Basis Set Research Articles

Kinetics and mechanism of the gas-phase reaction of the hydroxyl radical with meta-aminotoluene compound.

An ab initio investigation into the potential energy landscape of the meta-aminotoluene + •OHreaction has been conducted in this study. The calculated results reveal that the reaction channel leading to the product (NHC6H4CH3 + H2O) prevails under the 300-1700K temperature range, while the reaction path forming the product (NH2C6H4CH2 + H2O) dominates in the higher-temperature region (T ≥ 1800K). Within the specified temperature range, the product branching ratio for the former declines from 48 to 30%, while the latter shows an increase, reaching 29%. The overall second-order rate constants of the titled reaction obtained at the pressure 760Torr (N2) can be illustrated by the modified Arrhenius expression of ktotal = 1.46 × 10-13 T0.58 exp[(-0.759kcal.mol-1)/RT] cm3 molecule-1s-1 and ktotal = 1.86 × 10-22 T3.24 exp[(-5.086kcal.mol-1)/RT] cm3 molecule-1s-1, covering the temperature range of T = 300-600K and T > 600K, respectively. The total rate constant at the ambient conditions in this work, 1.43 × 10-11 cm3 molecule-1s-1, has been found to be roughly one order of magnitude lower than the available experimental data, ~ 1.2 × 10-10 cm3 molecule-1s-1, measured by Atkinson et al., Rinke et al., and Witte et al., or the theoretical value, 4.4 × 10-10 cm3 molecule-1s-1, and calculated by Abdel-Rahman and co-workers for the aniline + •OH reaction. The structures of reactants, transition states, intermediate states, and products of the meta-aminotoluene + •OHreaction are calculated with the aug-cc-pVTZ basis set and the methods DFT/B3LYP and CCSD(T). The rate constants and branching ratios in the 300-2000K temperature range are calculated with the statistical theoretical TST and RRKM master equation computations including tunneling corrections, with potential energy surface constructed by the CCSD(T)//B3LYP/aug-cc-pVTZ approach.

Frozen Natural Orbitals for the State-Averaged Driven Similarity Renormalization Group.

We present a reduced-cost implementation of the state-averaged driven similarity renormalization group (SA-DSRG) based on the frozen natural orbital (FNO) approach. The natural orbitals (NOs) are obtained by diagonalizing the one-body reduced density matrix from SA-DSRG second-order perturbation theory (SA-DSRG-PT2). We consider three criteria to truncate the virtual NOs for the subsequent electron correlation treatment beyond SA-DSRG-PT2. An additive second-order correction is applied to the SA-DSRG Hamiltonian to reintroduce correlation effects from the discarded orbitals. The FNO SA-DSRG method is benchmarked on 35 small organic molecules in the QUEST database. When keeping 98-99% of the cumulative occupation numbers, the mean absolute error in the vertical transition energies due to FNO is less than 0.01 eV. Using the same FNO threshold, we observe a speedup of 9 times compared to the conventional SA-DSRG implementation for nickel carbonyl with a quadruple-ζ basis set. The FNO approach enables nonperturbative SA-DSRG computations on chloroiron corrole [FeCl(C19H11N4)] with more than 1000 basis functions, surpassing the current limit of a conventional implementation.

Fostering a Holistic Understanding of the Full Volatility Spectrum of Organic Compounds from Benzene Series Precursors through Mechanistic Modeling.

