Development Of Density Functional Theory Research Articles

The atomic-level structure and stability of interfaces of Pt nanoparticles in alumina: An experimental and computational evaluation

The atomic-level structure of interfaces between Pt and a transition form of Al2O3 were studied using a combination of electron microscopy and first principles calculations. A model system of Pt nanoprecipitates in Al2O3 were formed in sapphire wafers via high-energy ion implantation of Pt followed by thermal annealing at 1000 °C in air. The Pt nanoparticles took the form of tetrahedra and truncated tetrahedra primarily bound by {111}Pt facets. The high prevalence of these facets motivated the development of density functional theory (DFT) based models of (111)Pt interfaces with six different chemical terminations of (2¯01) θ-alumina. The atomic-level structure of the Pt/Al2O3 interfaces was characterized with aberration-corrected scanning transmission electron microscopy (STEM) and the experimental images were compared to STEM image simulations of the DFT models. The model interface with Pt bonded to oxygen-terminated θ-Al2O3, with the Pt located on top of the O and with an underlying layer of octahedral Al, provided the best match to the experimental images. This interfacial termination is also the most stable for the thermal annealing conditions used based on thermodynamic calculations of the interfacial energy as a function of temperature and oxygen partial pressure. This experimentally verified model provides a basis for improving models of Pt/γ-alumina interfaces.

Density Functional Theory Study of Interaction between Ibuprofen and Alginic Acid for Targeted Drug Delivery

Abstract:: The development of density functional theory has led to the consideration of computational chemistry in the design and development of interactions of new drugs in the gas phase with nanocarriers. In the present study, the interaction of ibuprofen with alginic acid (as a nanocarrier) has been investigated using density functional theory (DFT) in the gas phase (M06-2X/6-31+G*). A study on the effects of ibuprofen’s interaction with the compounds present in alginic acid has been conducted, focusing on the electronic properties, the chemical shift tensors, and the natural bond orbital. Based on the results of UV spectra, the compound 6-thioguanine has been found to be changed into an alginic acid/ibuprofen complex. The quantum theory of atoms in molecules showed the interaction of ibuprofen to be mainly driven by non-covalent bonds with alginic acid during complex formation. A hydrogen bond has been found to be formed between the oxygen atoms of alginic acid and ibuprofen's hydrogen atoms. Consequently, alginic acid has been used for delivering ibuprofen to diseased cells.

Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.

Recent advancements in the cathodic catalyst for the hydrogen evolution reaction in microbial electrolytic cells

The microbial electrochemical technology is a foremost viable technology for hydrogen production from organic matter or wastewater catalyzed by electroactive microorganisms. Developing a high-efficient and low-cost cathode for hydrogen production is crucial for the practical applications of MEC. In the present article, cathode materials and catalysts for hydrogen evolution reaction (HER) in MECs are reviewed. There is an essential requirement of cost-effective HER catalysts for improving MEC performance and as the practical findings fell short of the ideal catalyst's expectations, the density functional theory (DFT) can give essential molecular knowledge and anticipate viable catalysts. Additionally, this article provides an overview of the development of density functional theory (DFT), as well as computer simulations for HER processes using DFT, and also computational designs and virtual screens of novel HER catalysts. The development of catalysts combined with DFT simulations offers significant advancements in the near future on the path to an ideal electrocatalyst in MEC.

Computational approach for predicting the adsorption properties and inhibition of some antiretroviral drugs on copper corrosion in HNO3

The use of computational chemistry as an effective means of designing eco-friendly organic corrosion inhibitors has been greatly enhanced by the development of Density Functional Theory (DFT). In this study, the inhibitory activity of four antiretroviral drugs, namely, lamivudine, emtricitabine, didanosine and stavudine, was analyzed by this theory. The quantum chemical parameters/descriptors calculated using DFT at B3LYP/6-31G(d) level were used to explain the mechanism of electron transfer between the inhibitors and the copper surface. The results showed that these compounds adsorb on copper surface. It is important to consider the effect of films formed by the adsorption products. In addition, the Fukui functions and the dual descriptor were used as indicators to locate the electrophilic and nucleophilic attack sites within each compound. Finally, the DFT has enabled to accurately predict the adsorption properties and the good inhibition performance of the molecules in the solution studied.

