DFTB Calculations Research Articles

Hydantoin-D,L-valine: Synthesis, characterization, and non-covalent interaction analysis from crystallographic studies, DFTB calculations, and Hirshfeld surface analysis

The title compound, hydantoin-D,L-daline or (RS)-5-isopropyl-imidazolidine-2,4‑dione, a new amino acid hydantoin derivative with formula C6H10N2O2 has been synthesized and structurally characterized by FT-IR, NMR, and X-ray diffraction techniques. Spectroscopy results are consistent with the skeleton structure. The powder X-ray diffraction data confirms the phase purity of the crystalline sample. Single-crystal X-ray diffraction analysis indicated that the title compound crystallizes in the monoclinic space group P21/c (N°14), Z = 4, and unit cell parameters a = 5.493(3) Å, b = 23.53(2) Å, c = 6.254(3) Å, β= 115.09(4)°, V = 732.1(9) Å3. The molecular structure and crystal packing are stabilized by intermolecular N–H···O, C–H···O, and C–H···π hydrogen bonds forming an infinite two-dimensional network with chains described by the graph-set notation C(5), and centrosymmetric rings with graphs R22(8) and R44(16). The non-covalent interactions were analyzed employing DFTB calculations, which reproduce the main features of the stereochemistry and geometries exhibited by X-ray diffraction. Additionally, these intermolecular interactions were analyzed using Hirshfeld surfaces analysis and 2D fingerprint plots.

Highly efficient oxidative C–H/C–H cross coupling of xanthines over bimetallic Ni/Ag@titania: The key role of surface polymorphism and mechanism by surface-enhanced Raman scattering

A new effiecient protocol for the cross dehydrogenative coupling (CDC) of C8(sp2)-H/C(sp2)-H of xanthines and aromatic compounds over nanosized bimetallic Ni/Ag@titania catalyst is presented. The notable properties of Ni/Ag bimetallic nanoparticles (NPs) facilitate the 2-fold activation of classically inert C(sp2)-H bonds. Molecular level study for the catalyst efficiency was determined, by performing the model reaction between caffeine and vanillin, on different catalysts, synthesised by varying the loading of two component metals, on four polymorphic forms of titania, brookite, rutile, anatase and mesoporous. Among the 63 catalyst systems, 5:1 Ni/Ag@anatase showed excellent catalytic activity in dry DMSO with 88% product formation. Tert-butyl hydroperoxide (TBHP) and H2O2 were used as oxidant. The regioselectivity of the CDC reaction depends on the nature of peroxide used. Non-covalent surface π-stacking interaction occurring between peroxide modified titania (PMT) and aromatic ring(s) is the key for the observed regioselectivity. Catalysts were characterised by UV–Vis, FT-IR, powder XRD, XPS, SEM, TEM, etc. The catalytic system showed good operational stability, functional group tolerance, robustness and recyclability. We identified the intermediate(s) through real time monitoring of SERS and proposed the most plausible catalytic cycle as well. Further, a possible energy profile diagram involving the transition states was obtained computationally by DFTB calculations. Almost all the products were afforded in good to excellent yields. Thus, the present process constitutes one straightforward and clean approach to a class of much sought organic transformation.

Cavity Size Effects on the Adsorption of CO2 on Pillar[n]arene Structures: A Density Functional Theory Study

AbstractCarbon dioxide (CO2) is the main greenhouse gas that contributes to the global warming. Therefore, CO2 adsorption is very urgent in the fight to limit global warming below 1.5 degrees Celsius. In this report, the interaction between CO2 with different structures of pillar[n]arene (P[n]A) is studied by using DFTB and DFT calculations, in order to understand the effect of P[n]A (with n=4, 5, and 6) cavity sizes on CO2 adsorption. The P[n]A structures physisorb CO2 at three principally different positions called cavity‐in, top‐in, and top‐out. The adsorbed CO2‐cavity‐in at P[4]A has the highest binding energy. The adsorbed CO2 at the other positions has similar binding energies on P[4]A, P[5]A, and P[6]A, because hydrogen bonding plays a major role for the interaction at the hydroxyl group. The number of CO2 molecules that can be adsorbed at the cavity site depends on the cavity size of P[n]A. The bigger the cavity site, the larger the number of CO2 molecules that can be adsorbed before saturation is achieved. We also observed that the adsorbed CO2 molecules can interact with each other, leading to an increase of the binding energy and highlighting the promising CO2 capture capabilities of P[n]A structures.

