2001
DOI: 10.1070/rc2001v070n04abeh000638
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Size effects in chemistry of heterogeneous systems

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Cited by 130 publications
(48 citation statements)
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“…It is well-established that a change in size of a metal nanoparticle results into: (i) a variation of the mean coordination number, 1 (ii) a change of the equilibrium shape, 2 (iii) a shift of the d-band center relative to the Fermi level, 2−5 and (iv) an expansion or a contraction of the lattice parameter. 6,7 Strikingly, despite specific cases such as the oxidation of carbon monoxide (CO) on Au nanoparticles, 8,9 the intrinsic catalytic activity is usually depreciated when decreasing the metal nanoparticle size. 4,5 This holds particularly true in proton-exchange membrane fuel cells (PEMFCs), where Ptbased nanoparticles supported onto a high-surface area carbon electrocatalyze the hydrogen oxidation reaction (HOR) and the oxygen reduction reaction (ORR).…”
Section: ■ Introductionmentioning
confidence: 99%
“…It is well-established that a change in size of a metal nanoparticle results into: (i) a variation of the mean coordination number, 1 (ii) a change of the equilibrium shape, 2 (iii) a shift of the d-band center relative to the Fermi level, 2−5 and (iv) an expansion or a contraction of the lattice parameter. 6,7 Strikingly, despite specific cases such as the oxidation of carbon monoxide (CO) on Au nanoparticles, 8,9 the intrinsic catalytic activity is usually depreciated when decreasing the metal nanoparticle size. 4,5 This holds particularly true in proton-exchange membrane fuel cells (PEMFCs), where Ptbased nanoparticles supported onto a high-surface area carbon electrocatalyze the hydrogen oxidation reaction (HOR) and the oxygen reduction reaction (ORR).…”
Section: ■ Introductionmentioning
confidence: 99%
“…It depends greatly on the production method: either by nanocluster aggregation, in particular, under conditions close to thermodynamic equilibrium [226,227], or by dispersion from the consolidated substance during non-equilibrium thermodynamic processes while applying outside powerful energy fluxes. The latter method increases greatly the energy saturation of nanoparticles, which may lead to their specific behavior and cause the threshold phenomena (see, for example: [228][229][230][231][232][233][234]). In all cases, a significant role in forming the nano-structure stability is played self-organization phenomena [235] including those happening at the formation level of the above-mentioned non-autonomous phases with particular physical chemistry.…”
Section: Dissipative Phenomena Chemical Thermal Current and Magnetmentioning
confidence: 99%
“…In addition, neglecting the difference in the Grüneisen parameter ␥ under isochoric conditions can also potentially result in a large deviation because the lattice vibrations in nanoparticles associated with the Grüneisen parameter ␥ are influenced to a certain degree by the interfaces of nanoparticles ͑size effect͒. 24 The comparison of the predicted Hugoniots for porous 2024 Al, Cu, and Fe with the available experimental data clearly show that the deviation of predicted results with experimental data are generally increasing with increasing porosity, which is linked to the effects of the specific internal energy and other thermodynamic properties. In more recent works, 25,26 the Wu-Jing model 12 has been extended by the authors to incorporate thermal pressure of electrons and correlate the calculated Hugoniot of highly porous metals including tungsten, copper, iron, lead, and aluminum, with experimental data available in the Russian literature.…”
Section: Model Calculationsmentioning
confidence: 99%
“…The principal cause for the ineffectiveness of the Wu-Jing method is most possibly the neglect of the characteristic properties of Fe nanoparticles, in particular, the contribution of the very large specific surface energy associated with the internal energy of the system. 24 The applicability of the Wu-Jing method for predicting the Hugoniot nanopowder compact can possibly be improved by incorporating the difference in internal energy between the powder compact and the solid, and the size effect of nanoparticles on lattice vibrations as they relate to the Grüneisen parameter. The experimental data obtained in this work are particularly valuable for probing the shock densification of Fe nanopowder, for validating the models for nanopowder Hugoniot prediction, and for modeling the complete EOS of iron over a relatively wide range of initial density and temperature.…”
Section: Fig 9 Example Of a Typical Voltagementioning
confidence: 99%