Structure Density Functional Theory Research Articles

Synthesis, spectroscopic analysis (FT-IR, FT-Raman, UV, NMR), non-covalent interactions (RDG, IGM) and dynamic simulation on Bis(8‑hydroxy quinoline) salicylate salicylic acid

Using spectrum techniques and density functional theory (DFT) reckonings, structural, vibrational and electrical characteristics of Bis(8‑hydroxy quinoline) salicylate salicylic acid (8HQSA) were determined. Characterizing the chemical under inquiry involved employing FT-IR, FT-Raman, UV–vis spectral studies and single crystal X-ray diffraction (SCXRD). For the characterization, the B3LYP approach inside the structure of DFT was employed, with a 6–311++G(d,p) basis set. The structural study shows that the stability of 8HQSA crystalline structure arising from N–H⋯O, C–O⋯H and O–H⋯O hydrogen bonding interactions. The 1H and 13C NMR chemical shifts were calculated using Gauge Independent Atomic Orbital (GIAO) technical. Vibrational frequencies and molecular geometry were computed and likened with experimental data. Here, non-covalent interactions were deeply analyzed in terms of topological parameters (AIM), electron localization function (ELF), localized orbital locator (LOL), Hirshfeld surface and reduced density gradient (RDG) method. Weak interactions such as H-bonds, van der Waals and steric effect in 8HQSA were visualized and quantified by the independent gradient density (IGM) based on the trimolecular density. The hyper-conjugative and the delocalization of charge in 8HQSA have been elucidated by natural bonding orbital (NBO) while its chemical reactivity was studied and discussed by using molecular electrostatic potential surface (MEP), frontier molecular orbital (FMOs), density of state (DOS) and partial density of state (PDOS). The positions of the molecule's nucleophilic and electrophilic groups were ascertained using Fukui analysis. To describe the size, structure, and reactive sites of the molecules, the molecular electrostatic potential and total electron density are calculated. With a band gap (2.58 eV), FMO study indicates that the material is both bioactive and stable. The ADMET factor and drug similarity are used to predict 8HQSA's pharmokinetic characteristics. Based on the findings, it can be concluded that the 8HQSA particle is optimally crystallised and recommended as a preventative measure against bacterial and fungal infections. The stability of the title compound has been investigated via molecular dynamics simulations. In-vitro antimicrobial activity results clearly reveal that in all the four strains, activity increases with increase in compound concentration and the inhibition of the strains also increases. From both molecular docking and In-vitro Antimicrobial Activity the title compound can be certified that it inhibits antimicrobial activity.

Ab initio electronic structure calculations based on numerical atomic orbitals: Basic fomalisms and recent progresses

AbstractThe numerical atomic orbital (NAO) basis sets offer a computationally efficient option for electronic structure calculations, as they require fewer basis functions compared with other types of basis sets. Moreover, their strict localization allows for easy combination with current linear scaling methods, enabling efficient calculation of large physical systems. In recent years, NAO bases have become increasingly popular in modern electronic structure codes. This article provides a review of the ab initio electronic structure calculations using NAO bases. We begin by introducing basic formalisms of the NAO‐based electronic structure method, including NAO base set generation, self‐consistent calculations, force, and stress calculations. We will then discuss some recent advances in the methods based on the NAO bases, such as real‐time dependent density functional theory (rt‐TDDFT), efficient implementation of hybrid functionals, and other advanced electronic structure methods. Finally, we introduce the ab initio tight‐binding model, which can be generated directly after the self‐consistent calculations. The model allows for efficient calculation of electronic structures, and the associated topological, and optical properties of the systems.This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Computational Materials Science

Some problems in density functional theory

Though calculations based on density functional theory (DFT) are used remarkably widely in chemistry, physics, materials science, and biomolecular research and though the modern form of DFT has been studied for almost 60 years, some mathematical problems remain. For context, we provide an outline of the basic structure of DFT, then pose several questions regarding both its time-independent and time-dependent forms. Progress on any of these would aid in development of better approximate functionals and in interpretation.

