Density Functional Based Tight Binding Research Articles

DFTB Simulation of Charged Clusters Using Machine Learning Charge Inference.

We present a modification to self-consistent charge density functional-based tight binding (SCC-DFTB), which allows computation based on approximate atomic charges. We obtain these charges by means of a machine learning (ML) process that combines a Coulomb model with a neural network. This allows us to avoid the SCC cycles in the SCC-DFTB calculation while maintaining its accuracy. The main input of the model is the atomic positions characterized by a set of atom-centered symmetry functions. The charge inference from our ML algorithm is as close as 10-2 units of charge from the exact SCC solution. Our ML-DFTB approach provides a good approximation of the density matrix and of the energy and forces with only a single diagonalization. This is a significant computational saving with respect to the complete SCC algorithm, which allows us to investigate a bigger ensemble of atoms. We show the quality of our approach in the case of charged silicon carbide (SiC) clusters. The ML-DFTB potential energy surface (PES) mimics the SCC-DFTB PES rather well, despite its simplicity. This allows us to obtain the same geometric structure ordering with respect to energy for small clusters. The dissociation barriers for ion emission are well-reproduced, which opens the way to investigating ion field emission and charged cluster stability. The ML-DFTB approach is obviously not limited to charged clusters or SiC materials. It opens a new route to investigate larger clusters than those investigated by standard SCC-DFTB, as well as surface and solid-state chemistry at the atomic level.

Probing the electronic structure and ground state symmetry of gas phase C60+ via VUV photoionization and comparison with theory.

Recently, some of us reviewed and studied the photoionization dynamics of C60 that are of great interest to the astrochemical community as four of the diffuse interstellar bands (DIBs) have been assigned to electronic transitions in the C60+ cation. Our previous analysis of the threshold photoelectron spectrum (TPES) of C60 [Hrodmarsson et al., Phys. Chem. Chem. Phys. 22, 13880-13892 (2020)] appeared to give indication of D3d ground state symmetry, in contrast to theoretical predictions of D5d symmetry. Here, we revisit our original measurements taking account of a previous theoretical spectrum presented in the work of Manini et al., Phys. Rev. Lett. 91(19), 196402 (2003), obtained within a vibronic model parametrized on density functional theory/local-density approximation electronic structure involving all hg Jahn-Teller active modes, which couple to the 2Hu components of the ground state of the C60+ cation. By reanalyzing our measured TPES of the ground state of the C60 Buckminsterfullerene, we find a striking resemblance to the theoretical spectrum calculated in the work of Manini et al., Phys. Rev. Lett. 91(19), 196402 (2003), and we provide assignments for many of the hg modes. In order to obtain deeper insights into the temperature effects and possible anharmonicity effects, we provide complementary modeling of the photoelectron spectrum via classical molecular dynamics (MD) involving density functional based tight binding (DFTB) computations of the electronic structure for both C60 and C60+. The validity of the DFTB modeling is first checked vs the IR spectra of both species which are well established from IR spectroscopic studies. To aid the interpretation of our measured TPES and the comparisons to the abinitio spectrum we showcase the complementarity of utilizing MD calculations to predict the PES evolution at high temperatures expected in our experiment. The comparison with the theoretical spectrum presented in the work of Manini et al., Phys. Rev. Lett. 91(19), 196402 (2003), furthermore, provides further evidence for a D5d symmetric ground state of the C60+ cation in the gas phase, in complement to IR spectroscopy in frozen noble gas matrices. This not only allows us to assign the first adiabatic ionization transition and thus determine the ionization energy of C60 with greater accuracy than has been achieved at 7.598 ± 0.005eV, but we also assign the two lowest excited states (2E1u and 2E2u) which are visible in our TPES. Finally, we discuss the energetics of additional DIBs that could be assigned to C60+ in the future.

