Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Artificial neural network & Finite element method. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Improved mechanical load transfer between shells of multiwalled carbon nanotubes

Abstract: Ultra-low friction between shells of multiwalled carbon nanotubes indicates that, when the nanotubes are used as reinforcement agents, the mechanical load is carried by the outermost shell of the tube only. We suggest using small-dose electron or ion irradiation to partially transfer the load to the nanotube inner shells. Employing analytical potential molecular dynamics, we simulate the response of multiwalled nanotubes to an external force acting on one of the shells with irradiation-induced defects which bridge adjacent shells. We demonstrate that a small number of defects can increase the interlayer shear strength by several orders of magnitude. We further discuss how the irradiation-induced load transfer can be measured experimentally and how, by manipulating the particle beam characteristics, one can improve the load transfer between preselected shells.

Synthesis and Characterization of Lactic Acid Based Telechelic Prepolymers

Abstract: The synthesis of low molecular weight (Mn (NMR) < 7000 g/mol) lactic acid prepolymers by condensation polymerization of l-lactic acid was investigated. Besides the l-lactic acid polymer, hydroxyl- and carboxyl-terminated telechelic prepolymers were also prepared by the addition of small amounts of 1,4-butanediol and adipic acid, respectively. All polymerizations were carried out in a melt with tin octoate as the catalyst. The products were characterized by differential scanning calorimetry, gel permeation chromatography (GPC), IR, 1H-NMR, and 13C-NMR. According to NMR, the resulting prepolymers contained less than 1 mol % of lactic acid monomer and less than 4.1 mol % of lactide. End group analysis of the polymers was carried out by comparing the NMR spectra of different polymers. According to NMR, the lactic acid can be copolymerized so that the resulting prepolymer chains have only one kind of end group, hydroxyl or carbonyl. The integrated area of the identified end group peak (hydroxyl or acid) was th...

Boundary regularity for the Ricci equation, geometric convergence, and Gel’fand’s inverse boundary problem

Abstract: This paper explores and ties together three themes. The first is to establish regularity of a metric tensor, on a manifold with boundary, on which there are given Ricci curvature bounds, on the manifold and its boundary, and a Lipschitz bound on the mean curvature of the boundary. The second is to establish geometric convergence of a (sub)sequence of manifolds with boundary with such geometrical bounds and also an upper bound on the diameter and a lower bound on injectivity and boundary injectivity radius, making use of the first part. The third theme involves the uniqueness and conditional stability of an inverse problem proposed by Gel'fand, making essential use of the results of the first two parts.

Unfolding Partiality and Disjunctions in Stable Model Semantics

Abstract: The paper studies an implementation methodology for partial and disjunctive stable models where partiality and disjunctions are unfolded from a logic program so that an implementation of stable models for normal (disjunction-free) programs can be used as the core inference engine. The unfolding is done in two separate steps. Firstly, it is shown that partial stable models can be captured by total stable models using a simple linear and modular program transformation. Hence, reasoning tasks concerning partial stable models can be solved using an implementation of total stable models. Disjunctive partial stable models have been lacking implementations which now become available as the translation handles also the disjunctive case. Secondly, it is shown how total stable models of disjunctive programs can be determined by computing stable models for normal programs. Hence, an implementation of stable models of normal programs can be used as a core engine for implementing disjunctive programs. The feasibility of the approach is demonstrated by constructing a system for computing stable models of disjunctive programs using the smodels system as the core engine. The performance of the resulting system is compared to that of dlv which is a state-of-the-art special purpose system for disjunctive programs.

Enhanced bandwidth of supercontinuum generated in microstructured fibers.

Abstract: Enhancement of the bandwidth of supercontinuum generated in microstructured fibers with a tailored dispersion profile is demonstrated experimentally. The fibers are designed to have two zero-dispersion wavelengths separated by more than 700 nm, which results in an amplification of two dispersive waves at visible and infrared wavelengths. The underlying physics behind the broad continuum formation is discussed and analyzed in detail. The experimental observations are confirmed through numerical simulations.