A comprehensive understanding of the full volatility spectrum of organic oxidation products from the benzene series precursors is important to quantify the air quality and climate effects of secondary organic aerosol (SOA) and new particle formation (NPF). However, current models fail to capture the full volatility spectrum due to the absence of important reaction pathways. Here, we develop a novel unified model framework, the integrated two-dimensional volatility basis set (I2D-VBS), to simulate the full volatility spectrum of products from benzene series precursors by simultaneously representing first-generational oxidation, multigenerational aging, autoxidation, dimerization, nitrate formation, etc. The model successfully reproduces the volatility and O/C distributions of oxygenated organic molecules (OOMs) as well as the concentrations and the O/C of SOA over wide-ranging experimental conditions. In typical urban environments, autoxidation and multigenerational oxidation are the two main pathways for the formation of OOMs and SOA with similar contributions, but autoxidation contributes more to low-volatility products. NOx can reduce about two-thirds of OOMs and SOA, and most of the extremely low-volatility products compared to clean conditions, by suppressing dimerization and autoxidation. The I2D-VBS facilitates a holistic understanding of full volatility product formation, which helps fill the large gap in the predictions of organic NPF, particle growth, and SOA formation.

Essential oils from fennel plants as valuable chemical products: gas chromatography–mass spectrometry, FTIR, quantum mechanical investigation, and antifungal activity

AbstractIn the present study, the biomass produced by fennel plants (Foeniculum vulgare Mill.) was converted to yield bioactive chemicals, and the hydrodistillation method was used to extract the essential oils (EOs) from both the leaves and the umbels. The antifungal activity of the EOs was tested using bioassay against the development of Fusarium oxysporum MW854649 and Alternaria solani MT279570. Molecular spectroscopic detection techniques were used to evaluate the EO products using gas chromatography–mass spectrometer (GC–MS) and Fourier transform infrared spectroscopy (FTIR). GC–MS equipped with single quadruple analyzers have been used to measure the electron ionization (EI) mass spectra of the primary constituents of fennel EOs at 70 eV. The main chemical compounds in the EO from leaves were anethole, estragole, D-limonene, trans-β-ocimene, and fenchone, with percentages of 37.94, 35.56, 17.46, 1.53, and 1.49%, respectively. The abundant compounds in the EO from umbels were estragole, anethole, D-limonene, fenchone, and γ-terpinene, with percentages of 51.18, 25.08, 12.22, 6.57, and 2.86%, respectively. EI mass spectral fragmentation of the major compounds D-limonene, estragole, anethole, and fenchone has been investigated. Umbels and leaf EOs at 5000 mg/L displayed the strongest suppression of fungal growth against A. solani, with values of 87.78% and 79.63%, respectively, compared to the positive control (94.44%). The EOs from umbels and leaves at 5000 mg/L showed the highest inhibition of fungal growth against F. oxysprium as compared to the positive control (94.44%), with values of 77.77% and 72.96%, respectively. All of the important ions—including a few distinctive fragment ions—have comprehensive fragmentation pathways defined. Based on EI, the main routes of fragmentation for the primary compounds have been identified. The existence of alkenes, aliphatic alcohols, ethers, carboxylic acids, ester compounds, alkanes, hydrogen-bonded alcohols, and phenols was demonstrated by the FTIR analysis of fennel EOs. On the other hand, the reactive behavior of the studied molecules has been investigated using two quantum mechanics method: the modified neglect of diatomic overlap (MNDO), a semi-empirical method, and the density functional theory (DFT)/B3LYP hybrid density functional method with the 6-311G (d, p) basis set in the ground state for gas phase. The optimum geometries have been obtained through the execution of computations and electrostatic potential. The obtained analytical and calculated results were then used to understand the activity of the studied EOs in further medical applications.

Reducing Training Data Needs with Minimal Multilevel Machine Learning (M3L)