Environmentally Benign Grape Seed Oil for Corrosion Inhibition: Cutting-Edge Computational Modeling Techniques Revealing the Intermolecular and Intramolecular Synergistic Inhibition Action

The growing interest in eco-friendly alternatives has sparked research into essential oils as corrosion inhibitors, offering an innovative approach. Investigating their unique properties, researchers aim to advance corrosion engineering for a sustainable future. Despite promising lab results, the exact mechanism of their action in corrosion engineering is not fully understood, highlighting the need for further exploration. Using computational modeling, we explored how grape seed oil (GSO) compounds interact with carbon steel (C38) surfaces, unraveling the inhibitive properties against corrosion. Employing various simulation methods, such as density functional theory (DFT), density functional-based tight-binding (DFTB), and molecular dynamics (MD), this study validates experimental findings and unveils novel insights into the underlying mechanisms of these interactions. Quantitative analysis quantifies the inter- and intramolecular synergistic effect and suggests that the LA@OA promotes the charge-transfer process. DFTB calculations reveal that the synergistic action in the parallel adsorption configuration of LA and OA molecules is sufficiently strong to form a stable adsorption layer on the Fe surface with a large negative value of Eads (6.74 eV). Experimental results demonstrated that the inhibition performance of GSO extract exhibited a notable increase with increasing concentrations, reaching a higher efficiency of 79% at 0.5 g/L of GSO. EIS results demonstrated that the existence of the GSO inhibitor film increases the resistance of the charge transfer (about 80 Ω cm2 at 0.5 g/L), indicating the superior barrier anticorrosion properties of the formed film. The theoretical results validate the exceptional anticorrosion performance and provide compelling evidence of the remarkable ability to prevent corrosion of C38 substrate. The findings offer potential pathways for the development of eco-friendly alternatives and interestingly provide a foundation understanding in the field.

Addressing electronic and dynamical evolution of molecules and molecular clusters: DFTB simulations of energy relaxation in polycyclic aromatic hydrocarbons.

We present a review of the capabilities of the density functional based Tight Binding (DFTB) scheme to address the electronic relaxation and dynamical evolution of molecules and molecular clusters following energy deposition via either collision or photoabsorption. The basics and extensions of DFTB for addressing these systems and in particular their electronic states and their dynamical evolution are reviewed. Applications to PAH molecules and clusters, carbonaceous systems of major interest in astrochemical/astrophysical context, are reported. A variety of processes are examined and discussed such as collisional hydrogenation, fast collisional processes and induced electronic and charge dynamics, collision-induced fragmentation, photo-induced fragmentation, relaxation in high electronic states, electronic-to-vibrational energy conversion and statistical versus non-statistical fragmentation. This review illustrates how simulations may help to unravel different relaxation mechanisms depending on various factors such as the system size, specific electronic structure or excitation conditions, in close connection with experiments.

Performance Evaluation of DFTB1 and DFTB2 Methods in reference to the Crystal Structures and Molecular Energetics of Siloxaalkane Molecular Compass

In the lately developed computational paradigms and state-of-art theoretical analyses, the density-functional based tight-binding (DFTB) scheme and its profound theoretical features extended to address the crystalline molecular systems stand as the most versatile quantum mechanical method. Being its computational parser codes extremely efficient and even assessable directly as a low-cost scheme despite hosting ab initio functionalities comprising mathematical formulations, the “non-self-consistent-charge” (DFTB1) and “self-consistent-charge" (DFTB2) approaches are extensively applied to the wide ranged molecular systems under both crystalline (PBC) and non-crystalline conditions. The "dispersion energy corrections (DECs)" features of it further add an additional value to their rational applications. Herewith, the intensive evaluations on their performances are carried out based on the results they produced for the experimentally synthesized amphidynamic type molecular crystal with macroscopic compass like supramolecular assembly possessing central dipolar difluorophenylene rotator (compass needle), axial Si-C bond spin axis, and peripheral -Si- & -Si-O- made siloxaalkane stator. It is found that the DFTB2 performed far better than the DFTB1 in reference to its datasets: (a) lengths for the bonds associated with rotator, stator, and spin axis, (b) free-volume unit around the rotator, (c) rotational energy barriers, viz. = 5.99 kcal/mol, & 5.52 kcal/mol under PBC with and without DECs, and (d) locations of the 1p-flipped (rotator) degenerate equilibrium structures, viz. at f = 0.505p & 1.493p (Expt. f = 0.56p & 1.56p) radians. Besides this, the dispersion constants for the F atom; cutoff =3.8Å, polarizability =3.4Å3, and effective nuclear charge =3.5au determined by DFTB2, and the precise unit-cell geometries derived by undertaking these numeral values further exemplified its superiority over DFTB1. It is believed that all the justifications and quantitative interpretations conferred throughout this article put considerable demands on the accuracy of DFTB2 for investigating crystal structures and molecular energetics explicitly.

