Preliminary communication:Novel method for uniform orientation of liquid crystal molecules by a polyimide surface exposed to a water flow

A novel technique for surface-induced orientation of liquid crystal (LC) molecules is proposed, using a polyimide surface exposed to a unidirectional water flow. The LC molecules director was unidirectionally oriented along the water flow direction on the polyimide surface. The orientational state of the LC director was strongly dependent upon whether the water flow exposure was carried out before or after thermal curing for imidization, and also upon the temperature of water flow.     

Superstructure-mechanical property relationships of polyglutamic acid esters

A study has been made of the relaxation phenomena in a series of poly-γ-n-alkyl-D-glutamates having linear side chains of different lengths in the temperature range from ?170 to 250°C. The solid-state films of poly-γ-n-alkyl-D-glutamate were cast from solutions in α-helix and random coil forming solvents. The technique of dynamic mechanical relaxation at various frequencies up to 110 Hz was used in the investigation. X-ray, IR, and density measurements were used as supplements to the mechanical measurements in order to determine the relationships between the mechanical properties and superstructures. Six relaxation regions are discernible in the temperature range investigated, and these are labeled α, β, γ, δ, ε, and ζ in order of decreasing temperature. The following mechanisms are assigned to these relaxations: (1) The α-relaxation arises from the thermal molecular motion of the α-helices in the crystalline region. (2) The β relaxation arises from micro-Brownian segmental motion of the disordered region or the distorted part of the a-helices, (3) The γ and δ relaxations are associated with motions of the entire side-chain groups in the crystalline and the disordered regions, respectively. (4) The ε and ζ relaxations involve the conformational rearrangements of n-alkyl groups including carboxyl group and n-alkyl groups alone, respectively.     

Assembly of Na3V2(PO4)3 Nanoparticles Confined in a One‐Dimensional Carbon Sheath for Enhanced Sodium‐Ion Cathode Properties

Structural and morphological control is an effective approach for improvement of electrochemical properties in rechargeable batteries. One‐dimensionally assembled structure composed of NASICON‐type Na₃V₂(PO₄)₃ nanoparticles were fabricated through an electrospinning method to meet the requirements for the development of efficient electrode materials in Na‐ion batteries. High‐temperature treatment of electrospun precursor fibers under an argon flow provides a nonwoven fabric of nanowires comprising crystallographically oriented nanoparticles of NASICON‐type Na₃V₂(PO₄)₃ within a carbon sheath. The mesostructure comprising NASICON‐type Na₃V₂(PO₄)₃ and carbon give a short sodium‐ion transport pass and an efficient electron conduction pass. Electrochemical properties of NASICON‐type Na₃V₂(PO₄)₃ are improved on the basis of one‐dimensional nanostructures designed in the present study.     

Temperature dependent light transmission-light scattering switching of (homeotropic liquid crystalline polymer network/liquid crystals/chiral dopant) composite film

A (photo-polymerizable liquid crystal (LC) monomer/LCs/chiral dopant/photoinitiator) mixture with a smectic A (SmA)-chiral nematic (N*) phase transition was sandwiched between two ITO glass substrates which were not subjected to any surface orientation treatment. When an electric field-induced homeotropically oriented SmA phase of the mixture was irradiated with UV light, an oriented liquid crystalline polymer (LCP) network was formed upon photo-polymerization of the LC monomer. Then, a (homeotropically oriented LCP network/LCs/chiral dopant) composite with a SmA-N* phase transition was prepared. A focal-conic texture appeared in the heat-induced N* phase of the composite upon heating from the transparent state of the homeotropically oriented SmA phase; the focal-conic texture exhibited strong light scattering. Upon cooling the composite to the SmA phase, this phase was again homeotropically oriented due to the strong intermolecular interaction between the LC molecules and the homeotropically oriented LCP network. Thus, the transparent state of the SmA phase and the light scattering state of the N* phase occurred reversibly upon cooling and heating, accompanied by the thermal SmA-N* phase transition.     

Determination of chromium, copper and lead in river water by graphite-furnace atomic absorption spectrometry after coprecipitation with terbium hydroxide.

Coprecipitation with terbium hydroxide quantitatively recovered trace amounts of chromium(III), copper(II) and lead(II) at pH 8.4 - 10.8, 8.0 - 11.5 and 8.7 - 11.5, respectively. The precipitate was dissolved in 0.85 mol dm(-3) nitric acid, and the analytes were determined by graphite-furnace atomic absorption spectrometry (GF-AAS). The presence of terbium (up to 7 g dm(-3)) did not interfere with the determination. The detection limits were 0.3 microg dm(-3) for chromium, 0.4 microg dm(-3) for copper and 0.5 microg dm(-3) for lead, when the analytes in 200 cm3 of the sample solution were concentrated into 10 cm3. The ions added to river or seawater were quantitatively recovered. Chromium and copper in a contaminated river water were successfully determined.     

A neural network system for solving an assortment problem in the steel industry

A neural network model for solving an assortment problem found in the iron and steel industry is discussed in this paper. The problem arises in the yard where steel plate is cut into rectangular pieces. The neural network model can be categorized as a Hopfield model, but the model is expanded to handle inequality constraints. The idea of a penalty function is used. A large penalty is applied to the network if a constraint is not satisfied. The weights are updated based on the penalty values. A special term is added to the energy function of the network to guarantee the convergence of the neural network which has this feature. The performance of the neural network was evaluated by comparison with an existing expert system. The results showed that the neural network has the potential to identify in a short time near-optimal solutions to the assortment problem. The neural network is used as the core of a system for dealing with the assortment problem. In building the neural networks system for practical use, there were many implementation issues. Some of them are presented here, and the fundamental ideas are explained. The performance of the neural network system is compared to that of the expert system and evaluated from the practical viewpoint. The results show that the neural network system is useful in handling the assortment problem.