Lingfei Wang

Charge order suppression and weak ferromagnetism in La1∕3Sr2∕3FeO3 nanoparticles

Perovskite-type polycrystalline La1/3Sr2/3FeO3 particles with different sizes (80-2000 nm) were prepared using a simple sol-gel technique. In samples of nanoparticles with a diameter of less than 300 nm, weak ferromagnetism was observed at room temperature, which was attributed to the lattice distortion. The magnetic and specific heat measurements suggest that the charge ordering state was largely suppressed due to the lowering of the particle size, but the charge ordering temperature remained unaffected

Ferromagnetic metal to cluster-glass insulator transition induced by A-site disorder in manganites

The magnetotransport behaviors of a series of rare earth manganites with the same A-site cational mean radius and different A-site ionic radii variance A-site disorder are investigated. It is found that the system’s ground state transforms from ferromagnetic metal to cluster-glass insulator with increasing A-site disorder. In the cluster-glass state, the magnetization shows the steplike behavior, indicating the existence of short-range magnetically ordered clusters. The significant effect of the A-site disorder on the electronic phase separation is revealed by detecting the cluster-glass ground state at low temperature.

Analytical carrier density and quantum capacitance for graphene

A disorder based analytical carrier density for graphene is presented here. The carrier density, a basic property of all semiconductors, is obtained based on exponential distribution describing the potential fluctuations induced by impurities and shows good agreement with numerical results. The quantum capacitance is subsequently derived from the carrier density, with a good agreement with experimental measurements. A method for extracting the gate coupling function is also proposed, which relates the internal surface potential with the external applied gate voltage. The essential properties of graphene device physics, such as the temperature, material disorder, and surface potential dependences, are captured in these analytical equations.

Role of long-range elastic energy in relaxor ferroelectrics

The dipole configuration of relaxor ferroelectrics (RFs) is investigated by numerically solving the time-dependent Ginzburg-Landau equation based on the dipole defect model. The domain structure of RFs is revealed to consist of dipole ordered clusters embedded in the paraelectric matrix. We demonstrate that the role of long-range elastic energy in RFs is much less important than in normal ferroelectrics, although the shape of the dipole clusters depends on the elastic energy. Based on the numerical results, a phase diagram of temperature-defect density for RFs is constructed, which identifies four distinct phase regimes.

Hysteresis dispersion scaling of a two-dimensional ferroelectric model

The ferroelectric hysteresis dispersion of a two-dimensional ferroelectric model lattice in an ac electric field of amplitude E-0 and frequency omega over a wide range, respectively, is calculated by Monte Carlo simulation based on the Ginzburg-Landau theory on tetragonal-type ferroelectric phase transitions. Given a fixed field amplitude E-0, the hysteresis dispersion as a function of field frequency omega shows a single-peaked pattern, which predicts the existence of a characteristic time responsible for domain switching in an external electric field. The scaling analysis demonstrates that given different field amplitudes E-0, the hysteresis dispersions can be scaled and the characteristic time depends inversely on the field amplitude E-0 over a wide range of E-0, but the large deviation occurs as E-0 is very small or extremely large. (c) 2005 American Institute of Physics.

A review for compact model of graphene field-effect transistors*

Graphene has attracted enormous interests due to its unique physical, mechanical, and electrical properties. Specially, graphene-based field-effect transistors (FETs) have evolved rapidly and are now considered as an option for conventional silicon devices. As a critical step in the design cycle of modern IC products, compact model refers to the development of models for integrated semiconductor devices for use in circuit simulations. The purpose of this review is to provide a theoretical description of current compact model of graphene field-effect transistors. Special attention is devoted to the charge sheet model, drift-diffusion model, Boltzmann equation, density of states (DOS), and surface-potential-based compact model. Finally, an outlook of this field is briefly discussed.

An Improved Cut-Off Frequency Model With a Modified Small-Signal Equivalent Circuit in Graphene Field-Effect Transistors

An improved cut-off frequency model of a modified equivalent circuit of graphene field-effect transistors, which incorporates the additional capacitive effect physically present due to dipole layer between the metal and the graphene, is proposed. The original equivalent circuit is not accurate for a large separation distance dipole layer. Based on the improved equivalent circuit model, a more accurate parameter extraction by two-port analysis is possible, and the cut-off frequency will be more accurate particularly for largely separated dipole layer near the Dirac point. Considering the dipole layer, the equivalent circuit is never investigated before, and the cut-off frequency model shows good agreement with experiments.

Surface-potential-based physical compact model for graphene field effect transistor

A surface potential based physical compact model for a graphene field effect transistor is proposed, including Boltzmann transport and thermally activated transport. We verified it by the experiments and Gummel symmetry test, showing good accuracy and continuity over a wide range of operation regions. Coded in Verilog-A, this model provides physics-based consistent DC and AC characteristics, which can be easily embedded into a vendor CAD tool to simulate circuits. Based on this model, a direct insight into the relationship between physical parameters and circuit performances can be achieved.

A new surface potential based physical compact model for GFET in RF applications

For the first time, we present a continuous surface potential based physical compact model for GFET and benchmark our work against device measurements. This model is based on semi-classical Boltzmann transport and thermally activated transport theories, including both remote and short range scattering mechanisms. Therefore the model is temperature dependent. Meanwhile, we provide the corresponding method to extract the key physical parameters. Furthermore, the compact model is coded in Verilog-A, and can be implemented in vendor CAD tools. The model provides a physics-based consistent description of DC and AC device characteristics and enables accurate circuit-level performance estimation and RF circuit design of GFET.

A hardware neural network for handwritten digits recognition using binary RRAM as synaptic weight element

A functional neural network for handwritten digits recognition using single binary RRAM as the synaptic weight element, was presented, with successful recognition rate is up to 81%. The results show that multilevel or continual resistances is not necessary for resistive device used as synaptic weight element in hardware neural network application. Variation of RRAM devices, sometimes, would not affect, but benefit the performance of the neural network. The simulated binary RRAM based network is so robust, that even if half of the basic elements were die, it will still be functional.