Computational insights into the rational design of organic electrode materials for metal ion batteries

AbstractMetal ion batteries (MIBs), represented by lithium ion batteries are important energy storage devices for storing renewable energy. Advanced development of MIBs depends on the exploration of efficient and sustainable electrode materials. Organic electrode materials (OEMs) with redox‐active moieties are low‐cost and eco‐friendly alternatives to conventional inorganic electrode materials for MIBs. Computational simulation plays an important role in understanding the energy storage mechanism of different active functional groups and boosting the discovery of new OEMs for high‐efficient MIBs. Here, we will review recent progress of OEMs and comprehensively survey factors that determine their electrochemical properties. Dependable computational methods to guide the design of OEMs are comprehensively discussed and machine learning is highlighted as an emerging method to reveal the underlying structure–performance relationship and facilitate screening of OEMs with high‐efficiency. Finally, we summarize the available molecular design strategies to effectively improve the redox activity and stability of OEMs, and discuss challenges and opportunities of theoretical calculations of OEMs for MIBs.This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Molecular Structures

Multiscale computations and artificial intelligent models of electrochemical performance in Li‐ion battery materials

AbstractLi‐ion battery (LIB) is widely used as one of renewable energy resources for powerful electronics and electric vehicles. The main challenge in developing next‐generation LIB is to further improve the energy density, rate capability, and cycling stability of electrode and electrolyte materials. With the rapid development of computational science, the material design has changed from the traditional trial‐and‐error approach to integrated database‐based computation. Multiscale computational methods and machine learning (ML) not only speed up the development of new materials, but also provide insight into the intrinsic relationship between the microscopic composition and macroscopic performance of materials. In this review, we revealed the correlation of electrochemical activity of LIB materials with the response of energy to variable parameters such as charge‐transfer number and Li‐ion diffusion coordinates. Based on the structure–property relationship, we reviewed multiscale calculation and ML methods for electrochemical properties in LIB materials. A comparison for various applied methods was outlined to provide a method‐selecting reference in LIB material design. It is expected that a deep combination of multiscale computations, experimental data, ML should be more powerful methods for discovering new LIB materials.This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Reaction Mechanisms and Catalysis

The Chemical Nature of Ti4O10-: Vibrational Predissociation Spectroscopy Combined with Global Structure Optimization.

The gas-phase infrared spectrum of Ti4O10- is studied in the spectral range from 400 cm-1 to 1250 cm-1 using cryogenic ion trap vibrational spectroscopy, in combination with density functional theory (DFT). The infrared photodissociation (IRPD) spectrum of D2-tagged Ti4O10- provides evidence for a structure of lower symmetry that contains a superoxo group (1121 cm-1) and two terminal Ti=O moieties. DFT combined with a genetic algorithm for global structure optimization predicts two isomers which feature a superoxo group: the Cs symmetric global minimum-energy structure and a similar isomer (C1) that is slightly higher in energy. Coupled cluster calculations confirm the relative stability. Comparison of the harmonic DFT spectra (different functionals) with the IRPD spectrum suggests that both of these isomers contribute. Earlier assignments to the adamantane-like C3v isomer with three terminal Ti-O• - groups in a quartet state are not confirmed. They were based on the infrared multiple photon photodissociation (IRMPD) spectrum of bare Ti4O10- and local DFT structure optimizations.

Locating Hydrides in Ligand-Protected Copper Nanoclusters by Deep Learning.