Ab initio study: Investigating the adsorption behaviors of polarized greenhouse gas molecules on pillar[5]arenes

Supramolecular organic frameworks (SOFs) based on Pillar[5]arenes (P[5]A) have shown great potential in capturing and separating greenhouse gases. In this study, we investigate the adsorption behaviors of other environmentally harmful gas molecules, including NO, NH3, CO, and NO2 on pillar[5]arenes (P[5]A) using DFTB and DFT calculations. The P[5]A structures exhibit the capability to adsorb including NO, NH3, CO, and NO2 at both the cavity site and OH group, facilitated by π-π interactions and hydrogen bonding. CO exhibits the lowest binding energy among the studied gases, primarily due to its weak dipole moment. In contrast, the cavity-in positions for NO2 and NH3, characterized by high polarization, exhibit the highest adsorption energies. The adsorption energies at the top-out positions are relatively similar for all gases examined. These findings provide valuable insights for the targeted design and optimization of P[5]A, enabling its potential applications in effectively capturing toxic gases.

Sulfur doping concentration effect on the electronic and structural properties of ZnO nanoparticles: Insights from DFTB calculations

The structural and energetic features of sulfur - doped ZnO nanoparticles (NPs) were studied using DFTB approach. The cohesive energy reveals that lower sulfur concentration causes an increase in energetic stability. The sulfur doping concentration rate determines the most electronically stable structure. A reduction in the energy gap with increasing sulfur concentration was predicted from 4.71 eV (undoped ZnO NPs) to 0.68 eV (9S-doped ZnO NP), which represents a similar trend to experimental findings. The LUMO level considerably shifts to higher energies, while the HOMO-level down-shifts with increasing sulfur doping concentration. From ionization potential and electron affinity, the S-ZnO and 9S-ZnO NPs are the least reactive and high kinetic stability. The 9S-ZnO NP has the strongest electrophilic character, and thus, it is the most conductive structure. Finally, current research demonstrated that the sulfur doping concentration can alter the energetic properties of ZnO NP and thus provide its use in desired applications.

Toward an efficient f-in-core/f-in-valence switchable description for DFTB calculations of Ce 4f states in ceria.

A computational protocol is developed for efficient studies of partially reduced redox-active oxides using the self-consistent charge density functional tight-binding method. The protocol is demonstrated for ceria, which is a prototypical reducible oxide material. The underlying idea is to achieve a consistent (and harmonized) set of Slater-Koster (SK) tables with connected repulsive potentials that enable switching on and off the in-valence description of the Ce 4f states without serious loss of accuracy in structure and energetics. The implicit treatment of the Ce 4f states, with the use of f-in-core SK-tables, is found to lead to a significant decrease in computational time. More importantly, it allows for explicit control of the oxidation states of individual Ce atoms. This makes it possible to "freeze" the electronic configuration, thereby allowing the exploration of the energetics for various meta-stable configurations. We anticipate that the outlined strategy can help to shed light on the interplay between the size, shape, and redox activity for nanoceria and other related materials.

GAMaterial-A genetic-algorithm software for material design and discovery.

Genetic algorithms (GAs) are stochastic global search methods inspired by biological evolution. They have been used extensively in chemistry and materials science coupled with theoretical methods, ranging from force-fields to high-throughput first-principles methods. The methodology allows an accurate and automated structural determination for molecules, atomic clusters, nanoparticles, and solid surfaces, fundamental to understanding chemical processes in catalysis and environmental sciences, for instance. In this work, we propose a new genetic algorithm software, GAMaterial, implemented in Python3.x, that performs global searches to elucidate the structures of atomic clusters, doped clusters or materials and atomic clusters on surfaces. For all these applications, it is possible to accelerate the GA search by using machine learning (ML), the ML@GA method, to build subsequent populations. Results for ML@GA applied for the dopant distributions in atomic clusters are presented. The GAMaterial software was applied for the automatic structural search for the Ti6 O12 cluster, doping Al in Si11 (4Al@Si11 ) and Na10 supported on graphene (Na10 @graphene), where DFTB calculations were used to sample the complex search surfaces with reasonably low computational cost. Finally, the global search by GA of the Mo8 C4 cluster was considered, where DFT calculations were made with the deMon2k code, which is interfaced with GAMaterial.

