Technical University of Berlin

About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.

Size-dependent morphology of dealloyed bimetallic catalysts: linking the nano to the macro scale

Abstract: Chemical dealloying of Pt binary alloy precursors has emerged as a novel and important preparation process for highly active fuel cell catalysts. Dealloying is a selective (electro)chemical leaching of a less noble metal M from a M rich Pt alloy precursor material and has been a familiar subject of macroscale corrosion technology for decades. The atomic processes occurring during the dealloying of nanoscale materials, however, are virtually unexplored and hence poorly understood. Here, we have investigated how the morphology and intraparticle composition depend on the particle size of dealloyed Pt-Co and Pt-Cu alloy nanoparticle precursor catalysts. To examine the size-morphology-composition relation, we used a combination of high-resolutionscanning transmission electron microscopy (STEM), transmission electron microscopy (TEM), electron energy loss (EEL) spectroscopy, energy-dispersive X-ray spectroscopy (EDS), and surface-sensitive cycling voltammetry. Our results indicate the existence of three distinctly different size-dependent morphology regimes in dealloyed Pt-Co and Pt-Cu particle ensembles: (i) The arrangement of Pt shell surrounding a single alloy core ("single core-shell nanoparticles") is exclusively formed by dealloying of particles below a characteristic diameter d(multiple cores) of 10-15 nm. (ii) Above d(multiple cores), nonporous bimetallic core-shell particles dominate and show structures with irregular shaped multiple Co/Cu rich cores ("multiple cores-shell nanoparticles"). (iii) Above the second characteristic diameter d(pores) of about 30 nm, the dealloyed Pt-Co and Pt-Cu particles start to show surface pits and nanoscale pores next to multiple Co/Cu rich cores. This structure prevails up to macroscopic bulklike dealloyed particles with diameter of more than 100 nm. The size-morphology-composition relationships link the nano to the macro scale and provide an insight into the existing material gap of dealloyed nanoparticles and highly porous bulklike bimetallic particles in corrosion science.

Invariant computations in local cortical networks with balanced excitation and inhibition

Abstract: Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area yet are carried out by networks that can vary widely within an area according to its functional architecture. Here we demonstrate a mechanism by which orientation selectivity is computed invariantly in cat primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity of both excitatory and inhibitory cells. Modeling results demonstrate that such covariation is a signature of recurrent rather than purely feed-forward processing and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.

Distributed algorithms for transmission power control in wireless sensor networks

Abstract: In a wireless, multi-hop sensor network, choosing transmission power levels has an important impact on energy efficiency and network lifetime. Two algorithms for dynamically adjusting transmission power level on a per-node basis are proposed here. Network lifetime, convergence speed as well as resulting network connectivity are used as figures of merit for these two algorithms. They have been evaluated in an indoor sensor environment. The network lifetime metrics of these two local algorithms are also benchmarked against power control algorithms using global information. We show that these local algorithms outperform fixed power level assignment and that the lifetime achieved by them is usually within a factor of two of globally computed solution while being scalable.