Abstract For many machine learning applications in science, data acquisition, not training, is the bottleneck even when avoiding experiments and relying on computation and simulation. 
Correspondingly, and in order to reduce cost and carbon footprint, training data efficiency is key. 
We introduce minimal multilevel machine learning (M3L) which 
optimizes training data set sizes using a loss function at multiple levels of reference data in order to minimize a combination of prediction error with overall training data acquisition costs (as measured by computational wall-times).
Numerical evidence has been obtained for calculated atomization energies and electron affinities of thousands of organic molecules at various levels of theory including HF, MP2, DLPNO-CCSD(T), DFHFCABS, PNOMP2F12, and PNOCCSD(T)F12, and treating them with 
basis sets TZ, cc-pVTZ, and AVTZ-F12.
Our M3L benchmarks for reaching chemical accuracy in distinct chemical compound sub-spaces 
indicate substantial computational cost reductions by factors of 
$\sim$ 1.01, 1.1, 3.8, 13.8, and 25.8 when compared to heuristic sub-optimal multilevel machine learning (M2L) for the data sets QM7b, QM9$^\mathrm{LCCSD(T)}$, EGP, QM9$^\mathrm{CCSD(T)}_\mathrm{AE}$, and QM9$^\mathrm{CCSD(T)}_\mathrm{EA}$, respectively.
Furthermore, we use M2L to investigate the performance for 76 density functionals when used within multilevel learning and building on the following levels drawn from the hierarchy of Jacobs Ladder:~LDA, GGA, mGGA, and hybrid functionals.
Within M2L and the molecules considered, 
mGGAs do not provide any noticeable advantage over GGAs. 
Among the functionals considered and in combination with LDA, the three on average top performing GGA and Hybrid levels for atomization energies on QM9 using M3L correspond respectively to PW91, KT2, B97D, and $\tau$-HCTH, B3LYP$\ast$(VWN5), and TPSSH.

Orbital ordering patterns in KBF (B = Sc, Ti, Fe, Co) perovskites.

The orbital ordering (OO) resulting from the partial occupancy of the subshell of the transition metals in KBF (B = Sc, Ti, Ffe, Co) perovskites, and the many possible patterns arising from the coupling between the B sites, have been investigated at the quantum mechanical level ( Gaussian type basis set, B3LYP hybrid functional) in a 40 atoms supercell. The numerous patterns are distributed into 162 classes of equivalent configurations. For each fluoroperovskite, one representative per class has been calculated. The four compounds behave similarly: an identical dependence of the energy and volume (or cell parameters) on the OO pattern; the spanned energy interval is small (1 to 2 mE per formula unit), suggesting that most of the configurations are occupied at room and even at low temperature. A linear model, taking into account the relative orbital order in contiguous sites, reproduces the energy order in the full set for each compound, suggesting that it could be used for studying OO in larger supercells.

Computational assessment of the use of graphene-based nanosheets as PtII chemotherapeutics delivery systems.

Graphene is the newest form of elemental carbon and it is becoming rapidly a potential candidate in the framework of nano-bio research. Many reports confirm the successful use of graphene-based materials as carriers of anticancer drugs having relatively high loading capacities compared with other nanocarriers. Here, the outcomes of a systematic study of the adsorption behavior of FDA approved PtII drugs cisplatin, oxaliplatin, and carboplatin on surface models of pristine, holey, and nitrogen-doped holey graphene are reported. DFT investigations in water solvent have been carried out considering several initial orientations of the drugs with respect to the surfaces. Adsorption free energies, calculated including basis set superposition error (BSSE) corrections, result to be significantly negative for many of the drug@carrier adducts indicating that tested layers could be used as potential carriers for the delivery of anticancer PtII drugs. The reduced density gradient (RDG) analysis allows to show that many kinds of non-covalent interactions, including canonical H-bond, are responsible for the stabilization of the formed adducts.

Hats and titles: Maya courtier dress and hierarchy in the late Classic Maya court

Abstract The Maya used dress to help them structure social interaction. Taking a behavioral chain and practice approach, I define dress elements of male courtiers and how they were combined into outfits during the daily practices of dressing and attending court. I identify two groups of headgear, Standard and Special, among courtiers on vases showing historical interaction among humans. Each vase is considered commemorative and must communicate to an audience. I identified six Standard hat types that were widespread in the Maya Lowlands. The distribution implies a basic set of recognizable roles that provided the political-religious structure of the typical Maya court, perhaps as early as the Late Preclassic period. Four of the hat types are connected to glyphic titles. Each titleholder's position in the vase's visual space implies a hierarchy of roles. The results support my hypothesis that dress does identify social roles in the Maya court.

