0000000000881311

AUTHOR

Jinyu Li

showing 2 related works from this author

Switch in Relative Stability between cis and trans 2-Butene on Pt(111) as a Function of Experimental Conditions: A Density Functional Theory Study

2018

International audience; The adsorption of cis and trans 2-butenes on Pt(111) has been studied as a function of hydrogen coverage OH by means of calculations based on density functional theory (DFT) with the inclusion of dispersion forces. All hydrogen coverages have been considered, from 0 to 1.00 monolayer (ML). For each case, the di-sigma and pi adsorption geometries of the olefins have been compared at a surface coverage of theta(C4H8) = 0.11 ML. Calculations of the Gibbs free energies of these systems have identified the most stable 2-butene isomer (cis or trans) as a function of coverage, temperature, and pressure. In particular, focus was placed on two sets of conditions, namely, one …

ab-initioMaterials scienceHydrogenmolecular-dynamicschemistry.chemical_element010402 general chemistryenergy recoil scattering7. Clean energy01 natural sciencesDFTCatalysischemistry.chemical_compoundsymbols.namesakecis-trans isomerizationAdsorptionPt(111)Monolayersingle-crystal surfaces[CHIM]Chemical Sciences[PHYS]Physics [physics]1st-principles calculationsethylene hydrogenation010405 organic chemistrymetal-surfacesheterogeneous catalystsGeneral ChemistryAtmospheric temperature range2-Butenefree energyhydrogenation catalysisCis trans isomerization0104 chemical sciencesGibbs free energyH coveragechemistry13. Climate actionadsorptionsymbolsPhysical chemistryDensity functional theory2-butenesolid-surfacestemperature diagram
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Application of EαNets to Feature Recognition of Articulation Manner in Knowledge-Based Automatic Speech Recognition

2006

Speech recognition has become common in many application domains. Incorporating acoustic-phonetic knowledge into Automatic Speech Recognition (ASR) systems design has been proven a viable approach to rise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as detectors for manner of articulation attributes starting from representations of speech signal frames. In this paper, a set of six detectors for the above mentioned attributes is designed based on the E-αNet model of neural networks. This model was chosen for its capability to learn hidden acti…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniArtificial neural networkGeneralizationComputer scienceSpeech recognitionSIGNAL (programming language)cognitive architectureFeature recognitionneural networks speech recognitionAnthropomorphic robotsManner of articulationSystems designSet (psychology)Articulation (phonetics)Robots
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