Rapidly predicting Kohn–Sham total energy using data-centric AI

Predicting material properties by solving the Kohn-Sham (KS) equation, which is the basis of modern computational approaches to electronic structures, has provided significant improvements in materials sciences. Despite its contributions, both DFT and DFTB calculations are limited by the number of electrons and atoms that translate into increasingly longer run-times. In this work we introduce a novel, data-centric machine learning framework that is used to rapidly and accurately predicate the KS total energy of anatase {mathrm{TiO}}_2 nanoparticles (NPs) at different temperatures using only a small amount of theoretical data. The proposed framework that we call co-modeling eliminates the need for experimental data and is general enough to be used over any NPs to determine electronic structure and, consequently, more efficiently study physical and chemical properties. We include a web service to demonstrate the effectiveness of our approach.

Discrete Oligomers and Polymers of Chloride Monohydrate Can Form in Encapsulated Environments: Structures and Infrared Spectra of [Cl4 (H2 O)4 ]4- and {[Cl(H2 O)]- }∞.

A discrete tetrachloride tetrahydrate cluster, [Cl4 (H2 O)4 ]4- , was obtained with a partially-fluorinated triaminocyclopropenium cation, [C3 (N(CH2 CF3 )2 )(NEt2 )(NPr2 )]+ . The cluster consists of a [Cl2 (H2 O)2 ]2- square with each Cl- coordinated by another H2 O bridged to another Cl- . A 1D polymer of chloride monohydrate, {[Cl(H2 O)]- }∞ , was obtained with [C3 (N(CH2 CF3 )2 )2 (NBuMe)]+ . The tetrameric and polymeric structures were found to be computationally-unstable in the gas phase which indicates that an encapsulated environment is essential for their isolation. DFT and DFTB calculations were carried out on gas-phase [Cl4 (H2 O)4 ]4- to assist the infrared assignments. Anharmonically-corrected B3LYP transition frequencies were in close agreement with experiment, but DFTB models were only appropriate for qualitative interpretation. Solid-state DFTB calculations allowed the vibrational modes to be assigned. The results found are consistent with "discrete" chloride hydrates.

Front Cover: Metal‐ligand cooperative activation of HX (X=H, Br, OR) bond on Mn based pincer complexes (14/2021)

The spaceship on the cover picture depicts a pincer complex browsing a vast space of different functionalization groups. The spaceship carries the reactive manganese site, whose properties can be tuned by changing the functional groups on the specific “docking sites” of the carrier ligand. Herein we present an automated high-throughput computational study of how ligand functionalization affects the reactivity and catalytic behaviour of metal-ligand cooperative Mn(I) pincer complexes. The study included DFT and DFTB calculations to analyze the stability of different adducts relevant to (de)hydrogenation catalytic chemistry (https://doi.org/10.1002/zaac.202100078).

Atomic arrangements, bond energies, and charge distribution on Si(0 0 1) surfaces with the adsorption of a Ge dimer by DFTB calculations

The atomic arrangements and electrical properties of SiGe nanomaterials are of significance when used in novel nanoelectronic devices and optoelectronic devices. Atomic arrangements, bond energies, and charge distribution of a Ge dimer adsorbed on Si(001) surfaces with different initial heights and inclination angles are investigated by using the DFTB algorithm. Eight different stable adsorption modes of the Ge dimer on the Si slab surface are demonstrated. The variations of the structural and electrical properties of the eight modes are elucidated. Different initial conditions caused stable adsorption of Ge dimer on the surface or caused two single Ge atoms from the Ge dimer to fragment. The Ge dimer, with different inclination angles, is adsorbed on the top site, bridge site, or hollow site of the Si dimer on the surface. The bond length of the Ge dimer is stretched, and the two Ge atoms lose charges. The further the Ge atom is from the surface, the more charges it loses. The different adsorption sites of the Ge dimer affect the properties of the Si dimer on the surface. The top adsorption site mode exerts a greater influence on the bond length and bond energy of the Si dimer, while the bridge adsorption site mode exerts a greater influence on the electron distribution of the Si dimer. The properties of the Ge monoatomic adsorption are akin to the case of a Ge dimer being adsorbed on the bridge site. The different adsorption sites and inclination angles cause the EGap values of the systems to differ, and the effect of the inclination angle on different sites also differs. The Ge dimer and Ge monoatom not only have similar effects on the properties of the Si dimer, but also exert the similar effects on EGap, suggesting that changes in the Si surface are the main contributors to the change in EGap.

Reliability of semiempirical and DFTB methods for the global optimization of the structures of nanoclusters.