Diversity of Behavior after Collisions of Sn and Si Nanoparticles Found Using a New Density Functional Tight-Binding Method.

We present a new approach to studying nanoparticle collisions using density functional based tight binding (DFTB). A novel DFTB parametrization has been developed to study the collision process of Sn and Si clusters (NPs) using molecular dynamics (MD). While bulk structures were used as training sets, we show that our model is able to accurately reproduce the cohesive energy of the nanoparticles using density functional theory (DFT) as a reference. A surprising variety of phenomena are revealed for the Si/Sn nanoparticle collisions, depending on the size and velocity of the collision: from core-shell structure formation to bounce-off phenomena.

Why DFT‐Based Tight Binding Gives a Better Representation of the Potential at Metal‐Solution Interfaces than DFT Does

AbstractIn modelling electrochemical interfaces it is important to treat electrode and electrolyte at the same level of theory. Density functional theory, which is usually the method of choice, suffers from a distinct disadvantage: The inner potential is calculated as the average of the total electrostatic potential. This includes the highly localized potential generated from the nuclei. The resulting inner potential is far too high, of the order of 3.5 V, and not relevant for electrochemistry. In the density functional based tight binding (DFTB) method the electrostatic potential is much smoother, as it stems from atomic charge fluctuations with respect to neutral reference atoms. The resulting values for the electrochemical inner potential are much lower and compare well with those obtained by other, elaborate methods. Thus DFTB recommends itself as a method for treating the electrochemical interface including the inner potential.

Treating Semiempirical Hamiltonians as Flexible Machine Learning Models Yields Accurate and Interpretable Results.

Quantum chemistry provides chemists with invaluable information, but the high computational cost limits the size and type of systems that can be studied. Machine learning (ML) has emerged as a means to dramatically lower the cost while maintaining high accuracy. However, ML models often sacrifice interpretability by using components such as the artificial neural networks of deep learning that function as black boxes. These components impart the flexibility needed to learn from large volumes of data but make it difficult to gain insight into the physical or chemical basis for the predictions. Here, we demonstrate that semiempirical quantum chemical (SEQC) models can learn from large volumes of data without sacrificing interpretability. The SEQC model is that of density-functional-based tight binding (DFTB) with fixed atomic orbital energies and interactions that are one-dimensional functions of the interatomic distance. This model is trained to ab initio data in a manner that is analogous to that used to train deep learning models. Using benchmarks that reflect the accuracy of the training data, we show that the resulting model maintains a physically reasonable functional form while achieving an accuracy, relative to coupled cluster energies with a complete basis set extrapolation (CCSD(T)*/CBS), that is comparable to that of density functional theory (DFT). This suggests that trained SEQC models can achieve a low computational cost and high accuracy without sacrificing interpretability. Use of a physically motivated model form also substantially reduces the amount of ab initio data needed to train the model compared to that required for deep learning models.

Tracking the Electron Transfer Cascade in European Robin Cryptochrome 4 Mutants

The primary step in the mechanism by which migratory birds sense the Earth's magnetic field is thought to be the light-induced formation of long-lived magnetically sensitive radical pairs within cryptochrome flavoproteins located in the birds' retinas. Blue-light absorption by the non-covalently bound flavin chromophore triggers sequential electron transfers along a chain of four tryptophan residues toward the photoexcited flavin. The recently demonstrated ability to express cryptochrome 4a from the night-migratory European robin (Erithacus rubecula), ErCry4a, and to replace each of the tryptophan residues by a redox-inactive phenylalanine offers the prospect of exploring the roles of the four tryptophans. Here, we use ultrafast transient absorption spectroscopy to compare wild type ErCry4a and four mutants having a phenylalanine at different positions in the chain. We find that each of the three tryptophan residues closest to the flavin adds a distinct relaxation component (time constants: 0.5, 30, and 150 ps) in the transient absorption data. The dynamics of the mutant containing a phenylalanine at the fourth position, furthest from the flavin, are very similar to those of wild type ErCry4a, except for a reduced concentration of long-lived radical pairs. The experimental results are evaluated and discussed in the framework of real-time quantum mechanical/molecular mechanical electron transfer simulations based on the density functional-based tight binding approach. This comparison between simulation results and experimental measurements provides a detailed microscopic insight into the sequential electron transfers along the tryptophan chain. Our results offer a route to the study of spin transport and dynamical spin correlations in flavoprotein radical pairs.

