Electronic conduction and breakdown in liquid helium and liquid neon

New data of the electronic properties of liquid helium and liquid neon are discussed with respect to their relevance for the initiation of electric breakdown. It is concluded that under ideal conditions the cathode plays a decisive role in the initiation of the breakdown process. It is speculated that a Townsend type breakdown mechanism is absent in the liquid phase of these elements.     

Quantum Lattice-Gas Automata Simulation of Electronic Wave Propagation in Nanostructures

We report the two- and three-dimensional quantum lattice-gas automata simulation for one-particle electronic wave propagation in nanostructures. The transmission coefficient of the electronic wave through the two-dimensional quantum point contact is investigated taking account of the surface roughness of the confinement wall. It is demonstrated that the electron transmission is significantly affected by the surface roughness pattern even if the same roughness parameter is assumed. We also perform the three-dimensional simulation, and the wave propagation in the structure like an ultrathin-body MOSFET is visualized.     

三水铝石的粉碎机械力化学效就与热特性

使用振动球磨机将三水铝石粉体进行干式微粉碎.粉碎实验条件为介质球/试样(质量比)=8.5.研究调查了不同粉碎时间处理粉碎试样的机械力化学效应(平均粒径、结晶无定形和加热特性).结果表明,长时间粉碎,达到粉碎平衡,平均粒径趋于极限值.粉碎过程中未脱水.由于粉碎,加热脱水温度、结晶相变温度降低.     

Super‐resolution of the undersampled and subpixel shifted image sequence by a neural network

Numerous approaches to super‐resolution (SR) of sequentially observed images (image sequence) of low resolution (LR) have been presented in the past two decades. However, neural network methods are almost ignored for solving SR problems. This is because the SR problem traditionally has been regarded as the optimization of an ill‐posed large set of linear equations. A designed neural network based on this has a large number of neurons, thereby requiring a long learning time. Also, the deduced cost function is overly complex. These defects limit applications of a neural network to an SR problem. We think that the underlying meaning of the SR problem should refer to super‐resolving an imaging system by image sequence observation, instead of merely improving the image sequence itself. SR can be regarded as a pattern mapping from LR to SR images. The parameters of the pattern mapping can be learned from the imaging process of the image sequence. This article presents a neural network for SR based on learning from the imaging process of the image sequence. In order to speed up the convergence, we employ vector mapping to train the neural network. A mapping vector is composed of some neighbor subpixels. Such a well‐trained neural network has powerful generalization ability so that it can be used directly to estimate the SR image of the other image sequences without learning again. Our simulations show the effectiveness of the proposed neural network. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 8–15, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20001     

Classification of amorphous-silicon microstructures by structural parameters: molecular dynamics study

Amorphous silicon is the most popular material in the field of semiconductors. However, little is known about its microstructures. To understand the dependence of these microstructures on the fabrication process and on structural relaxation, amorphous silicon samples fabricated by various simulated processes are classified according to structural parameters within the molecular dynamics method.

The results show that the amorphous structures fabricated by the melt-quench method have many odd-membered rings and large bond-angle deviation. The structures fabricated by the molecular-beam epitaxy method involve fewer floating bonds, smaller bond-angle deviations, and fewer six-membered rings in comparison with the melt-quenched structure. Through long-term annealing, both structures are transformed to the most stable structure as described by the Tersoff potential. It is also found that the continuous random network structure does not meet the Tersoff potential. Verification of the results through first-principle calculations shows that well-relaxed amorphous structure can be described by classical molecular dynamics despite the slightly large number of the floating bond and the overestimation of amorphous-phase energy.     

Estimating the creep behavior of polycarbonate with changes in temperature and aging time

Thermoplastic resins are typically used without any kind of physical aging treatment. For such materials, creep behavior and physical aging, which depend on time and temperature, occur simultaneously. The effects of these processes are evident after quenching and are recorded in the material as a thermal history. This history strongly influences mechanical properties and creep behavior in particular. Thus, a more thorough understanding of the physical aging process is desirable. We examined the creep deformation of polycarbonate (PC) to reveal the effects of physical aging on creep behavior. The effects were dependent on both time and temperature. The relationship between physical aging and creep behavior exemplified superposition principles with regard to time and both pre-test aging time and pre-test aging temperature. The superposition principles allowed the calculation of creep deformations at a given temperature; the calculated results were corroborated by experimental data.     

Production of hyaluronic‐acid‐based cell‐enclosing microparticles and microcapsules via enzymatic reaction using a microfluidic system

This article describes the preparation of cell‐enclosing hyaluronic acid (HA) microparticles with solid core and microcapsules with liquid core through cell‐friendly horseradish peroxidase (HRP)‐catalyzed hydrogelation. The spherical vehicles were made from HA derivative possessing phenolic hydroxyl moieties (HA‐Ph) cross‐linkable through the enzymatic reaction by extruding cell‐suspending HA‐Ph aqueous solution containing HRP from a needle of 180 μm in inner diameter into the ambient coaxial flow of liquid paraffin containing H₂O₂ in a microtubule of 600 μm in diameter. By altering the flow rate of liquid paraffin, the diameters of gelatin and HA‐Ph microparticles were varied in the range of 120–220 μm and 100–300 μm, respectively. The viability of the enclosed human hepatoma HepG2 cells in the HA‐Ph microparticles of 180 μm in diameter was 94.2 ± 2.3%. The growth of the enclosed HepG2 cells was enhanced by decreasing the HRP concentration. The microcapsules of 200 μm in diameter were obtained by extruding HA‐Ph aqueous solution containing thermally liquefiable cell‐enclosing gelatin microparticles of 150 μm in diameter using the same microfluidic system. The enclosed cells grew and filled the cavity within 10 days. Spherical tissues covered with a heterogeneous cell layer were obtained by degrading the microcapsule membrane using hyaluronidase after covering the surface with a heterogeneous cell layer. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43107.     

The formation of graphene–titania hybrid films and their resistance change under ultraviolet irradiation

We report the fabrication of hybrid films of graphene and monolayer titania using a simple electrostatic self-assembly method. Ultraviolet (UV) responses of the hybrid films based on the graphene–titania structure were investigated. We observed that the resistance of the graphene–titania hybrid increased exponentially with UV irradiation time and decreased exponentially when UV was turned off. Time constants of the order of hundreds of seconds were identified and found to be sensitive to the gas environment of graphene. The UV response as well as the time constant is tunable by varying the number of titania layers. Our results confirmed that UV irradiation played a significant role in the resistance modulation of graphene as well as graphene–titania hybrid films.     

Conductive and flexible multi-walled carbon nanotube/polydimethylsiloxane composites made with naphthalene/toluene mixture

Conventional conductive materials face challenges when utilizing them for flexible and wearable electronics and soft robotics. Carbon nanotube/polydimethylsiloxane (CNT/PDMS) composites are a promising alternative to the conventional hard conductors because they are light and can realize large deformation. To date, well dispersion of CNTs into PDMS to increase conductivity while maintaining flexibility remains challenging. We aimed at developing highly electrically conductive and flexible multi-walled carbon nanotube/PDMS (MWCNT/PDMS) composites. To this end, we proposed a method to enhance the dispersion of MWCNTs into PDMS using naphthalene and toluene. Our results showed that the addition of naphthalene and toluene into the composites improved dispersion of the MWCNTs and increased the direct current (DC) electrical conductivity. We also found that the morphology of primary aggregates of the MWCNTs influenced the DC electrical conductivity of the composites. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48167.