Hydrides play an important role in constructing atomically precise metal nanoclusters and nanoparticles. They occupy both the interstitial sites inside the metal cores and the interfacial sites between the surface of the metal core and the ligand layer. Although the heavy-atom positions can be routinely determined by single-crystal X-ray diffraction, the challenge in growing a large and high-enough-quality single crystal for neutron diffraction and the limited availability of neutron sources have prevented researchers from precisely knowing the hydride locations. A recently developed deep-learning method showed great promise in accelerating the determination of hydride sites in metal nanostructures, but it is unclear if this approach, trained on clusters up to Cu32 in size, can be applied to recently discovered, much larger nanoclusters such as Cu81. Here we show that an improved deep-learning model based on convolutional neural networks is both accurate and robust. We apply it to two recently reported copper nanoclusters, [Cu32(PET)24H8Cl2]2- and [Cu81(PhS)46(tBuNH2)10H32]3+, whose hydride locations have not been determined by neutron but were proposed from density functional theory (DFT) calculations. In the former, our CNN model confirms the DFT structure; in the latter, our CNN model predicts a more stable structure with different hydride sites.

Dimensionality effects in high‐performance thermoelectric materials: Computational and experimental progress in energy harvesting applications

AbstractThermoelectric (TE) materials can be used in the conversion of heat to electricity and vice versa, which can enhance the efficiency of the fuel, in addition to supplying solid alternative energy in several applications in accumulating waste heat and, as a result, help to find new energy sources. Considering the current environment as well as the energy crisis, the TE modules are a need of the future. The present review focuses on the new strategies and approaches to achieve high‐performance TE materials including materials improvement, structures, and geometry improvement and their applications. Controlling the carrier concentration and the band structures of materials is an effective way to optimize the electrical transport properties, while engineered nanostructures and engineering defects can immensely decrease the thermal conductivity and significantly improved the power factor. The present review gives a better understanding of how the theory is affecting the TE field.This article is categorized under: Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Computational Materials Science

Bulk O2 formation and Mg displacement explain O-redox in Na0.67Mn0.72Mg0.28O2

Summary O-redox in compounds with Li on the transition-metal layers (TML) has recently been attributed to the formation of molecular O2 on charge, trapped in the lattice. Here, we show that a similar process occurs for P2-Na0.67[Mn0.72Mg0.28]O2, which contains Mg2+ on the TML. The molecular O2 is identified by high-resolution RIXS and quantified by magnetometry, showing that it equates to the charge passed. This O2 is trapped in voids that are formed by Mg2+ out-of-plane displacement and Mn4+ in-plane disordering and is then reduced on discharge associated with a large voltage hysteresis. In contrast to compounds containing Li+ in the TML, in which the honeycomb ordering and the high-voltage plateau are irreversibly lost after the first cycle, in P2-Na0.67[Mn0.72Mg0.28]O2, the plateau reappears partially on the second charge due to the partial reversibility of Mn in-plane and Mg out-of-plane migration and the local reformation of the honeycomb ordering.

Quasiparticle band structures of bulk and few-layer PdSe2 from first-principles GW calculations

We performed first-principles density functional theory (DFT) and GW calculations to investigate electronic structures of bulk and few-layer PdSe2. We obtained the quasiparticle band structure of bulk PdSe2, and the obtained energy gap agrees excellently with the reported experimental value. For monolayer and bilayer PdSe2, we obtained quasiparticle band structures with respect to the vacuum level. We analyzed DFT and GW band structures in detail, finding k-space positions of valence band maxima and conduction band minima, effective masses, the quasiparticle density of states, work functions, ionization potentials, electron affinities, and k-space shapes of electron and hole pockets. These results provide a foundation for development of basic studies and device applications.

Computational analysis of apatite-type compounds for band gap engineering: DFT calculations and structure prediction using tetrahedral substitution

Mineral apatite compounds have attracted significant interest due to their chemical stability and adjustable hexagonal structure, which makes them suitable as new photovoltaic functional materials. The band gap of natural apatite is ~ 5.45 eV, and such a large value limits their applications in the field of catalysis and energy devices. In this research, we designed a method to narrow the band gap via the tetrahedral substitution effect in apatite-based compounds. The density functional theory (DFT) and experimental investigation of the electronic and optical properties revealed that the continuous incorporation of [MO4]4– tetrahedrons (M = Si, Ge, Sn, and Mn) into the crystal lattice can significantly reduce the band gap. In particular, this phenomenon was observed when the [MnO4]4– tetrahedron replaces the [PO4]4– tetrahedron because of the formation of a Mn 3d-derived conduction band minimum (CBM) and interacts with other elements, leading to band broadening and obvious reduction of the band gap. This approach allowed us to propose a novel scheme in the band gap engineering of apatite-based compounds toward an entire spectral range modification.