Effect of ZnO dimers on the thermoelectric performance of armchair graphene nanoribbons.

Enhancing the thermoelectric performance in engineered graphene nanoribbons is used to produce thermoelectric nanodevices, which are important in many applications. By using a chemical doping method, armchair graphene nanoribbons (AGNRs) can have thermoelectric properties that are tunable. We predicted that changing the number and geometrical pattern of zinc oxide (ZnO) dimers in an AGNR can engineer thermoelectric properties, so we used density functional-based tight binding (DFTB) combined with the non-equilibrium Green's function (NEGF) to investigate the geometric, electronic, and thermoelectric properties of the AGNR with and without various dopants of ZnO dimers. With three forms of ZnO dimers, ortho, meta, and para dimers, different concentration ratios of Zn and O atoms are used. Our results indicate that the electronic features of AGNR are influenced not only by the concentrations of ZnO dimers but also by the geometrical pattern of ZnO dimers in the AGNR. These results are helpful in better understanding the effect of chemical doping on the transport properties of AGNRs and in motivating nanodevices to improve their thermoelectric performance.

Structures and stabilities of PAH clusters solvated by water aggregates: The case of the pyrene dimer.

Although clusters made of polycyclic aromatic hydrocarbon and water monomers are relevant objects in both atmospheric and astrophysical science, little is known about their energetic and structural properties. In this work, we perform global explorations of the potential energy landscapes of neutral clusters made of two pyrene units and one to ten water molecules using a density-functional-based tight-binding (DFTB) potential followed by local optimizations at the density-functional theory level. We discuss the binding energies with respect to various dissociation channels. It shows that cohesion energies of the water clusters interacting with a pyrene dimer are larger than those of the pure water clusters, reaching for the largest clusters an asymptotic limit similar to that of pure water clusters and that, although the hexamer and octamer can be considered magic numbers for isolated water clusters, it is not the case anymore when they are interacting with a pyrene dimer. Ionization potentials are also computed by making use of the configuration interaction extension of DFTB, and we show that in cations, the charge is mostly carried by the pyrene molecules.

Insights into the Corrosion Inhibition Performance of Three 2-Isoxazoline-γ-Lactones for Carbon Steel in Acidic Medium: Linking Molecular and Experimental-Level Information with Microscopic-Scale Modeling

The corrosion inhibition properties of three spiro-isoxazoline derivatives, namely 3,4-diphenyl-1,7-dioxa-2-azaspiro[4.4]non-2-en-6-one (DDA), 3-phenyl-4-(p-tolyl)-1,7-dioxa-2-azaspiro[4.4]non-2-en-6-one (PDA) and 4-(4-methoxyphenyl)-3-phenyl-1,7-dioxa-2-azaspiro[4.4]non-2-en-6-one (MDA) on carbon steel in 1.0 mol/L HCl acid medium were experimentally and computationally investigated. The experimental results showed that the inhibitory efficiency reached remarkable values of 76.26, 80.31, and 82.91%, respectively, for DDA, PDA and MDA at a maximum concentration of 10−3 mol/L. The potentiodynamic polarization curves (PPCs) showed that investigated compounds had a mixed type character, controlling both anodic and cathodic corrosion reactions. In addition, electrochemical impedance spectroscopy (EIS) indicated that the addition of increasing concentration of tested compounds to HCl solutions led to a significant increase in the polarization resistance of the carbon steel, which was accompanied with a simultaneous decrease in the double layer capacitance. On the other hand, the morphological study of the metal surface by scanning electron microscope (SEM) and energy dispersive X-ray (EDX) confirmed the effective protection of the carbon steel by the inhibitors against corrosion through the formation of a protective film on its surface. The adsorption characteristics of investigated compounds on carbon steel were assessed at microscopic level using Density Functional Based Tight Binding (DFTB) simulation, which revealed the formation of covalent bonds between inhibitors’ atoms and Fe atoms. Furthermore, additional insights into the compounds’ reactivity and adsorption configurations on steel surface were obtained from global reactivity descriptors and Monte Carlo simulation. The present work’s outcomes are interesting for further design and performance evaluation of effective organic corrosion inhibitors for acid environments.