A DFTB study on the electronic response of encapsulated DNA nucleobases onto chiral CNTs as a sequencer

Sequencing the DNA nucleobases is essential in the diagnosis and treatment of many diseases related to human genes. In this article, the encapsulation of DNA nucleobases with some of the important synthesized chiral (7, 6), (8, 6), and (10, 8) carbon nanotubes were investigated. The structures were modeled by applying density functional theory based on tight binding method (DFTB) by considering semi-empirical basis sets. Encapsulating DNA nucleobases on the inside of CNTs caused changes in the electronic properties of the selected chiral CNTs. The results confirmed that van der Waals (vdW) interactions, π-orbitals interactions, non-bonded electron pairs, and the presence of high electronegative atoms are the key factors for these changes. The result of electronic parameters showed that among the CNTs, CNT (8, 6) is a suitable choice in sequencing guanine (G) and cytosine (C) DNA nucleobases. However, they are not able to sequence adenine (A) and thymine (T). According to the band gap energy engineering approach and absorption energy, the presence of G and C DNA nucleobases decreased the band gap energy of CNTs. Hence selected CNTs suggested as biosensor substrates for sequencing G and C DNA nucleobases.

A Theoretical Benchmark of the Geometric and Optical Properties for 3d Transition Metal Nanoclusters via Density Functional Theory.

Understanding structure-property relationships in atomically precise metal nanoclusters is vital in finding selective and tunable catalysts. In this study, density functional theory (DFT) was used to benchmark seven exchange correlation functionals at different basis sets for 17 atomically precise nanoclusters against experimentally determined geometries, band gaps, and optical gaps. The set contains both monometallic and bimetallic clusters that possess at least two types of 3d transition metals (specifically, Cu, Ni, Fe, or Co). The benchmark highlights that PBE0 is a good functional to use regardless of the basis set, and Minnesota functionals do well with respect to specific metals. Further, while long-range corrected functionals overestimate band and optical gaps, they model absorption features better than the other considered functionals. The study additionally looks at the photoinduced hydrogen evolution reaction (HER) and the CO2 reduction mechanism on nanoclusters reported from the literature.

Screening Stability, Thermochemistry, and Chemical Kinetics of 3-Hydroxybutanoic Acid as a Bifunctional Biodiesel Additive.

The thermo-kinetic aspects of 3-hydroxybutyric acid (3-HBA) pyrolysis in the gas phase were investigated using density functional theory (DFT), specifically the M06-2X theoretical level in conjunction with the cc-pVTZ basis set. The obtained data were compared with benchmark CBS-QB3 results. The degradation mechanism was divided into 16 pathways, comprising 6 complex fissions and 10 barrierless reactions. Energy profiles were calculated and supplemented with computations of rate coefficients and branching ratios over the temperature range of 600-1700 K at a pressure of 1 bar using transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) methods. Thermodynamics results indicated the presence of six stable conformers within a 4 kcal mol-1 energy range. The estimated chemical kinetics results suggested that TST and RRKM approaches are comparable, providing confidence in our calculations. The branching ratio analysis reveals that the dehydration reaction pathway leading to the formation of H2O and CH3CH═CHCO2H dominates entirely at T ≤ 650 K. At these temperatures, there is a minor contribution from the simple homolytic bond fission reaction, yielding related radicals [CH3•CHOH + •CH2CO2H]. However, at T ≥ 700 K, this reaction becomes the primary decomposition route. At T = 1700 K, there is a minor involvement of a reaction pathway resulting in the formation of CH3CH(OH)•CH2 + •CHO(OH) with an approximate contribution of 16%, and a reaction leading to [•CH3 + •CH2OHCH2CO2H] with around 9%.

Toward Real Chemical Accuracy on Current Quantum Hardware Through the Transcorrelated Method.