Computational strategies to address the catalytic activity of nanoclusters

AbstractMetal nanoclusters have been emerged as imperative elements of heterogenous catalysis. Remarkably different properties from the bulk at the atomic level asserts construction of unique principles for understanding nanocluster catalysis. Computational studies abided by delicate theoretical framework are versatile tools for unveiling the structural, energetic, and mechanistic aspects of nanocluster‐based catalysis. Unlike other systems, nanoclusters feature properties derived from the unique surface structure, size dependence, and dynamics insisting fine‐tuning of computational approaches for accurate prediction of catalytic properties. Finding a balance between realistic simulation and computational affordability is of pressing priority. We highlight the urgency of computational models and practices to be updated by learning from the recent developments in this field. Focus is given to less explored factors governing the catalytic potential of nanoclusters.This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Reaction Mechanisms and Catalysis

Band engineering of non-hexagonal 2D tetragonal-silicene sheet and nanoribbons: A theoretical approach

We report combined first-principle and tight-binding (TB) calculation to investigate the mechanical and electronic properties of non-hexagonal two-dimensional (2D) tetragonal-silicene (TS) sheet and nanoribbons (NRs). The results obtained by the TB method are consistent with the density functional theory (DFT) results. The elastic constants of the TS sheet are comparable to silicene. The existence of two Dirac cones is observed at different k→ points in the irreducible Brillouin Zone. A spin-orbit bandgap larger than silicene is observed in TS. The criteria for the stability and robustness of the Dirac Cones on the TB parameters are extensively investigated. Both the Dirac points are robust and stable under a wide range of hopping parameters. The degeneracy of the Dirac cones can be removed by introducing asymmetry in the on-site energy. Comparing the DFT and TB band structures, the values of the TB hopping parameters are estimated. The electronic properties of the TSNRs show a strong dependence on the width and the edge states. The symmetric armchair TSNRs show a width dependent multiple Dirac cones in the Brillouin zone. The number of Dirac cones of the NR is found to be dependent on the TB hopping parameters as well. On the other hand, asymmetric armchair TSNRs are semiconducting. The tuning of the bandgap for asymmetric armchair TSNRs by modulating the TB hopping parameters is also explored. Zigzag TSNR behaves as a degenerate semiconductor with the presence of Dirac cones just below and above EF. We subsequently expect that these theoretical findings will give a better comprehension of Dirac materials and their NRs with its potential application in nano-electronics.

Adsorption of U(VI) on Stoichiometric and Oxidised Mackinawite: a DFT Study.

Naturally occurring minerals, such as the iron sulfide mackinawite, play a key role in the remediation of uranium from groundwater systems. Here, density functional theory (DFT) is used to investigate the interaction of uranium with the most stable surface of stoichiometric mackinawite, {001}-S. The high reactivity of the mineral toward oxygen may affect its ability to sequester uranium; therefore, two models of oxidized mackinawite are also used to study the effect of surface oxidation on adsorption. Weak adsorption of mononuclear uranyl(VI) complexes is found on stoichiometric mackinawite; however, equivalent adsorption modes on the oxidized mackinawite models generally exhibit stronger adsorption. Some of the most energetically stable DFT structures are found to match well with experimental extended X-ray absorption fine structure (EXAFS) data. The implications for the proposed use of mackinawite as a scavenger material for uranium in groundwater systems are discussed.