Accuracy of Computational Chemistry Methods to Calculate Organic Contaminant Molecular Properties

AbstractThe quantitative structure activity relationship (QSAR) methodology has been developed and extensively used to predict unknown environmental data for compounds that have not been experimentally studied yet. QSAR is based on a large series of descriptors: such as the number of atoms, the number of bonds… (descriptive), or based on the 2D structure of the molecule (connectivity indices…) or on its 3D structure (dipole moment, polarizability…). Among them, quantum‐based 3D descriptors appear as promising tools to predict macroscopic environmental properties. For a set of 104 pharmaceuticals and personal care products, four quantum‐based 3D descriptors (electric dipole moment, polarizability, HOMO energy and ionization potential) were calculated using different computational chemistry strategies involving a conformational search followed by local quenches within three different frameworks: density functional theory (DFT), semi‐empirical Austin Model 1 (AM1) approach, and density functional based tight binding (DFTB). Comparing the results obtained using each framework highlights the necessity of a comprehensive conformational search and the use of an accurate potential for the local quenches. Using the combination of a global exploration through molecular dynamics with local quenches at B3LYP/6‐31G* (DFT) allows the calculation of accurate and tractable quantum‐based 3D descriptors.

Mechanical and Electronic Properties of a Carbon-Composite 3D Nanomaterial with an Island-Type Topology

An atomistic model of a carbon-composite 3D nanomaterial with an island-type topology based on fullerene and graphene fragments as well as chiral/achiral single-walled carbon nanotubes (SWCNTs) with a subnanometer diameter is constructed. The island type refers to the presence of inhomogeneously distributed local regions with increased density of the nanomaterial in the structure of the composite. The effect of the concentration of nanotubes in the composite on the volume compressibility and electronic properties is investigated. It is found that an increase in the mass fraction of SWCNTs in the composite leads to a decrease in the coefficient of volume compressibility and, at the same time, improvement in the conductive properties. Classical molecular dynamics and the density functional based tight binding (DFTB) method with the use of dispersive energy correction are used for the physically correct description of individual fragments of the composite which are not covalently bound.

(Digital Presentation) Charge Trapping in TiO2 Nanoparticles

TiO2 is a common component of electrode surfaces and photocatalytic systems. Depending on the preparation, the oxide can be formed in different shapes and morphology which can effect the selectivity and efficiency of the electrode [1]. Since the morphology and shape of the nanoparticles can be easily tuned with experimental conditions, this may offer a new, unexplored strategy to improve electrode properties in these systems. The goal of our computational studies is to understand better how charge carriers behave in these oxide nanoparticles.We studied the electronic states around the bandgap in anatase-type TiO2 nanoparticles of different shapes with (101) and (001) facets using Density Functional based Tight Binding (DFTB) and DFT methods. The previous calculation has already shown that most orbitals of the valence and conduction bands form delocalized band-like orbitals; however, there are a significant number of localized states at the lower edge of the conduction band, too. The calculations clearly show the position of these trapping sites when we compare the electron density of neutral and charged nanoparticles. Reference: [1] Selectivity enhancement in the electrochemical reduction of oxalic acid over titanium dioxide nanoparticles achieved by shape and energy-state control. H Eguchi, K Kato, G Juhasz, M Yamauchi - Catalysis Science & Technology, 2021Figure 1. The electron density difference between negatively charged and neutral nanoparticle (left); electron density difference reflected in Mulliken charges of the atoms (right). Figure 1