Density Functional Theory as a Data Science.

The development of density functional theory (DFT) functionals and physical corrections are reviewed focusing on the physical meanings and the semiempirical parameters from the viewpoint of data science. This review shows that DFT exchange-correlation functionals have been developed under many strict physical conditions with minimizing the number of the semiempirical parameters, except for some recent functionals. Major physical corrections for exchange-correlation function- als are also shown to have clear physical meanings independent of the functionals, though they inevitably require minimum semiempirical parameters dependent on the functionals combined. We, therefore, interpret that DFT functionals with physical corrections are the most sophisticated target functions that are physically legitimated, even from the viewpoint of data science.

Direct evaluation of the isotope effect within the framework of density functional theory for superconductors

Within recent developments of density functional theory, its numerical implementation and of the superconducting density functional theory is nowadays possible to predict the superconducting critical temperature, , with sufficient accuracy to anticipate the experimental verification. In this paper we present an analytical derivation of the isotope coefficient within the superconducting density functional theory. We calculate the partial derivative of with respect to atomic masses. We verified the final expression by means of numerical calculations of isotope coefficient in monatomic superconductors (Pb) as well as polyatomic superconductors (CaC6). The results confirm the validity of the analytical derivation with respect to the finite difference methods, with considerable improvement in terms of computational time and calculation accuracy. Once the critical temperature is calculated (at the reference mass(es)), various isotope exponents can be simply obtained in the same run. In addition, we provide the expression of interesting quantities like partial derivatives of the deformation potential, phonon frequencies and eigenvectors with respect to atomic masses, which can be useful for other derivations and applications.

First-principles study of organic molecule for corrosion inhibition

The widespread use of steel in various industries, especially in the transportation of hydrocarbons and gas, has recently gained a potential interest to explore eco-friendly solutions against corrosion. In fact, the highly aggressive environment generates considerable losses that affect global economy of countries that are mainly depending on the production and transport of energy. In the field of corrosion inhibitors, most common method so far available for protection against corrosion relies on synthetic one. These are unfortunately harmful to the environment as well to the human health, however they remain the most popular and the most effective due to their cost, and their ease of application. One of the most challenging issues in this area is the accurate understanding and measure of the degree of the passivation of corrosion inhibitors, which is complex and depend on many factors such as the nature of the metal, the fluid, the electronic structure of the inhibitor, the temperature, the exposure time, and so on. Recently, organic inhibitors have become increasingly attractive due to their competitive character as compared to the synthetic ones. With the use of advanced computational techniques enhanced by the development of density functional theory (DFT), it becomes possible to identify and design at the fundamental level, novel corrosion inhibitor molecules as complementary well established tool beside to the experimental techniques, which are often very expensive and time-consuming. In this work, we explore by mean of DFT, the anti-corrosion effect of the Lawsone molecule (2-hydroxy-1,4-naphthoquinone) and some of its derivatives to clarify and understand the relationship at the fundamental level between the anti-corrosion properties and the structure of the molecule in contact with the iron.

Unravelling the Potential of Density Functional Theory through Integrated Computational Environments: Recent Applications of the Vienna Ab Initio Simulation Package in the MedeA® Software

The development of density functional theory and the tremendous increase of compute power in recent decades have created a framework for the incredible success of modern computational materials engineering (CME). CME has been widely adopted in the academic world and is now established as a standard tool for industrial applications. As theory and compute resources have developed, highly efficient computer codes to solve the basic equations have been implemented and successively integrated into comprehensive computational environments leading to unprecedented increases in productivity. The MedeA software of Materials Design combines a set of comprehensive productivity tools with leading computer codes such as the Vienna Ab initio Simulation Package (VASP), LAMMPS, GIBBS and the UNiversal CLuster Expansion code (UNCLE), provides interoperability at different length and time scales. In the present review, technological applications including microelectronic materials, Li-ion batteries, disordered systems, high-throughput applications and transition-metal oxides for electronics applications are described in the context of the development of CME and with reference to the MedeA environment.

