Molecular structure, vibrational spectra, HOMO, LUMO and NMR studies of 1,2-dichloro-4-nitrobenzene and 2,3,5,6-tetrachloro-1-nitrobenzene based on density functional calculations

Krishnakumar, V.; Barathi, D.; Mathammal, R.

doi:10.1016/j.saa.2011.10.024

Cited by 13 publications

(2 citation statements)

References 19 publications

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“…H per moleculeAve. C per moleculeTypes of moleculesAlver [63]124118Boron-based compoundAsiri et al [64]1331216Organic photochromic compoundBagno et al [66]4442118Small organic molecules with constrained conformationsBarkowski et al [67]15835031Pentacyclic terpenoids (fernenes)Coruh et al [68]125813Heterocyclic aromatic compoundFulmer et al [69]331494Commonly used NMR solventsHill et al [70]1703330Complex drug with multiple chemical groups and one stereocenterIzgi et al [71]124158Molecule with cyclohexene (C 6 H 10 ) attached to ethylamine (C 2 H 7 N)Karabacak et al [72]11787Planar benzene ring with attached B(OH) 2 and two F groupsKrishnakumar et al [74]21646Agrochemical intermediate compounds with planar ringsKrishnakumar et al [73]2167…”

Section: Methodsmentioning

confidence: 99%

An automated framework for NMR chemical shift calculations of small organic molecules

Yesiltepe¹,

Nuñez²,

Colby³

et al. 2018

J Cheminform

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When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties—specifically NMR chemical shifts in this manuscript—via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries. Electronic supplementary materialThe online version of this article (10.1186/s13321-018-0305-8) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

An automated framework for NMR chemical shift calculations of small organic molecules

Yesiltepe¹,

Nuñez²,

Colby³

et al. 2018

J Cheminform

View full text Add to dashboard Cite

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“…Development of quantum computational tools for investigating molecular properties helps to select molecules for particular applications thereby reducing considerably both expenses on chemicals and the generation of chemical wastes. Various computational methods are available to predict the chemical and physical properties of molecular systems which are useful in interpreting the experimental results and also helps in designing new materials for electronic devices [7,8]. The density functional theory (DFT) is invoked to obtain cost effective molecular modelling methods which provides meaningful results of optimized structures, charge transport, linear and nonlinear optical properties.…”

Section: Introductionmentioning

confidence: 99%

Electron Transport and Optical Properties of Pyrene derivatives for OLED Applications: A DFT Approach

Felscia,

Rajkumar,

Mary

2023

Preprint

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The charge transport properties of aminopyrene (APy) and pyrene acetic acid (PAA) are investigated using the B3LYP/6-31++G(d,p) level of theory. The charge distributions of the systems are analyzed using the natural population analysis (NPA) and the plot of molecular electrostatic potential (MEP). Reorganization energy calculation is carried out to identify the charge transport behavior of the molecules under study. The energy level diagram and electrophilicity index identifies APy as the better system and its mobility computations are also performed. The energy level alignment, fluorescence behavior and mobility of charges suggest the application of APy in the design of electron transport layer (ETL) in blue OLED devices.

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Enhanced catalytic performance of B-doped SiC supported Ni catalysts for the hydrogenation of nitroarenes

Zhao,

Yao,

et al. 2024

Applied Catalysis A: General

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Molecular structure, vibrational spectra, HOMO, LUMO and NMR studies of 1,2-dichloro-4-nitrobenzene and 2,3,5,6-tetrachloro-1-nitrobenzene based on density functional calculations

Cited by 13 publications

References 19 publications

An automated framework for NMR chemical shift calculations of small organic molecules

An automated framework for NMR chemical shift calculations of small organic molecules

Electron Transport and Optical Properties of Pyrene derivatives for OLED Applications: A DFT Approach

Enhanced catalytic performance of B-doped SiC supported Ni catalysts for the hydrogenation of nitroarenes

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