Eco-Friendly Synthesis and Characterization of Double-Crossed Link 3D Graphene Oxide Functionalized With Chitosan for Adsorption of Sulfamethazine From Aqueous Solution: Experimental and DFT Calculations

Graphene oxide–chitosan composites are attracting considerable interest as an eco-friendly adsorbent material for most aquatic environmental pollutants. Today, the focus is on the emerging applications of 2D and 3D graphene functionalized with chitosan to enhance its mechanical properties and adsorption efficiency. Herein, the super adsorbent 3D graphene functionalized with chitosan (3D GF-CS) is synthesized to remove sulfamethazine, (SMZ) as a model aquatic antibiotic pharmaceutical. The synthesized materials were characterized by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), X-ray photon spectroscopy (XPS), Brunauer–Emmett–Teller (BET), and Raman spectroscopy. After that, adsorption experiments were conducted for SMZ adsorption to find out the optimized adsorption parameters, such as pH, temperature, contact time, initial antibiotic concentration, and adsorbent dosage. The results show the optimal adsorption parameters were as pH of 7, temperature of 25°C, initial antibiotic concentration Ci of 50 ppm. Also, the kinetics, isotherms models, and thermodynamics parameters of SMZ adsorption were studied. The experimental results revealed to be best suited by both the pseudo-second-order kinetic and the Freundlich isotherm model compared with other isotherm models. The thermodynamics parameters demonstrated that the adsorption is exothermic, exhibiting higher adsorption efficiency at lower temperature. In addition, Gibb’s free energy suggested the adsorption to be spontaneous as well as entropy indication of the loss of disorder. Furthermore, the regeneration of 3D GF-CS was utilized in ten consecutive cycles, and the SMZ adsorption capacity did not decline significantly. Additionally, this research studied the adsorption energies and how sulfamethazine adsorbs onto 3D GF-CS was determined by applying the density-functional–based tight binding (DFTB) and Monte Carlo simulations at different adsorption positions. The chemical reactivity (local and global) of the free drug was investigated using the density functional theory (DFT), namely, the B3LYP and PBEPBE functionals with the 6–31+G (d, p) basis set in the gas phase and aqueous solution.

Hydrogen Titanate H2TiO3 Nanowires Derived from K2TiO3 as Potential Materials for Solar Cell Applications: A Theoretical Study

AbstractOne‐dimensional systems of titanium dioxide and titanates are interesting for the fundamental study of physical and chemical properties at the nanoscale. In this work we present the electronic structure, mechanical and optical properties of angstrom scale titanate derived nanowires (ASW) by means of density functional theory (DFT) and Density Functional based Tight Binding (DFTB). This one‐dimensional H2TiO3 nanostructure is an interesting real material that could serve for understanding, at a fundamental level, the physical properties of TiO5 concatenated polyhedrons derived from hydrogen titanates. The proposed structural model demonstrates to be locally stable according to phonon analysis, and it can be inferred that the one‐dimension structure is essentially preserved. The mechanical properties put this nanowire as a flexible material, that could be used in flexible substrates maintaining its electronic properties. Also, the capacity of this system to be sensitized with a catechol dye was explored. For this porpoise, the adsorption of the catechol molecule was tested showing that the most stable interaction corresponds to a dissociative chelate configuration. Finally, it was possible to verify the capability of the sensitized system for injecting electrons from the catechol dye to the nanowire under visible light exposure. Thus, we present these extreme one‐dimensional nanostructured materials as candidates for solar cell applications.