Ab Initio Approach and Its Impact on Superconductivity

One of the main motivations for studying superconductivity is to search for high-temperature superconductors, especially room-temperature superconductors. During the long history of more than 100 years since the discovery of superconductivity, a number of high-temperature superconductors were found and several great breakthroughs were achieved. Recently, thanks to advances in computing power, progress in crystal structure prediction, and developments in density functional theory, computations have been carried out to predict the structures and an appearance of superconductivity of hydrides at high pressure. More exciting, it is been the first time when a simple, perfect cubic phase of H3S which become superconductor at Tc = 200 K under high pressure was successfully predicted by means of ab initio calculation, and then confirmed experimentally. This observation breaks the temperature record of cuprate with Tc = 164 K and further stimulates the studies of hydrides under pressure. Very recently, the high value of Tc = 286 K was theoretically predicted for LaH10 at 210 GPa and this prediction has been confirmed experimentally. These two successful examples demonstrate the importance of ab initio approach to superconductivity.

First-Principles Modeling in Heterogeneous Electrocatalysis

The last decade has witnessed tremendous progress in the development of computer simulation based on quantum mechanical description of the interactions between electrons and between electrons and atomic nuclei with electrode potentials taken into account–promoting the possibility to model electrocatalytic reactions. The cornerstone of this development was laid by the widely used computational hydrogen electrode method which involves a posteriori correction of standard constant charge first principles studies in solvent environment. The description of this technique and its contribution to our effort to understand electrocatalytic reactions on the active sites of metal-based nanoparticles are reviewed. The pathways and energetics of the relevant elementary reactions are presented. We also discussed a recent attempt in the literature to account for the inflow and outflow of electrons from the electrode as electrochemical reactions proceed, which has been greatly assisted by the development of density functional theory within the grand canonical framework. Going beyond the computational hydrogen electrode method by explicit incorporation of electrode potential within the calculations permits access to more detailed insights without requiring extra computational burden.

A tryst with density

WalterKohn transformed theoretical chemistry and solid state physics with his development of density functional theory, for which he was awarded the Nobel Prize. This article tries to explain, in simple terms, why this was an important advance in the field, and to describe precisely what it was that he (together with his collaborators Pierre Hohenberg and Lu Jeu Sham) achieved.

Implementation Strategies for Orbital-dependent Density Functionals

The development of density functional theory (DFT) has been focused primarily on two main pillars: (1) the pursuit of more accurate exchange-correlation (XC) density functionals; (2) the feasibility of computational implementation when dealing with many-body systems. In this context, this work is aimed on using one-dimensional quantum systems as theoretical laboratories to investigate the implementation of orbital functionals (OFs) of density. By definition, OFs are those which depend only implicitly on the density, via an explicit formulation in terms of Kohn-Sham orbitals. Typical examples are the XC functionals arising from the Perdew-Zunger self-interaction correction (PZSIC). Formally, via Kohn-Sham equations, the implementation of OFs must be performed by means of the optimized effective potential method (OEP), which is known by requiring an excessive computational effort even when dealing with few electrons systems. Here, we proceed a systematical investigation aiming to simplify or avoid the OEP procedure, taking as reference the implementation of the PZSIC correction applied to one-dimensional Hubbard chains.