Quantum computing is emerging as a new computational paradigm with the potential to transform several research fields including quantum chemistry. However, current hardware limitations (including limited coherence times, gate infidelities, and connectivity) hamper the implementation of most quantum algorithms and call for more noise-resilient solutions. We propose an explicitly correlated Ansatz based on the transcorrelated (TC) approach to target these major roadblocks directly. This method transfers, without any approximation, correlations from the wave function directly into the Hamiltonian, thus reducing the resources needed to achieve accurate results with noisy quantum devices. We show that the TC approach allows for shallower circuits and improves the convergence toward the complete basis set limit, providing energies within chemical accuracy to experiment with smaller basis sets and, thus, fewer qubits. We demonstrate our method by computing bond lengths, dissociation energies, and vibrational frequencies close to experimental results for the hydrogen dimer and lithium hydride using two and four qubits, respectively. To demonstrate our approach's current and near-term potential, we perform hardware experiments, where our results confirm that the TC method paves the way toward accurate quantum chemistry calculations already on today's quantum hardware.

Tuning the potentials of aluminum phosphide nanotube photocatalyst for wastewater treatment through band gap engineering: a DFT study

Abstract The photocatalytic properties of semiconductor materials, which are controllable through the design of the bandgap structure, make them a promising catalyst for wastewater treatment. This work investigated the photocatalytic properties of single-walled aluminum phosphide nanotube (SWAlPNT) doped with different concentrations of boron (B) atoms for wastewater treatment. Analysis of the structural, electronic and optical properties of the SWAlPNT photocatalyst was performed using the density functional theory approach in terms of plane wave basis set and pseudopotential. The SWAlPNT was found to be stable to B doping with 3.6% and 7.1% concentrations. Cohesive energy decreases with an increase in concentration of dopant which results in efficient thermal stability. An indirect band gap value of 1.4 eV was obtained with B-doped SWAlPNT with 3.6% concentration which agreed with band gaps of other photocatalysts used for wastewater purification. Analysis using optical absorption spectra revealed that 3.6% B-doped system absorbs visible light while 7.1% doped system absorbs both visible and ultraviolet light. This study found both 3.6% and 7.1% B-doped SWAlPNT as suitable photocatalysts for wastewater treatment under solar irradiation, while the 3.6% B-doped system shows relatively better performance for wastewater treatment.

Theoretical spectroscopic electronic elucidation with polar and non-polar solvents (IEFPCM model), molecular docking and molecular dynamic studies on bendiocarb -antiallergic drug agent

The potential antiallergic compound bendiocarb was studied theoretically by polar and non-polar (six) solvents (IEFPCM model) by quantum chemical DFT calculations. Rotational potential barriers were estimated for water, acetone, THF, chloroform, benzene, and toluene are 12.62, 12.45, 12.55, 12.69, 12.74 and 12.57 kJ/mol. Analysis was done on the variations in geometries brought about by the electronegative atom’s replacement as well as the intramolecular interactions caused by the benzodioxol ring. NBO analysis as well as geometrical equilibrium have been performed using DFT employing the B3LYP technique with the 6-311G++(d, p) basis set. In vibrational analysis, CH stretching of bendiocarb was theoretically estimated within 3207–3181 cm−1 (gas), 3207–3184 cm−1 (acetone and water), 3207–3182 cm−1 (benzene and toluene), and 3207–3183 cm−1 (chloroform and THF) due to CN vibrations is challenging because of the overlapping and appearance of multiple bands in similar regions. Energy gaps for Bendiocarb in different solvents for water (5.719 eV), acetone (5.716 eV), THF (5.722 eV), chloroform (5.724 eV), benzene (5.731 eV), toluene (5.730 eV), and gas phase (5.746 eV). Lipinski’s rule of five was exploited to guide research on drug similarity and oral action. Using docking simulation against the antiallergic protein, a binding energy of −5.22 kcal/mol, 4P5M has been examined. The protein 4P5M exhibits variations between 0.12 and 0.155 nm for RMSD in molecular dynamic simulation. One can infer information about the pharmacokinetic features of the target molecule from its drug similarity, absorption, distribution, metabolism, excretion, and toxicity properties.