Theoretical investigation of para amino‐dichloro chalcone isomers, part I: A DFT structure—stability study

AbstractChalcones are versatile compounds with various biological activities and nonlinear optical applications. This study investigated the trans and cis isomers of 3‐(x,y‐dichlorophenyl)‐1‐(4′‐NH2‐phenyl)‐2‐propen‐1‐one, where (x) and (y) represent the positions of the two chlorine atoms [(2,3), (2,4), (2,5), (2,6), (3,4) and (3,5)] and their cyclic chromene isomers. The B3LYP density functional theory (DFT) method was used, with a 6‐311G (d,p) basis set. Calculations revealed that trans chalcones prefer s‐cis conformations. The syn conformation, in which chlorine atoms at carbon (2) or (3) is parallel to the carbonyl group, was more stable than the anti‐syn in trans chalcones. However, in cis chalcones, the opposite result was obtained. In contrast, (3,4) chalcones behaved in the opposite manner, for both trans and cis isomers. This order of conformation stability did not change when dispersion correction (DC) was incorporated in the calculations. Geometry optimisation with DC revealed that the trans (3,5) chalcone is the most stable, and the cis (2,3) chalcone is the least stable isomer in both chalcone series. However, (2,6) chromene was the most stable in chromene series isomers and the (3,4) chromene as the least stable. Calculated heat of hydrogenations for cis and trans isomers revealed that trans and cis (3,4) chalcones are the most stable in each series. However, trans and cis (2,6) chalcones are the least stable in each series. The stability of the three isomers, with and without DC, was determined as the following order: trans > cis > chromene.

Efficient removal of perfluorooctane sulphonate by nanofiltration: Insights into the effect and mechanism of coexisting inorganic ions and humic acid

The removal of perfluorooctane sulphonate (PFOS) with coexisting substances is very important. Inorganic ions and humic acid (HA) commonly coexist and may influence PFOS removal performance. However, there is little information on the capacity for systematic PFOS removal in the presence of inorganic ions and HA during nanofiltration (NF) process. In this paper, the impact of the coexistence of anions, cations, and HA on PFOS removal were investigated by NF. More specifically, the effect and interaction of anions, cations, and HA on PFOS removal performance and mechanism were examined. The PFOS removal rejection increased from 92% to 99% when HA was present together with both cations and anions. The higher the valence of the inorganic ion was, the greater the PFOS rejection was. The sieving effect was dominant in the improvement of PFOS removal by the presence of cations. The electrostatic repulsion played an important role in the improvement of PFOS removal by the presence of anions. Furthermore, density functional theory (DFT) was applied to calculate the interaction between PFOS molecules, cations, and HA. Corresponding DFT structures and thermodynamics parameters were obtained. It showed that the Ca2+ ions could more easily bridge two PFOS than one PFOS, HA could more easily coordinate with both Ca2+ and PFOS molecules. The increase of PFOS size after the coordination reaction results in the improvement of the sieving effect. Additionally, other analyses including X-ray photoelectron spectroscopy, atomic force microscopy, and the surface zeta potential also demonstrated the sieving effect mainly governed PFOS removal in coexistence with HA and cations. The electrostatic repulsion was dominant in PFOS separation performance in coexistence with HA and anions.

Generalized Kohn‐Sham energy decomposition analysis and its applications

AbstractEnergy decomposition analysis (EDA) methods bridge the gap between electronic structure calculations and conceptual interpretations of molecular interactions. The recently developed generalized Kohn‐Sham EDA (GKS‐EDA) can be used to examine various molecular interactions with restricted, restricted open‐shell or unrestricted Kohn‐Sham orbitals. It supports different density functional theory functionals, including LDA, GGA, hybrid, double hybrid, range‐separated, and dispersion‐corrected density functionals. GKS‐EDA can be also efficiently applied for intermolecular interactions in solutions and intramolecular interactions when used in combination with an implicit solvation model and appropriate fragmentation method. GKS‐EDA helps us not only to understand but also to predict the structures and properties of various interacting systems within a unified approach.This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Molecular and Statistical Mechanics > Molecular Interactions Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Molecular Structures