In this work, we explore the possibility of using computationally inexpensive electronic structure methods, such as semiempirical and DFTB calculations, for the search of the global minimum (GM) structure of chemical systems. The basic prerequisite that these inexpensive methods will need to fulfill is that their lowest energy structures can be used as starting point for a subsequent local optimization at a benchmark level that will yield its GM. If this is possible, one could bypass the global optimization at the expensive method, which is currently impossible except for very small molecules. Specifically, we test our methods with clusters of second row elements including systems of several bonding types, such as alkali, metal, and covalent clusters. The results reveal that the DFTB3 method yields reasonable results and is a potential candidate for this type of applications. Even though the DFTB2 approach using standard parameters is proven to yield poor results, we show that a re-parametrization of only its repulsive part is enough to achieve excellent results, even when applied to larger systems outside the training set.

Spin-flip approach within time-dependent density functional tight-binding method: Theory and applications.

A spin-flip time-dependent density functional tight-binding (SF-TDDFTB) method is developed that describes target states as spin-flipping excitation from a high-spin reference state obtained by the spin-restricted open shell treatment. Furthermore, the SF-TDDFTB formulation is extended to long-range correction (LC), denoted as SF-TDLCDFTB. The LC technique corrects the overdelocalization of electron density in systems such as charge-transfer systems, which is typically found in conventional DFTB calculations as well as density functional theory calculations using pure functionals. The numerical assessment of the SF-TDDFTB method shows smooth potential curves for the bond dissociation of hydrogen fluoride and the double-bond rotation of ethylene and the double-cone shape of H3 as the simplest degenerate systems. In addition, numerical assessments of SF-TDDFTB and SF-TDLCDFTB for 39 S0 /S1 minimum energy conical intersection (MECI) structures are performed. The SF-TDDFTB and SF-TDLCDFTB methods drastically reduce the computational cost with accuracy for MECI structures compared with SF-TDDFT.

Size dependent content of structural vacancies within TiO nanoparticles: Quantum-chemical DFTB study

The bulk titanium monoxide TiO – a promising thermoelectric component – contains a significant number of structural vacancies on both sublattices even at strictly stoichiometric composition. Their condition predetermines many physical properties of TiO, including electronic structure. Yet, the role of specific surface and the size factor in regulation of both distribution and concentration of the vacancies in nanosized TiO has not been elucidated. To fulfill this gap the quantum-chemical DFTB calculations have been performed. According to calculations, the content of vacancies in a TiO nanoparticle should be lower, than that in the bulk, hence, the surface acts as a structure stabilizing agent. At that, the calculated DOS for both the crystals with vacancies and the nanoparticles with any content of vacancies possess a great similarity.

Influence of porosity and methyl doping inside silica network: An electron diffraction and DFTB analysis

The continuous scaling of transistor size towards deep submicron level demands an inevitable replacement of SiO2 with a low-k dielectric material. Doping of methyl groups in SiO2 network reduces the dielectric constant by replacing oxygen atoms bonded with silicon and creating a lower polarizable silicon methyl bond in the network. Further reduction in dielectric constant is possible by introducing porosity in the dense low-k network. The detailed knowledge about atomic structure of such low-k materials is a must for understanding their electronic and optical properties. In this study, electron diffraction and (density functional based tight binding) DFTB calculations are used to investigate the structure of dense and porous low-k dielectric materials. The radial distribution function (RDF) obtained from electron diffraction technique contains information about the short-range order present in the material. Bond lengths and bond angles determined from RDF indicate a significant modification occurring in the SiO2 network after doping with methyl groups. The local density of the materials is also derived from radial distribution function. It depends on the number and distances of nearest neighbors and was found to be decreased in these low-k materials compared with amorphous SiO2.

Two-dimensional titanium carbonitrides and their hydroxylated derivatives: Structural, electronic properties and stability of MXenes Ti3C2−xNx(OH)2 from DFTB calculations

3D titanium carbonitrides TiCxNy possess excellent physical, chemical, and mechanical properties, attractive for various industrial applications. Most recently, the uncommon nano-sized layers of 2D-like titanium carbonitrides were fabricated from MAX phases. Herein, the structural, electronic properties and stability of these new compounds as well as their hydroxylated derivatives - so-called MXenes Ti3C2-xNx and Ti3C2-xNx(OH)2 are probed by means of SSC-DFTB calculations. The genesis of the properties is discussed in the sequence: binary MXenes Ti3C2 (Ti3N2) -> their hydroxylated forms Ti3C2(OH)2 (Ti3N2(OH)2) -> pristine MXene Ti3C2-xNx -> hydroxylated Ti3C2-xNx(OH)2. Our results show that the examined materials are metallic-like. The most favorable type of OH-covering is presented by the occupation of the hollow sites between three neighboring carbon (nitrogen) atoms. The formation of 2D MXene carbonitrides with random distribution of C and N atoms was found to be thermodynamically more favorable.

