Toyota

About: Toyota is a company organization based out in Safenwil, Switzerland. It is known for research contribution in the topics: Internal combustion engine & Battery (electricity). The organization has 40032 authors who have published 55003 publications receiving 735317 citations. The organization is also known as: Toyota Motor Corporation & Toyota Jidosha KK.

Hybrid vehicle drive system having clutch between engine and synthesizing/distributing mechanism which is operatively connected to motor/generator

Abstract: A hybrid drive system for a motor vehicle, having an engine operated by combustion of a fuel, an electric energy storage device for storing an electric energy, a motor/generator connected to the electric energy storage device, and a synthesizing/distributing mechanism which includes a first rotary element, a second rotary element connected to the motor/generator, and a third rotary element, and an output member connected to the third rotary element, wherein a first clutch is provided for connecting the first rotary element and the engine, and a second clutch is provided for connecting two elements of the first, second and third rotary elements of the synthesizing/distributing mechanism, for rotation of the two elements as a unit.

Predicting Catalytic Activity of Nanoparticles by a DFT-Aided Machine-Learning Algorithm

Abstract: Catalytic activities are often dominated by a few specific surface sites, and designing active sites is the key to realize high-performance heterogeneous catalysts. The great triumphs of modern surface science lead to reproduce catalytic reaction rates by modeling the arrangement of surface atoms with well-defined single-crystal surfaces. However, this method has limitations in the case for highly inhomogeneous atomic configurations such as on alloy nanoparticles with atomic-scale defects, where the arrangement cannot be decomposed into single crystals. Here, we propose a universal machine-learning scheme using a local similarity kernel, which allows interrogation of catalytic activities based on local atomic configurations. We then apply it to direct NO decomposition on RhAu alloy nanoparticles. The proposed method can efficiently predict energetics of catalytic reactions on nanoparticles using DFT data on single crystals, and its combination with kinetic analysis can provide detailed information on stru...

Thermal and transport properties of the Heusler-type Fe 2 VAl 1 − x Ge x ( 0 ≤ x ≤ 0.20 ) alloys: Effect of doping on lattice thermal conductivity, electrical resistivity, and Seebeck coefficient

Abstract: We report on the thermoelectric properties of the Heusler-type ${\mathrm{Fe}}_{2}{\mathrm{VAl}}_{1\ensuremath{-}x}{\mathrm{Ge}}_{x}$ alloys with compositions $0\ensuremath{\le}x\ensuremath{\le}0.20$. While ${\mathrm{Fe}}_{2}\mathrm{VAl}\phantom{\rule{0.3em}{0ex}}(x=0)$ exhibits a semiconductorlike behavior in electrical resistivity, a slight substitution of Ge for Al causes a significant decrease in the low-temperature resistivity and a large enhancement in the Seebeck coefficient, reaching $\ensuremath{-}130\phantom{\rule{0.3em}{0ex}}\mathrm{\ensuremath{\mu}}\mathrm{V}∕\mathrm{K}$ for $x=0.05$ at around room temperature. Comparison with the ${\mathrm{Fe}}_{2}{\mathrm{VAl}}_{1\ensuremath{-}x}{\mathrm{Si}}_{x}$ system demonstrates that the compositional variation of the Seebeck coefficient falls on a universal curve irrespective of the doping elements (Ge and Si), both of which are isoelectronic elements. The net effect of doping is most likely to cause a rigid-bandlike shift of the Fermi level from the central region in the pseudogap. In spite of a similar decrease in the electrical resistivity with composition of Ge and Si, the thermal conductivity decreases more rapidly for the Ge substitution. It is concluded that doping of heavier atoms such as Ge reduces more effectively the lattice thermal conductivity while retaining the low electrical resistivity as well as the large Seebeck coefficient.