Direct Growth of Germanene at Interfaces between Van der Waals Materials and Ag(111)

Germanene, a 2D honeycomb germanium crystal, is grown at graphene/Ag(111) and hexagonal boron nitride (h-BN)/Ag(111) interfaces by segregating germanium atoms. A simple annealing process in N₂ or H₂/Ar at ambient pressure leads to the formation of germanene, indicating that an ultrahigh-vacuum condition is not necessary. The grown germanene is stable in air and uniform over the entire area covered with a van der Waals (vdW) material. As an important finding, it is necessary to use a vdW material as a cap layer for the present germanene growth method since the use of an Al₂O₃ cap layer results in no germanene formation. The present study also proves that Raman spectroscopy in air is a powerful tool for characterizing germanene at the interfaces, which is concluded by multiple analyses including first-principles density functional theory calculations. The direct growth of h-BN-capped germanene on Ag(111), which is demonstrated in the present study, is considered to be a promising technique for the fabrication of future germanene-based electronic devices.     

The effect of thiophene sequence separation on air-stable organic thin-film transistor materials

The relationship between thiophene sequences and organic thin-film transistor (OTFT) characteristics was studied to determine their effect on ionization potential, molecular orientation, and air stability. Two types of molecular structures were used: continuous sequence and divided sequence thiophenes. The length of thiophene sequence did not affect FET characteristics but did affect ionic potential and air stability. Furthermore, materials with divided thiophene sequences showed no change in OTFT characteristics when exposed to air. These results suggest that separation of thiophene sequences can improve air stability, which is a problem of thiophene-based materials.     

High performance 35 nm gate length CMOS with NO oxynitride gate dielectric and Ni salicide

The 35 nm gate length CMOS devices with oxynitride gate dielectric and Ni salicide have been fabricated to study the feasibility of higher performance operation. Nitrogen concentration in gate oxynitride was optimized to reduce gate current I/sub g/ and to prevent boron penetration in the pFET. The thermal budget in the middle of the line (MOL) process was reduced enough to realize shallower junction depth in the S/D extension regions and to suppress gate poly-Si depletion. Finally, the current drives of 676 /spl mu/A//spl mu/m in nFET and 272 /spl mu/A//spl mu/m in pFET at V/sub dd/=0.85 V (at I/sub off/=100 nA//spl mu/m) were achieved and they are the best values for 35 nm gate length CMOS reported to date.     

Photoactive Electro-Controlled Visual Perception Memory for Emulating Synaptic Metaplasticity and Hebbian Learning

In bionic technology, it has become an innovative process imitating the functionality and structuralism of human biological systems to exploit advanced artificial intelligent machines. Bionics plays a significant role in environmental protection, especially for its low energy loss. By fusing the concept of receptor-like sensing component and synapse-like memory, the photoactive electro-controlled optical sensory memory (PE-SM) is proposed and realized in a single device, which endows a simple methodology of reducing power consumption by photoactive electro-control. The PE-SM is the system built with the stacked atomically thick materials, in which rhenium diselenide serves as a robust photosensor, hexagonal boron nitride serves as a tunneling dielectric, and graphene serves as a charge-storage layer. With the features of the PE-SM, it performs synaptic metaplasticities under optical spikes. In addition, a simulated spiking neural network composed of 24 × 24 PE-SMs is further presented in an unsupervised machine learning environment, performing image recognition via the Hebbian rule. The PE-SM not only improves the neuromorphic computing efficiency but also simplifies the circuit-size structure. Eventually, the concept of photoactive electro-control can extend to other photosensitive 2D materials and provide a new approach of constructing either visual perception memory or photonic synaptic devices.     

A Quaternary van der Waals Ferromagnetic Semiconductor AgVP2Se6

The recent realization of 2D magnetism in van der Waals (vdWs) magnets holds promise for future information technology. However, the vdWs semiconducting ferromagnets, which remain rare, are especially important in developing 2D magnetic devices with new functionalities due to the possibility of simultaneous control of the carrier charge and spin. Metal thiophosphate (MTP), a multifunctional vdWs material system that combines the sought‐after properties of complex oxides, is a promising vdWs magnet system. Here, single crystals of a novel vdWs ferromagnetic semiconductor MTP AgVP₂Se₆ with a room‐temperature resistivity of 1 Ω m are successfully synthesized. Due to the nature of vdWs bonding along the c‐axis, the magnetic properties of the few‐layer AgVP₂Se₆ with different thicknesses are characterized on the exfoliated samples. The AgVP₂Se₆ flakes exhibit significant thickness‐dependent magnetic properties, and a rectangular hysteresis loop with a large coercive field of 750 Oe at 2 K and an undiminished Curie temperature of 19 K are observed in the 6.7 nm AgVP₂Se₆ flake. The discovered vdWs ferromagnet AgVP₂Se₆ with semiconducting behavior will provide alternative platforms for exploring 2D magnetism and potential applications in spintronic devices.     

