Local Temperature as a Chemical Reactivity Descriptor

The quantum chemical calculations of organic compounds viz. (E)-1-(2,6-bis(4-chlorophenyl)-3-ethylpiperidine-4-ylidene)-2-phenyl-hydrazine (3ECl), (E)-1-(2,6-bis(4-chlorophenyl)-3-methylpiperidine-4-ylidene)-2-phenylhydrazine (3MCl) and (E)-1-(2,6-bis(4-chloro-phenyl)-3,5-dimethylpiperidine-4-ylidene)-2-phenylhydrazine (3,5-DMCl) have been performed by density functional theory (DFT) using B3LYP method with 6-311G (d,p) basis set. The electronic properties such as Frontier orbital and band gap energies have been calculated using DFT. Global reactivity descriptor has been computed to predict chemical stability and reactivity of the molecule. The chemical reactivity sites of compounds were predicted by mapping molecular electrostatic potential (MEP) surface over optimized geometries and comparing these with MEP map generated over crystal structures. The charge distribution of molecules predict by using Mulliken atomic charges. The non-linear optical property was predicted and interpreted the dipole moment (μ), polarizability (α) and hyperpolarizability (β) by using density functional theory.

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Chemical Reactivity Descriptor for the Oxide-Electrolyte Interface in Li-Ion Batteries

The Journal of Physical Chemistry Letters ◽

10.1021/acs.jpclett.7b01655 ◽

2017 ◽

Vol 8 (16) ◽

pp. 3881-3887 ◽

Cited By ~ 45

Author(s):

Livia Giordano ◽

Pinar Karayaylali ◽

Yang Yu ◽

Yu Katayama ◽

Filippo Maglia ◽

...

Keyword(s):

Chemical Reactivity ◽

Li Ion Batteries ◽

Electrolyte Interface ◽

Reactivity Descriptor ◽

Li Ion ◽

Oxide Electrolyte

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Chemical reactivity from local temperature

Science ◽

10.1126/science.373.6555.638-e ◽

2021 ◽

Vol 373 (6555) ◽

pp. 638.5-639

Author(s):

Yury Suleymanov

Keyword(s):

Chemical Reactivity ◽

Local Temperature

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Computational study of the chemical reactivity properties of bis (trimethyl tetrathiafulvalenyl) thiophene

JOURNAL OF ADVANCES IN CHEMISTRY ◽

10.24297/jac.v13i12.6072 ◽

2017 ◽

Vol 13 (1) ◽

pp. 5937-5947

Author(s):

Bendjeddou Amel ◽

Tahar Abbaz ◽

Abdelkrim Gouasmia ◽

Didier Villemin

Keyword(s):

Molecular Electrostatic Potential ◽

Computational Study ◽

Chemical Reactivity ◽

Energy Levels ◽

Electronic Energy ◽

Basis Set ◽

Chemometric Methods ◽

Lumo Energy ◽

Reactivity Descriptor ◽

Homo Lumo

The chemical reactivity of four bis (trimethyltetrathiafulvalenyl) thiophene is determined by its potential (electronic) energy (hyper) surface. All the quantum chemical calculations have been carried out using DFT level of theory, B3LYP functional and 6-31G(d,p) as basis set. Molecular electrostatic potential (MEP) and HOMO-LUMO energy levels have been performed. The local reactivity descriptor such as Fukui function is also performed to determine the reactive sites within the title molecules. The chemometric methods PCA and HCA were employed to find the subset of variables that could correctly classify the compounds according to their reactivity.

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Chemical reactivity descriptor based aromaticity indices applied to and systems

Journal of Molecular Structure THEOCHEM ◽

10.1016/j.theochem.2005.10.041 ◽

2006 ◽

Vol 759 (1-3) ◽

pp. 109-110 ◽

Cited By ~ 24

Author(s):

P.K. Chattaraj ◽

D.R. Roy ◽

M. Elango ◽

V. Subramanian

Keyword(s):

Chemical Reactivity ◽

Reactivity Descriptor

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Spatially Resolved Photoelectron Spectroscopy: Recent Progress and Future Plans

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010013554x ◽

1990 ◽

Vol 48 (2) ◽

pp. 388-389

Author(s):

A. M. Bradshaw

Keyword(s):

Photoelectron Spectroscopy ◽

Chemical Reactivity ◽

Target Material ◽

Orbital Energy ◽

Light Sources ◽

Analytical Technique ◽

Hartree Fock ◽

Spatially Resolved ◽

Koopmans Theorem ◽

Surface Analytical Technique

X-ray photoelectron spectroscopy (XPS or ESCA) was not developed by Siegbahn and co-workers as a surface analytical technique, but rather as a general probe of electronic structure and chemical reactivity. The method is based on the phenomenon of photoionisation: The absorption of monochromatic radiation in the target material (free atoms, molecules, solids or liquids) causes electrons to be injected into the vacuum continuum. Pseudo-monochromatic laboratory light sources (e.g. AlKα) have mostly been used hitherto for this excitation; in recent years synchrotron radiation has become increasingly important. A kinetic energy analysis of the so-called photoelectrons gives rise to a spectrum which consists of a series of lines corresponding to each discrete core and valence level of the system. The measured binding energy, EB, given by EB = hv−EK, where EK is the kineticenergy relative to the vacuum level, may be equated with the orbital energy derived from a Hartree-Fock SCF calculation of the system under consideration (Koopmans theorem).

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Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100132078 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1488-1489

Author(s):

Thomas W. Shattuck ◽

James R. Anderson ◽

Neil W. Tindale ◽

Peter R. Buseck

Keyword(s):

Cluster Analysis ◽

Chemical Reactivity ◽

Large Data ◽

Large Data Sets ◽

Particle Analysis ◽

Data Sets ◽

Halogen Chemistry ◽

Complete Study ◽

Components Analysis ◽

Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

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