Predicting the interaction between organic layer and metal substrate through DFTB and electrochemical approach for excellent corrosion protection

Despite the growing interest in dealing with how to control the corrosion behavior of steel alloys via organic corrosion inhibitors (CIs), the adsorption mechanism of CIs has remained less understood with respect to the physical–chemical interactions as well as the self-assembly of organic coatings, which might be the primary sources for excellent electrochemical resistance. For this purpose, a new carbocyclic compound, namely 4-Hydroxy-3-(2-methoxybenzoyl)-2,6-bis(4-methoxylphenyl)-4-(2-methoxyphenyl)cyclohexane-1,1dicarbonitrile (PTC), was synthesized as a sustainable-green corrosion inhibitor for mild steel (MS) in HCl solution in a bid to understand the organic-metal mechanism, the adsorption behavior, and the correlation between charge transfer phenomena and corrosion properties of PTC compound. NMR (1H and 13C) spectroscopy, electrochemical techniques and surface analysis were used to characterize and evaluate the inhibitive performance of PTC compound on the metal substrate. The electrochemical results revealed that the PTC inhibitor exhibited high corrosion resistance with inhibition efficiency reaches 92.86 % at 10−3 M due to the significant growth of organic layer sealing the micro-defects present in corroded metal. Furthermore, thePTC inhibitor showed good performance at all temperatures (303–333 K) studied and maintainedprotective ability at the maximum temperature. Then, the protective layer assembled by the adsorption of PTC inhibitor presents robust protection and reliable corrosion stability. Multi-level theoretical calculations based on density functional theory (DFT), density functional based tight-binding (DFTB) and molecular dynamic (MD) simulations were performed to explore the corrosion protection mechanism activated by the presence of PTC inhibitor. As a result, the PTC-surface interactions are mainly dominated by the formation of strong covalent bonds such as N–Fe and O–Fe in the parallel adsorption geometries, in which the formation of the organic layer is consistent with improved charge transfer behavior. Thus, the PTC molecule was preferentially adsorbed through polar functional groups and exhibits high adsorption energy (–6.43 eV), resulting from self-assembly triggered by an organic-metal interaction. This was confirmed experimentally by the results of electrochemical assessments, which showed that reliable and excellent barrier properties were provided for more than 72 h owing to the significant role of functional groups in the π–π interactions of adsorbed PTC molecule. Finally, the computational perspectives provide a profound explanation for the interfacial mechanism of the PTC molecule and show a good correlation with the experimental observations.

Anticorrosive properties of green-synthetized benzylidene derivatives for mild steel in hydrochloric acid: An experimental study combined with DFTB and molecular dynamics simulations

Two benzylidene derivatives anisaldehyde-cyanoguanidine imine (CMBG) and p–dimethylaminobenzaldehyde-TRIS imine (DBHP) were prepared according to the 12 Principles of Green Chemistry. They were evaluated as corrosion inhibitors for 1020 mild steel in acidic media (HCl 1 mol L–1) by gravimetric and electrochemical measurements and reached 82 and 92% anticorrosive efficiency, respectively, at 2.20 mmol L-1. A comprehensive theoretical study was carried out using Density-Functional Based Tight Binding (DFTB) and molecular dynamics (MD) simulations. Electrochemical results indicated that inhibitors had a robust inhibitive effect on the corrosion process, significantly increasing the polarization resistance of the working electrode while reducing both cathodic and anodic corrosion reactions. Physical-chemical calculations indicated the formation of a protective multilayer and that physical–chemical adsorption governed the inhibition process. AFM and SEM with EDX analyses depicted a smoother surface in the presence of the organic molecules, pointing to the formation of a protective barrier. DFTB calculations revealed that inhibitor molecules formed covalent bonds with iron atoms, which was confirmed by the Projected Density of States (PDOS) of adsorbed systems.

A computational study of mechanical and electrical properties of zigzag graphene nanoribbon force sensor

Force sensors have many applications in new technologies such as robotic systems, medical tools and electronics. Therefore, it is necessary to make high sensitivity force sensors. Nanomaterials are very useful for making these sensors. In this paper, we study the mechanical and electrical properties of zigzag graphene nanoribbon force sensor by classical molecular dynamics (MD) with reactive force field (Reaxff) and density functional based tight binding (DFTB) combined with non-equilibrium Green's function (NEGF) method. Our results show that the bending angle, potentials energy, bond energy and deflection distance increase with increasing external force, while distance between tip and nanoribbon and electrical conductivity decrease. In addition, to study the electrical properties of force sensor, we calculated the local density of states (LDOS), density of states (DOS) and transmission spectrum. Our results show that these quantities change by external force. So we can measure them to judge the operation of sensor.