掺锡As2S8非饱和光阻断效应实验与机理研究

为了研究微量Sn掺As2S8非晶态薄膜波导非饱和光阻断效应的内在机理,采用双棱镜耦合技术,对波导样品进行了实验研究,在实验观测数据,分析了薄膜材料内部的化学键结构,结合电子能带理论和轨道杂化理论,建立了非饱和光阻断效应的动力学模型,并对实验数据进行数值拟合,得到了描述非饱和光阻断效应性质的参数。数值分析与实验结果吻合,说明本文模型能解释实验现象,揭示实验本质。     

Statistical analysis for multiplicatively modulated nonlinear autoregressive model and its applications to electrophysiological signal analysis in humans

Modulating the dynamics of a nonlinear autoregressive model with a radial basis function (RBF) of exogenous variables is known to reduce the prediction error. Here, RBF is a function that decays to zero exponentially if the deviation between the exogenous variables and a center location becomes large. This paper introduces a class of RBF-based multiplicatively modulated nonlinear autoregressive (mmNAR) models. First, we establish the local asymptotic normality (LAN) for vector conditional heteroscedastic autoregressive nonlinear (CHARN) models, which include the mmNAR and many other well-known time-series models as special cases. Asymptotic optimality for estimation and testing is described in terms of LAN properties. The mmNAR model indicates goodness-of-fit for surface electromyograms (EMG) using electrocorticograms (ECoG) as the exogenous variables. Concretely, it is found that the negative potential of the motor cortex forces change in the frequency of EMG, which is reasonable from a physiological point of view. The proposed mmNAR model fitting is both useful and efficient as a signal-processing technique for extracting information on the action potential, which is associated with the postsynaptic potential.     

Filling behavior of UV nanoimprint resin observed by using a midair structure mold

The filling behavior of resin during UV nanoimprint lithography (UV-NIL) was observed by using a “midair structure mold” and by changing the imprint pressure. The midair structure molds were fabricated by electron beam lithography (EBL) using hydrogen silsesquioxane (HSQ) as a negative tone resist. After the fabrication of midair structure mold, two types of surface treatment molds, which were with or without release coating, were prepared. Using these molds, the filling behavior of a UV curable resin was investigated at various pressures. The results indicate that a pressure of approximately 1.2 MPa is necessary for complete filling in the case of molds treated with a release agent. This method demonstrates effect of a release coating for UV-NIL.     

A circuit technology for high-speed battery-operated 16-Mb CMOSDRAM's

A battery-operated 16-Mb CMOS DRAM with address multiplexing has been developed by using an existing 0.5-μm CMOS technology. It can access data in 36 ns when powered from a 1.8-V battery-source, and 20 ns at 3.3 V. However, this device requires a mere 57 mA of operating current for an 80-ns cycle time and only 5 μA of standby current at 3.3 V. To achieve both high-speed and low-power operation, the following four circuit techniques have been developed: 1) a parallel column access redundancy (PCAR) scheme coupled with a current sensing address comparator (CSAC), 2) an N&PMOS cross-coupled read-bus-amplifier (NPCA), 3) a gate isolated sense amplifier (GISA) with low V_T, and 4) a layout that minimizes the length of the signal path by employing the lead on chip (LOC) assembly technique     

Determination of the best-fit values of kinetic parameters of the Michaelis-Menten equation by the method of least squares with the Taylor expansion

The best-fit values of the Michaelis constant (Km) and the maximum velocity (V) in the Michaelis-Menten equation can be obtained by the method of least squares with the Taylor expansion for the sum of squares of the absolute residual, i.e., the difference between the observed velocity and the corresponding velocity by calculation. This method makes it possible to determine the values of Km and V not in a trial-and-error manner but in a deductive and unique manner after some iterative procedures starting from arbitrary approximate values of Km and V. These values can be said to be uniquely determined for a set of data as the finally converged values are no longer dependent upon the initial approximate values of Km and V. It is also very important to obtain initial approximate values of parameters for the application of the method described above. A simple method is proposed to estimate the approximate values of parameters involved in fractional functions. The method of rearrangement after canceling of denominator of a fractional function can be utilized to obtain approximate values, not only for cases of two unknown parameters such as the Michaelis-Menten equation, but also for cases with more than two unknowns.