ChemInform Abstract: Predicting Density Functional Theory Total Energies and Enthalpies of Formation of Metal—Nonmetal Compounds by Linear Regression

The availability of quantitatively accurate total energies $({E}_{\mathrm{tot}})$ of atoms, molecules, and solids, enabled by the development of density functional theory (DFT), has transformed solid state physics, quantum chemistry, and materials science by allowing direct calculations of measureable quantities, such as enthalpies of formation $(\mathrm{\ensuremath{\Delta}}{H}_{f})$. Still, the ability to compute ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ values does not, necessarily, provide insights into the physical mechanisms behind their magnitudes or chemical trends. Here, we examine a large set of calculated ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ values obtained from the DFT+$U$-based fitted elemental-phase reference energies (FERE) approach [V. Stevanovi\ifmmode \acute{c}\else \'{c}\fi{}, S. Lany, X. Zhang, and A. Zunger, Phys. Rev. B 85, 115104 (2012)] to probe relationships between the ${E}_{\mathrm{tot}}/\mathrm{\ensuremath{\Delta}}{H}_{f}$ of metal-nonmetal compounds in their ground-state crystal structures and properties describing the compound compositions and their elemental constituents. From a stepwise linear regression, we develop a linear model for ${E}_{\mathrm{tot}}$, and consequently $\mathrm{\ensuremath{\Delta}}{H}_{f}$, that reproduces calculated FERE values with a mean absolute error of \ensuremath{\sim}80 meV/atom. The most significant contributions to the model include calculated total energies of the constituent elements in their reference phases (e.g., metallic iron or gas phase ${\mathrm{O}}_{2}$), atomic ionization energies and electron affinities, Pauling electronegativity differences, and atomic electric polarizabilities. These contributions are discussed in the context of their connection to the underlying physics. We also demonstrate that our ${E}_{\mathrm{tot}}/\mathrm{\ensuremath{\Delta}}{H}_{f}$ model can be directly extended to predict the ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ of compounds outside the set used to develop the model.

Walter Kohn (1923–2016)

Walter Kohn, who died on April 19, 2016, once said “Physics isn’t what I do; it is what I am.” Indeed, Walter was a world-renowned physicist, winner of the 1960 Oliver E. Buckley Prize for his prediction of anomalies in the phonon spectrum in metals, the 1977 Davisson–Germer Prize with Nortan Lang for their studies of the inhomogeneous interacting electron gas at surfaces, and the 1991 Eugene Feenberg Medal for the development of density-functional theory. However, it was in Chemistry that Walter received the ultimate scientific recognition. The 1998 Nobel Prize in Chemistry was shared by Walter Kohn, “for his development of the density-functional theory,” and John A. Pople, “for his development of computational methods in quantum chemistry.” The Nobel Committee recognized Walter’s work in the 1960s with postdoctorates Pierre Hohenberg (Bell Labs) and Lu Sham (University of California, San Diego) in the development of the density-functional theory in which the properties of a many-electron system can be determined by using functionals of the spatially …

Computational Materials Engineering: Recent Applications of VASP in the MedeA® Software Environment

Electronic structure calculations have become a powerful foundation for computational materials engineering. Four major factors have enabled this unprecedented evolution, namely (i) the development of density functional theory (DFT), (ii) the creation of highly efficient computer programs to solve the Kohn-Sham equations, (iii) the integration of these programs into productivityoriented computational environments, and (iv) the phenomenal increase of computing power. In this context, we describe recent applications of the Vienna Ab-initio Simulation Package (VASP) within the MedeA ® computational environment, which provides interoperability with a comprehensive range of modeling and simulation tools. The focus is on technological applications including microelectronic materials, Li-ion batteries, high-performance ceramics, silicon carbide, and Zr alloys for nuclear power generation. A discussion of current trends including high-throughput calculations concludes this article.

Predicting density functional theory total energies and enthalpies of formation of metal-nonmetal compounds by linear regression