Discovery of a New Polymorph of 5-Methoxy-1H-Indole-2-Carboxylic Acid: Characterization by X-ray Diffraction, Infrared Spectroscopy, and DFT Calculations

This study presents a new 5-methoxy-1H-indole-2-carboxylic acid (MI2CA) polymorph investigated by single-crystal X-ray diffraction, infrared spectroscopy, and density functional theory (ωB97X-D) calculations employing two basis sets (6-31++G(d,p) and aug-cc-pVTZ). The compound crystallizes in the monoclinic system, space group P21/c (a = 4.0305(2) Å, b = 13.0346(6) Å, c = 17.2042(9) Å, β = 91.871(5)°, Z = 4). In the crystalline structure, the formation of cyclic dimers via double hydrogen bonds O−H⋯O between MI2CA molecules was observed. Interactions between the NH groups of the indole rings and the adjacent methoxy groups, as well as C–H⋯O contacts, significantly influence the spatial arrangement of molecules. The results from DFT calculations, including dimeric and trimeric structures, agree well with the experimental structural and spectroscopic data. Analysis of the infrared spectra confirms the conclusions drawn from X-ray diffraction studies and reveals differences between the IR spectra of the newly obtained polymorph and that reported earlier in the literature. This comprehensive study sheds some light on the MI2CA polymorphism and is important for a potential pharmacological applications of this compound.

Synthesis, Structural Characterization of Substituted Phenoxyimine Based Ti(IV) Complexes for Ring Opening Polymerization and DFT Studies

AbstractA series of 4 new titanium complexes bearing phenoxyimine ligands that differ in their steric and electronic properties have been synthesized and investigated for the polymerization of ethylene and rac‐lactide. X‐ray crystal structures of these catalysts reveal compounds 1–3 exhibit distorted octahedral geometry while complex 4 shows distorted trigonal bipyramidal. The substituents on the phenoxyimine framework have a profound influence on the catalytic activities of these compounds in the polymerization reactions. All four complexes afforded polylactide with a heterotactic bias in ring opening polymerization of rac‐lactide. In addition to this, density functional theory calculations using (B3LYP) with the 6‐311++G (d, p) basis set and no constraints were used while doing geometry optimizations and compared with experimental results. Hirshfeld surface analysis, MEP and Mulliken charge also reported an unexpected relationship between the nitrogen, oxygen on the ligands, titanium isopropoxide, and good relation between the experimental findings.

Ab initio dispersion potentials based on physics-based functional forms with machine learning.

In this study, we introduce SAPT10K, a comprehensive dataset comprising 9982 noncovalent interaction energies and their binding energy components (electrostatics, exchange, induction, and dispersion) for diverse intermolecular complexes of 944 unique dimers. These complexes cover significant portions of the intermolecular potential energy surface and were computed using higher-order symmetry-adapted perturbation theory, SAPT2+(3)(CCD), with a large aug-cc-pVTZ basis set. The dispersion energy values in SAPT10K serve as crucial inputs for refining the abinitio dispersion potentials based on Grimme's D3 and many-body dispersion (MBD) models. Additionally, Δ machine learning (ML) models based on newly developed intermolecular features, which are derived from intermolecular histograms of distances for element/substructure pairs to simultaneously account for local environments as well as long-range correlations, are also developed to address deficiencies of the D3/MBD models, including the inflexibility of their functional forms, the absence of MBD contributions in D3, and the standard Hirshfeld partitioning scheme used in MBD. The developed dispersion models can be applied to complexes involving a wide range of elements and charged monomers, surpassing other popular ML models, which are limited to systems with only neutral monomers and specific elements. The efficient D3-ML model, with Cartesian coordinates as the sole input, demonstrates promising results on a testing set comprising 6714 dimers, outperforming another popular ML model, component-based machine-learned intermolecular force field (CLIFF), by 1.5 times. These refined D3/MBD-ML models have the capability to replace the time-consuming dispersion components in symmetry-adapted perturbation theory-based calculations and can promptly illustrate the dispersion contribution in noncovalent complexes for supramolecular assembly and chemical reactions.