Information‐theoretic approach in density functional theory and its recent applications to chemical problems

AbstractUsing simple functionals of the electron density to appreciate and quantify molecular structure and chemical reactivity properties is a recent endeavor in density functional theory (DFT) toward the development of a new chemical reactivity theory. According to the first Hohenberg–Kohn theorem in DFT, the electron density alone should be able to determine any property in the ground state. Exchange and correlation energies are such properties, so are molecular structure and chemical reactivity, and hence they all should accurately be determined by electron density functionals. Quantities such as Shannon entropy, Fisher information, Ghosh–Berkowitz–Parr entropy, information gain, Onicescu information energy, etc., from the information‐theoretic approach are simple electron density functionals, whose analytical forms are exactly known. In this article, we demonstrate their usefulness and validity to quantify regioselectivity, stereoselectivity, and other structure and reactivity properties. We will outline the current understanding of its theoretical framework at first, and then highlight recent applications to chemical problems including isomeric and conformational stability, electrophilicity and nucleophilicity, strong covalent and weak noncovalent interactions, acidity and basicity, aromaticity and antiaromaticity, and numerous other properties. The effort of employing electron density functionals to quantify chemical concepts should open up a new door for us to ultimately develop a chemical reactivity theory using the DFT language.This article is characterized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Electronic Structure Theory > Density Functional Theory Structure and Mechanism > Molecular Structures Molecular and Statistical Mechanics > Molecular Interactions

Density-Functional Tight-Binding for Platinum Clusters and Bulk: Electronic vs Repulsive Parameters

ABSTRACTWe present a general purpose Pt-Pt density-functional tight-binding (DFTB) parameter for Pt clusters as well as bulk, using a genetic algorithm (GA) to automatize the parameterization effort. First we quantify the improvement possible by only optimizing the repulsive potential alone, and second we investigate the effect of improving the electronic parameter as well. During both parameterization efforts we employed our own training set and test sets, with one set containing ∼20,000 spin-polarized DFT structures. We analyze the performance of our two DFTB Pt-Pt parameter sets against density functional theory (DFT) as well as an earlier DFTB Pt-Pt parameters. Our study sheds light on the role of both repulsive and electronic parameters with regards to DFTB performance.

Efficient preparation of TiO2 nanoparticle models using interatomic potentials.

Computational modeling has proven to be extremely useful for understanding how the morphology, size, and structure of TiO2 nanoparticles (NPs) affect their electronic properties and their usage in targeted applications (e.g., photocatalysis). Density functional theory (DFT) based calculations of NPs (on the order of hundreds to thousands of atoms) are, however, computationally highly demanding. Herein, we show that interatomic potentials (IPs) can provide a highly computationally efficient means to prepare NP structures which are sufficiently accurate to significantly reduce the computational cost of subsequent DFT calculations. We first compare the direct DFT optimization of faceted NPs directly cut from the anatase bulk crystal with the same calculation where the NP is preoptimized using four different IPs. We then establish the subsequent computational time saving for the respective complete DFT optimizations. We show that IP-based preoptimizing can greatly speed up DFT convergence, with speed-ups of 3×-10× for single point DFT energy evaluations. Moreover, as IP preoptimized NP structures can be closer to those of DFT energy minima, further speed-ups of 2× for DFT structure optimizations can be achieved. Finally, taking NPs derived from anatase spherical cuts, we show that IP-based molecular dynamics annealing gives rise to significant structural reconstruction with an associated high energetic stabilization, as confirmed by DFT calculations. Although similar results can be achieved using DFT tight binding methods, IP-based methods are 3-4 orders of magnitude faster and thus provide a particularly highly computationally efficient route to the preparation and design of large and diverse NP sets.