The availability of quantitatively accurate total energies $({E}_{\mathrm{tot}})$ of atoms, molecules, and solids, enabled by the development of density functional theory (DFT), has transformed solid state physics, quantum chemistry, and materials science by allowing direct calculations of measureable quantities, such as enthalpies of formation $(\mathrm{\ensuremath{\Delta}}{H}_{f})$. Still, the ability to compute ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ values does not, necessarily, provide insights into the physical mechanisms behind their magnitudes or chemical trends. Here, we examine a large set of calculated ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ values obtained from the DFT+$U$-based fitted elemental-phase reference energies (FERE) approach [V. Stevanovi\ifmmode \acute{c}\else \'{c}\fi{}, S. Lany, X. Zhang, and A. Zunger, Phys. Rev. B 85, 115104 (2012)] to probe relationships between the ${E}_{\mathrm{tot}}/\mathrm{\ensuremath{\Delta}}{H}_{f}$ of metal-nonmetal compounds in their ground-state crystal structures and properties describing the compound compositions and their elemental constituents. From a stepwise linear regression, we develop a linear model for ${E}_{\mathrm{tot}}$, and consequently $\mathrm{\ensuremath{\Delta}}{H}_{f}$, that reproduces calculated FERE values with a mean absolute error of \ensuremath{\sim}80 meV/atom. The most significant contributions to the model include calculated total energies of the constituent elements in their reference phases (e.g., metallic iron or gas phase ${\mathrm{O}}_{2}$), atomic ionization energies and electron affinities, Pauling electronegativity differences, and atomic electric polarizabilities. These contributions are discussed in the context of their connection to the underlying physics. We also demonstrate that our ${E}_{\mathrm{tot}}/\mathrm{\ensuremath{\Delta}}{H}_{f}$ model can be directly extended to predict the ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ of compounds outside the set used to develop the model.

A novel method for the calculation of bond stretching force constants of diatomic molecules

Chemical hardness is one of the chemical reactivity descriptors of chemical species and this concept has widely benefited from the development of Density Functional Theory (DFT). In the present report, chemical hardness values for approximately fifty diatomic molecules have been calculated using a new molecular hardness (ηM) equation derived by us in recent times. Then, correlation between force constant (k) and chemical hardness for the above mentioned diatomic molecules that situate hydrides, halides, oxides and sulfides among them has been investigated. Consequently, a relation that can be presented by a simple equation between chemical hardness with bond stretching force constants has been found.

Catalyst screening: Refinement of the origin of the volcano curve and its implication in heterogeneous catalysis

Understanding the overall catalytic activity trend for rational catalyst design is one of the core goals in heterogeneous catalysis. In the past two decades, the development of density functional theory (DFT) and surface kinetics make it feasible to theoretically evaluate and predict the catalytic activity variation of catalysts within a descriptor-based framework. Thereinto, the concept of the volcano curve, which reveals the general activity trend, usually constitutes the basic foundation of catalyst screening. However, although it is a widely accepted concept in heterogeneous catalysis, its origin lacks a clear physical picture and definite interpretation. Herein, starting with a brief review of the development of the catalyst screening framework, we use a two-step kinetic model to refine and clarify the origin of the volcano curve with a full analytical analysis by integrating the surface kinetics and the results of first-principles calculations. It is mathematically demonstrated that the volcano curve is an essential property in catalysis, which results from the self-poisoning effect accompanying the catalytic adsorption process. Specifically, when adsorption is strong, it is the rapid decrease of surface free sites rather than the augmentation of energy barriers that inhibits the overall reaction rate and results in the volcano curve. Some interesting points and implications in assisting catalyst screening are also discussed based on the kinetic derivation. Moreover, recent applications of the volcano curve for catalyst design in two important photoelectrocatalytic processes (the hydrogen evolution reaction and dye-sensitized solar cells) are also briefly discussed.

Total energy equation leading to exchange-correlation functional

By solving the total energy equation, we obtain the formula of exchange-correlation functional for the first time. This functional is usually determined by fitting experimental data or the numerical results of models. In the uniform electron gas limit, our exchange-correlation functional can exactly reproduce the results of Perdew-Zunger parameterization from the jellium model. By making use of a particular solution, our exchange-correlation functional could take into account the case of non-uniform electron density, and its validity can be confirmed through comparisons of the band structure, equilibrium lattice constant, and bulk modulus of aluminum and silicon. The absence of mechanical prescriptions for the systematic improvement of exchange-correlation functional hinders further development of density-functional theory (DFT), and the formula of exchange-correlation functional given in this study might provide a new perspective to help DFT out of this awkward situation.