The heat risk during hardening of dental glass-ionomer cements using a light-curing

Journal of Thermal Analysis and Calorimetry - An use of a polymerization lamp to irradiate chemically hardened glass-ionomer materials may improve their properties and accelerate the setting time....     

Silica-based diffusion probes for use in FRAP and NMR-diffusometry

Development of multi-purpose probes for mass transport measurements is of importance to gain knowledge in diffusional behaviour in heterogeneous structures such as food, hygiene or pharamceuticals. By combining different techniques, such as Fluorescence Recovery After Photobleaching (FRAP) and Nuclear Magnetic Resonance Diffusometry (NMR-d), information of both local and global diffusion can be collected and used to gain insights on for example material heterogeneities and probe-material interactions. To obtain a FRAP-responsive probe, fluorescent silica particles were produced using fluorescent preconjugates added in a modified Stöber process. A NMR-d responsive moiety was introduced by derivatizing the fluorescent silica particles with polyethylene glycol. The particle size distributions were determined by dynamic light scattering and transmission electron microscopy and these measurements were compared to value extrapolated from diffusion measurements using FRAP and NMR-d. The good agreement between the FRAP and NMR-d measurements demonstrates the potential of multi-purpose probes for future applications concerning mass transport at local and global scale simultaneously.     

1/f Noise modeling of InAs/GaSb superlattice mid-wavelength infrared detectors

The empirical 1/f noise model for p\(^{+}\)-p-n infrared detector made of type-II InAs/GaSb superlattice material is presented. It is shown that 1/f noise magnitude can be accurately estimated if dark current contributions are determined and noise coefficients are known. It is found that the shunt, the bulk generation–recombination, and the trap-assisted tunneling currents contribute to the total 1/f noise. No 1/f noise connected with the diffusion and the band-to-band tunneling currents is observed.     

The BSM-AI project: SUSY-AI–generalizing LHC limits on supersymmetry with machine learning

A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets – each tested against 200 signal regions by ATLAS – have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least \(93\%\). It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/.     

Theoretical evaluation of NMR shifts in polycyclic aromatic hydrocarbons

ABSTRACT

Using computational chemistry methodology, we evaluate the proton magnetic shieldings and the corresponding chemical shifts of 12 polycyclic aromatic hydrocarbons that derive from chrysene, perylene and picene. Due to the large size of the studied compounds, we resort to density functional theory (DFT) and use it together with the B3LYP and the KT1 functionals. After a systematic method and basis set selection study carried out on methane, benzene and anthracene, the DFT(B3LYP) method and the 6-31G*, 6-31G** and 6-311++G** bases are selected to carry out the calculations, because of the efficiency in providing shifts close to the experimental data available. Additionally, we select the DFT(KT1) method together with the aug-pcS-1 basis set, and HF/6-31G* shifts are also calculated. In order to estimate the error in the theoretical results, we take as reference accurate experimental chemical shifts obtained for the molecules under investigation. Extra measurements are needed for this purpose and are included in the present work. The best combination of method and basis set is DFT(B3LYP)/6-31G**, proving to be very efficient in getting shifts close to experiment at a relatively low computational cost, and therefore we recommend it for the evaluation of proton shifts in larger polycyclic aromatic hydrocarbons.     

The method for calculation of carrier concentration in narrow-gap n-type doped Hg<Subscript>1−x</Subscript>Cd<Subscript>x</Subscript>Te structures

A simple method for the computation of carrier concentration in n-type doped Hg_1?xCd_xTe (MCT) structures is proposed. The method is based on the postulate of the existence of donor bands. In our model the donor bands are postulated to have a Gaussian distribution of density of states characterized by two parameters only (mean energy for this distribution and standard deviation). These parameters could be obtained with experimental data, which were comprised of a wide range of doping levels for various kinds of dopants.     

On the need of mode interpolation for data-driven Galerkin models of a transient flow around a sphere

We present a low-dimensional Galerkin model with state-dependent modes capturing linear and nonlinear dynamics. Departure point is a direct numerical simulation of the three-dimensional incompressible flow around a sphere at Reynolds numbers 400. This solution starts near the unstable steady Navier–Stokes solution and converges to a periodic limit cycle. The investigated Galerkin models are based on the dynamic mode decomposition (DMD) and derive the dynamical system from first principles, the Navier–Stokes equations. A DMD model with training data from the initial linear transient fails to predict the limit cycle. Conversely, a model from limit-cycle data underpredicts the initial growth rate roughly by a factor 5. Key enablers for uniform accuracy throughout the transient are a continuous mode interpolation between both oscillatory fluctuations and the addition of a shift mode. This interpolated model is shown to capture both the transient growth of the oscillation and the limit cycle.     

Bifurcation analysis of 4-axle rail vehicle models in a curved track

The dynamics of a diffusive predator–prey model with time delay and Michaelis–Menten-type harvesting subject to Neumann boundary condition is considered. Turing instability and Hopf bifurcation at positive equilibrium for the system without delay are investigated. Time delay-induced instability and Hopf bifurcation are also discussed. By the theory of normal form and center manifold, conditions for determining the bifurcation direction and the stability of bifurcating periodic solution are derived. Some numerical simulations are carried out for illustrating the theoretical results.     

Copolymerization of (Meth)acrylates with Olefins Using Activators Regenerated by Electron Transfer for Atom Transfer Radical Polymerization (ARGET ATRP)

Summary: Controlled copolymerization of polar (meth)acrylates with non-polar olefin monomers (1-octene, norbornene, vinylcyclohexane) was studied by ARGET (activators regenerated by electron transfer) ATRP (atom transfer radical polymerization). When a normal ATRP of n-butyl acrylate (nBA) and 1-octene was conducted, the polymerization resulted in relatively low conversion, limited control over the polymerization process and high polydispersity (PDI > 1.6). This was due to formation of a dormant species, by reaction of 1-octene radicals with Cu(II) deactivator, that could not be reactivated. However, in ARGET ATRP with 10 ppm amounts of Cu-based catalyst, higher yields and a better controlled copolymerization was obtained (PDI < 1.4), because the low concentration of Cu(II) deactivator reduced the formation of the non-reactive dormant species. The influence of the amount of Cu catalyst, ligand structure, initiators with different halogens, the reaction temperature, and monomer feed ratio were also investigated for ARGET ATRP. In copolymerization of (meth)acrylates with non-polar alkenes, the level of control and the total conversion in ARGET ATRP were higher than those for normal ATRP.     

On Numerical Simulation of Interlaminar Failure of Composites

This paper deals with one of the most dangerous failure modes in fiber reinforced composites, namely delamination. The laminated structure is modeled by a solid–shell finite element. The mechanical modeling of delamination onset and propagation is based upon a cohesive zone model implemented into a cohesive element located between laminae of a composite structure. The numerical simulations are accomplished within the commercial software package ABAQUS by the implementation of a user–written finite element. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)