A big data approach to the ultra-fast prediction of DFT-calculated bond energies

BackgroundThe rapid access to intrinsic physicochemical properties of molecules is highly desired for large scale chemical data mining explorations such as mass spectrum prediction in metabolomics, toxicity risk assessment and drug discovery. Large volumes of data are being produced by quantum chemistry calculations, which provide increasing accurate estimations of several properties, e.g. by Density Functional Theory (DFT), but are still too computationally expensive for those large scale uses. This work explores the possibility of using large amounts of data generated by DFT methods for thousands of molecular structures, extracting relevant molecular properties and applying machine learning (ML) algorithms to learn from the data. Once trained, these ML models can be applied to new structures to produce ultra-fast predictions. An approach is presented for homolytic bond dissociation energy (BDE).ResultsMachine learning models were trained with a data set of >12,000 BDEs calculated by B3LYP/6-311++G(d,p)//DFTB. Descriptors were designed to encode atom types and connectivity in the 2D topological environment of the bonds. The best model, an Associative Neural Network (ASNN) based on 85 bond descriptors, was able to predict the BDE of 887 bonds in an independent test set (covering a range of 17.67–202.30 kcal/mol) with RMSD of 5.29 kcal/mol, mean absolute deviation of 3.35 kcal/mol, and R2 = 0.953. The predictions were compared with semi-empirical PM6 calculations, and were found to be superior for all types of bonds in the data set, except for O-H, N-H, and N-N bonds. The B3LYP/6-311++G(d,p)//DFTB calculations can approach the higher-level calculations B3LYP/6-311++G(3df,2p)//B3LYP/6-31G(d,p) with an RMSD of 3.04 kcal/mol, which is less than the RMSD of ASNN (against both DFT methods). An experimental web service for on-line prediction of BDEs is available at http://joao.airesdesousa.com/bde.ConclusionKnowledge could be automatically extracted by machine learning techniques from a data set of calculated BDEs, providing ultra-fast access to accurate estimations of DFT-calculated BDEs. This demonstrates how to extract value from large volumes of data currently being produced by quantum chemistry calculations at an increasing speed mostly without human intervention. In this way, high-level theoretical quantum calculations can be used in large-scale applications that otherwise would not afford the intrinsic computational cost.

Layers and tubes of fluorographene C4F: Stability, structural and electronic properties from DFTB calculations

By means of the DFTB band structure calculations we have explored the layers’ isomerism of fluorographene C4F. The relative stability, structural and electronic properties of the C4F layers and nanotubes have been revealed depending on the possible types of fluorine coverage: single-sided, double-sided or so-called non-uniform variants. Our main finding is that the aforementioned types of fluorine coverage are crucial for the morphology of these materials. At the non-uniform or single-sided coverage types the C4F structures aspire to the spontaneous folding in order to minimize their surface tension.

Speciation of Copper–Peptide Complexes in Water Solution Using DFTB and DFT Approaches: Case of the [Cu(HGGG)(Py)] Complex

The DFTB and DFT methods are applied to the study of different forms of the [Cu(HGGG)(Py)] complex in water, with the aim of identifying the most stable isomer. The DFTB calculations were possible thanks to a careful parametrization of the atom-atom repulsive energy terms for Cu-H, Cu-C, Cu-N, and Cu-O. The speciation process is carried out by computing different DFTB-steered molecular dynamics (SMD) trajectories, each of which ends in a well-defined different form. The last frame of each trajectory is subjected to geometry optimization at both DFTB and DFT levels, leading to a different isomer. From the corresponding energy values, a rank of relative stability of the isomers can be established. The computational protocol developed here is of general applicability to other metal-peptide systems and represents a new powerful tool for the study of speciation of metal-containing systems in water solution, particularly useful when the full characterization of the compound cannot be carried out on the basis of experimental results only.

Stability and structural, elastic, and electronic properties of 3D-(sp 3) carbon allotropes according to DFTB calculations

Stability and structural, elastic, and electronic properties of 3D-(sp 3) carbon allotropes according to DFTB calculations