees, but with roughly the same clustering characteristic. We then start SIR epidemics on these networks, censor the simulated incidences, and use them to reconstruct the infection network. We then efficiently fragment the estimated network by removing the smallest number of nodes identified by a graph partitioning algorithm. Finally, we demonstrate the effectiveness of this targeted strategy, by comparing it against traditional untargeted strategies, in slowing down and reducing the size of advancing epidemics.

Quantitative Comparison Between Crowd Models for Evacuation Planning and Evaluation

Crowd simulation is rapidly becoming a standard tool for evacuation planning and evaluation. However, the many crowd models in the literature are structurally different, and few have been rigorously calibrated against real-world egress data, especially in emergency situations. In this paper we describe a procedure to quantitatively compare different crowd models or between models and real-world data. We simulated three models: (1) the lattice gas model, (2) the social force model, and (3) the RVO2 model, and obtained the distributions of six observables: (1) evacuation time, (2) zoned evacuation time, (3) passage density, (4) total distance traveled, (5) inconvenience, and (6) flow rate. We then used the DISTATIS procedure to compute the compromise matrix of statistical distances between the three models. Projecting the three models onto the first two principal components of the compromise matrix, we find the lattice gas and RVO2 models are similar in terms of the evacuation time, passage density, and flow rates, whereas the social force and RVO2 models are similar in terms of the total distance traveled. Most importantly, we find that the zoned evacuation times of the three models to be very different from each other. Thus we propose to use this variable, if it can be measured, as the key test between different models, and also between models and the real world. Finally, we compared the model flow rates against the flow rate of an emergency evacuation during the May 2008 Sichuan earthquake, and found the social force model agrees best with this real data.

Temperature-dependent terahertz conductivity of tin oxide nanowire films

Temperature-dependent terahertz conductivity of tin oxide (SnO2) nanowire films was measured from 10 to 300K using terahertz time-domain spectroscopy. The optical parameters, including the complex refractive index, optical conductivity and dielectric function, were obtained using a simple effective medium theory. The complex conductivity was fitted with the Drude-Smith model and the plasmon model. The results show that the carrier density (N) and plasmon resonance frequency (ω0) increase while the scattering time decreases with increasing temperature. The reduced carrier mobility compared with bulk SnO2 indicates the presence of carrier localization or trapping in these nanowires. (Some figures may appear in colour only in the online journal)

Understanding agent-based models of financial markets: A bottom-up approach based on order parameters and phase diagrams

We describe a bottom–up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.