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Networks conducting

Figure 17.4 Cartoon representation of strategies for studying and exploiting enzymes on electrodes that have been used in electrocatalysis for fuel cells, (a) Attachment or physisorption of an enzyme on an electrode such that redox centers in the protein are in direct electronic contact with the surface, (b) Specific attachment of an enzyme to an electrode modified with a substrate, cofactor, or analog that contacts the protein close to a redox center. Examples include attachment of the modifier via a conductive linker, (c) Entrapment of an enzyme within a polymer containing redox mediator molecules that transfer electrons to/from centers in the protein, (d) Attachment of an enzyme onto carbon nanotubes prepared on an electrode, giving a large surface area conducting network with direct electron transfer to each enzyme molecule. Figure 17.4 Cartoon representation of strategies for studying and exploiting enzymes on electrodes that have been used in electrocatalysis for fuel cells, (a) Attachment or physisorption of an enzyme on an electrode such that redox centers in the protein are in direct electronic contact with the surface, (b) Specific attachment of an enzyme to an electrode modified with a substrate, cofactor, or analog that contacts the protein close to a redox center. Examples include attachment of the modifier via a conductive linker, (c) Entrapment of an enzyme within a polymer containing redox mediator molecules that transfer electrons to/from centers in the protein, (d) Attachment of an enzyme onto carbon nanotubes prepared on an electrode, giving a large surface area conducting network with direct electron transfer to each enzyme molecule.
Danescu, R. I., and Zumbrunnen, D. A., Creation of conducting networks among particles in polymer melts by chaotic mixing. J. Thermoplast Composites, 11, 299-320 (1998). [Pg.199]

The main idea of the model is that in order for the electrically conductive additive to effectively fulfill its functions, it must form a closed cluster (skeleton of the interconnected carbon particles, which is the conducting pass in electrode matrix). Once the sufficient conductive network was formed, further considerable increase of additive content is not needed, as it leads to decrease in the percentage of the electrochemically active constituent in the electrode. [Pg.316]

On one hand, the partially oxidized TTFs are crucial to obtain conducting network but, on the other hand, the penetration of anions in the organic lattice prevent any significant electronic conductivity. The material is an insulator. [Pg.68]

Due to their high aspect ratio, nanocarbons dispersed in a polymer matrix can form a percolating conductive network at very low volume fractions (< 0.1 %). The conductivity of a composite above the transition from an insulator can be described by the statistical percolation using an excluded volume model [22,23] to yield the following expression ... [Pg.232]

While conductivities of nanocarbons dispersed in polymers fall short of those of metals, a variety of applications can be unlocked by turning an insulating matrix into a conductor, which requires only small volume fractions that can therefore keep the system viscosity at a level compatible with composite processing techniques. Of particular interest are novel functionalities of these conductive matrices that exploit the presence of a conductive network in them, such as structural health monitoring (SHM) based on changes in electrical resistance of the nanocarbon network as it is mechanically deformed [30]. [Pg.233]

Fig. 12.1 Main structural models of graphene-metal oxide hybrids, (a) Anchored model oxide particles are anchored to the graphene surface, (b) Encapsulated model oxide particles are encapsulated by graphene, (c) Sandwich-like model graphene is sandwiched between the metal oxide layers, (d) Layered model a structure composed of alternating layers of oxide nanoparticles and graphene, (e) Mixed model graphene and oxide particles are mechanically mixed and graphene sheets form a conductive network among the oxide particles. Red metal oxide Blue graphene. Reprinted with permission from [41]. Copyright 2012, Elsevier B.V. Fig. 12.1 Main structural models of graphene-metal oxide hybrids, (a) Anchored model oxide particles are anchored to the graphene surface, (b) Encapsulated model oxide particles are encapsulated by graphene, (c) Sandwich-like model graphene is sandwiched between the metal oxide layers, (d) Layered model a structure composed of alternating layers of oxide nanoparticles and graphene, (e) Mixed model graphene and oxide particles are mechanically mixed and graphene sheets form a conductive network among the oxide particles. Red metal oxide Blue graphene. Reprinted with permission from [41]. Copyright 2012, Elsevier B.V.
Li and co-workers [139] synthesized Pt (5 30wt%) nanoparticles supported on CNFs using a modified ethylene glycol method. Pt-CNF based MEAs with 50 wt% Nafion exhibited higher cell performance than the carbon black based MEAs with an optimized 30 wt% Nafion content (Fig. 14.11). This was attributed to the larger length to diameter ratio of CNFs that allows the formation of conductive networks in the Nafion matrix [140]. [Pg.373]

Two complex tissues, the xylem and phloem, provide the conducting network or "circulatory system" of plants. In the xylem or woody tissue, most of the cells are dead and the thick-walled tubes (tracheids) serve to transport water and dissolved minerals from the roots to the stems and leaves. The phloem cells provide the principal means of downward conduction of foods from the leaves. Phloem cells are joined end to end by sieve plates, so-called because they are perforated by numerous minute pores through which cytoplasm of adjoining sieve cells appears to be connected by strands 5-9 pm in diameter.154 Mature sieve cells have no nuclei, but each sieve cell is paired with a nucleated "companion" cell. [Pg.30]

Substrate Treatment. When the desired image is developed in the resist, the pattern created provides a template for substrate modification. The various chemical and physical modifications currently used can be classified into additive and subtractive treatments. Examples of additive treatments include the insertion of dopants (by either diffusion or ion implantation) to alter the semiconductor characteristics and metal deposition (followed by lift-off or electroplating) to complete a conduction network. In most cases, however, the substrate material is etched by a subtractive process. [Pg.368]

G. B. Bianchet, G. Jaycox and C. Nuckolls, Self-assembled three-dimensional conducting network of single-wall carbon nanotubes , Appl. Phys. Lett. 85, 828-830 (2004). [Pg.269]

Guo Y-G, Hu YS, Sigle W, Maier J. Superior electrode performance of nanostructured mesoporous TiC>2 (anatase) through efficient hierarchical mixed conducting networks. Adv Mater 2007 19(16) 2087-91. [Pg.247]

Zhang et al. studied the effect of conductive network formation in a polymer melt on the conductivity of MWNT/TPU composite systems (91). An extremely low percolation threshold of 0.13 wt% was achieved in hot-pressed composite film samples, whereas a much higher CNT concentration (3-4 wt%) is needed to form a conductive network in extruded composite strands. This was explained in terms of the dynamic percolation behavior of the CNT network in the polymer melt. The conductivity of extruded strand showed a hopping resistivity dominated behavior at low concentrations and a dynamic percolation induced network dominated behavior at higher concentrations. It was shown that a higher temperature can reduce the filler concentration required for the dynamic percolation to take effect. [Pg.161]


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See also in sourсe #XX -- [ Pg.33 ]

See also in sourсe #XX -- [ Pg.33 ]

See also in sourсe #XX -- [ Pg.33 ]




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Conductive microfibril network

Filler networks conductive

Hierarchical 3D Mixed Conducting Networks

Network conductive

Proton conduction mechanism water channel network

Random Network Model of Membrane Conductivity

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