Early Stage In Vitro Bioprofiling of Potential Low-Molecular-Weight Organoboron Compounds for Boron Neutron Capture Therapy (BNCT)—Proposal for a Guide

Given the renewed interest in boron neutron capture therapy (BNCT) and the intensified search for improved boron carriers, as well as the difficulties of coherently comparing the carriers described so far, it seems necessary to define a basic set of assays and standardized methods to be used in the early stages of boron carrier development in vitro. The selection of assays and corresponding methods is based on the practical experience of the authors and is certainly not exhaustive, but open to discussion. The proposed tests/characteristics: Solubility, lipophilicity, stability, cytotoxicity, and cellular uptake apply to both low molecular weight (up to 500 Da) and high molecular weight (5000 Da and more) boron carriers. However, the specific methods have been selected primarily for low molecular weight boron carriers; in the case of high molecular weight compounds, some of the methods may need to be adapted.

Structural and Functional Characterization of Medicinal Plants as Selective Antibodies towards Therapy of COVID-19 Symptoms

Considering the COVID-19 pandemic, this research aims to investigate some herbs as probable therapies for this disease. Achillea millefolium (Yarrow), Alkanet, Rumex patientia (Patience dock), Dill, Tarragon, and sweet fennel, including some principal chemical compounds of achillin, alkannin, cuminaldehyde, dillapiole, estragole, and fenchone have been selected. The possible roles of these medicinal plants in COVID-19 treatment have been investigated through quantum sensing methods. The formation of hydrogen bonding between the principal substances selected in anti-COVID natural drugs and Tyr-Met-His (the database amino acids fragment), as the active area of the COVID protein, has been evaluated. The physical and chemical attributes of nuclear magnetic resonance, vibrational frequency, the highest occupied molecular orbital energy and the lowest unoccupied molecular orbital energy, partial charges, and spin density have been investigated using the DFT/TD-DFT method and 6-311+G (2d,p) basis set by the Gaussian 16 revision C.01 program toward the industry of drug design. This research has exhibited that there is relative agreement among the results that these medicinal plants could be efficient against COVID-19 symptoms.

Electronic structure and optical spectral analysis of the MnO42- anion with consideration of site and Jahn-Teller distortion.

The ground state of 3d1 MnO42- was studied by density functional theory (DFT) and complete active space self-consistent field (CASSCF) methods in terms of a variety of molecular point group structures to ascertain the site and Jahn-Teller (JT) distortion effect. Modeling results from UB3LYP/6-31+G(d) calculations with natural bond orbital analysis show the four Mn-O bonds are coordinate covalent. The one-electron matrix elements from CASSCF(AILFT) (abinitio ligand field theory) with a second order perturbation treatment were used to calculate the parameters of the angular overlap model. These allowed the calculation of JT stabilization energies and first and second order JT coupling constants for MnO42- with C2v and D2d symmetry. Absorption spectra and excited state transition energies were calculated assuming the lattice distorted geometry was C2v with time-dependent DFT (TDDFT) using the unrestricted coulomb-attenuating UCAM-B3LYP density functional and with the spin-adapted spin-flip DFT using the UBH&HLYP density functional, both with the AUG-CC-PVTZ basis set. The mean absolute deviation of the calculations from experimental excited states for the ligand field and ligand-to-metal charge transfer (LMCT) bands was better than 0.1eV. Several new assignments for LMCT excited states were made on the basis of the TDDFT excitation results.