Density Functional Tight Binding Research Articles

Probing the range of applicability of structure- and energy-adjusted QM/MM link bonds III: QM/MM MD simulations of solid-state systems at the example of layered carbon structures.

The previously introduced workflow to achieve an energetically and structurally optimized description of frontier bonds in quantum mechanical/molecular mechanics (QM/MM)-type applications was extended into the regime of computational material sciences at the example of a layered carbon model systems. Optimized QM/MM link bond parameters at HSEsol/6-311G(d,p) and self-consistent density functional tight binding (SCC-DFTB) were derived for graphitic systems, enabling detailed investigation of specific structure motifs occurring in graphene-derived structures quantum-chemical calculations. Exemplary molecular dynamics (MD) simulations in the isochoric-isothermic (NVT) ensemble were carried out to study the intercalation of lithium and the properties of the Stone-Thrower-Wales defect. The diffusivity of lithium as well as hydrogen and proton adsorption on a defective graphene surface served as additional example. The results of the QM/MM MD simulations provide detailed insight into the applicability of the employed link-bond strategy when studying intercalation and adsorption properties of graphitic materials.

Benchmark Investigation of SCC-DFTB against Standard and Hybrid DFT to Model Electronic Properties in Two-Dimensional MOFs for Thermoelectric Applications.

Recent studies have shown that metal-organic frameworks (MOFs) have potential as thermoelectric materials, and the topic has received increasing attention. The main motivation for this project is to further our knowledge of thermoelectric properties in MOFs and find which available self-consistent-charge density functional tight binding (SCC-DFTB) method can best predict (at least trends in) the electronic properties of MOFs at a lower computational cost than standard density functional theory (DFT). In this work, the electronic properties of monolayer, serrated, AA-stacked, and/or AB-stacked Zn3C6O6, Cd3C6O6, Zn-NH-MOF─for which no previous calculations of thermoelectric performance exist─and Ni3(HITP)2 MOFs are modeled with DFT-PBE, DFT-HSE06, GFN1-xTB, GFN2-xTB, and DFTB-3ob/mio. The band structures, density of states, and their relative orbital contributions, as well as the electrical conductivity, Seebeck coefficient, and power factor, are compared across methods and geometries. Our results suggest that GFN-xTB is adequate to predict the MOFs' band structure shape and density of states but not band gap. Our calculations further indicate that Zn3C6O6, Cd3C6O6, and Zn-NH-MOF have higher power factor values than Ni3(HITP)2, one of the highest performing synthesized MOFs, and are therefore promising for thermoelectric applications.

Exploring the Mechanisms behind Non-aromatic Fluorescence with the Density Functional Tight Binding Method.

Recent experimental findings reveal nonconventional fluorescence emission in biological systems devoid of conjugated bonds or aromatic compounds, termed non-aromatic fluorescence (NAF). This phenomenon is exclusive to aggregated or solid states and remains absent in monomeric solutions. Previous studies focused on small model systems in vacuum show that the carbonyl stretching mode along with strong interaction of short hydrogen bonds (SHBs) remains the primary vibrational mode explaining NAF in these systems. In order to simulate larger model systems taking into account the effects of the surrounding environment, in this work we propose using the density functional tight-binding (DFTB) method in combination with non-adiabatic molecular dynamics (NAMD) and the mixed quantum/molecular mechanics (QM/MM) approach. We investigate the mechanism behind NAF in the crystal structure of l-pyroglutamine-ammonium, comparing it with the related nonfluorescent amino acid l-glutamine. Our results extend our previous findings to more realistic systems, demonstrating the efficiency and robustness of the proposed DFTB method in the context of NAMD in biological systems. Furthermore, due to its inherent low computational cost, this method allows for a better sampling of the nonradiative events at the conical intersection which is crucial for a complete understanding of this phenomenon. Beyond contributing to the ongoing exploration of NAF, this work paves the way for future application of this method in more complex biological systems such as amyloid aggregates, biomaterials, and non-aromatic proteins.

Relation of alkyl chain length and corrosion inhibition efficiency of N-Acylated Chitosans over mild steel in acidic medium

The present investigation is focussed on unveiling the potential of ecologically safe Chitosan derived N-Acylated products (N-ACs) as anti-corrosive agents for mild steel in 0.5M H2SO4. Electrochemical Impedance Spectroscopy (EIS) including potentiodynamic polarization (PDP) and potentiostatic electrochemical impedance were deployed to evaluate their anti-corrosive performance and the results of the same reported N-acylated chitosan derivatives project remarkable inhibition efficiency with the most effective performance of 96.80% at 250 mgL-1. The pronounced inhibition efficiency reported was conclusively accredited to the availability of heteroatoms in modified chitosan which further aid in the formation of a protective barrier over mild steel counterparts. The final acylated products were reported to be mixed type as demarcated by PDP results. Further, the prevention ability of modified chitosan was obtained via adsorption and the Langmuir adsorption model was best seen as suitable in this regard. Surface studies and theoretical modeling including Global Reactivity results, molecular Dynamic Modelling (MD), and Density Functional Bond Tight Binding Results (DFBT) were incorporated to gain insights into the molecular level of interactions between metal and N-ACs.

The Density Functional Tight Binding (DFTB) Approach for Investigating Vacancy and Doping in Graphene as Hydrogen Storage

A study on graphene defects for hydrogen storage has been successfully conducted using the Density Functional Tight Binding (DFTB) approach. The research aimed to modify solid materials for hydrogen storage. A 4 × 4 × 1 unit cell was used as the basis, while the supercell used for sampling was enlarged to 40 × 40 × 1. The analyzed data included changes in Density of States (DOS), Fermi level shifts, electronic band structures, formation energy, adsorption energy, and isosurfaces for each graphene orientation. It has been observed that modifying the surface structure of graphene can alter the electronic properties of graphene. This is indicated by shifts in DOS intensity, characterized by increased electronic intensity around the Fermi level total density charge different. The interaction energy between graphene and hydrogen gas has been determined to be -0.0155 eV for H-epoxy graphene, -0.4941 eV for H-monovacancy graphene, and -0.0424 eV for HN-monovacancy graphene. The presence of the vacancy increase the potential to adsorp hydrogen.

Enhanced Photocatalytic Activity of Surface‐Modified TiO2 with Bimetallic AuPd Nanoalloys for Hydrogen Generation

Herein, commercial titania (TiO2‐P25) is modified with mono‐ and bi‐metallic (Au, Pd, and AuPd) nanoparticles synthesized by chemical reduction method using NaBH4 as a strong reducing agent at room temperature. Bimetallic AuPd nanoalloys homogeneous in size and well dispersed on the TiO2 surface are obtained. The charge‐carrier dynamics, which is a key factor in photocatalysis, is studied by time‐resolved microwave conductivity. The results reveal that surface modification plays a crucial role in charge‐carrier separation, increasing the activity under UV–vis light irradiation. The bimetallic AuPd nanoalloys formation is confirmed by high‐angle annular dark field scanning transmission electron microscopy and corroborated by semiempirical molecular dynamics simulations (Gupta‐LAMMPS). The surface‐modified TiO2 with bimetallic AuPd nanoalloys exhibits higher photocatalytic activity compared to TiO2 modified with their monometallic counterparts. The experimental results are also supported by density functional theory and density functional tight binding calculations, which show that alloying AuPd with low Pd content presents significant synergetic effects for hydrogen generation under UV–vis light from aqueous triethanolamine solutions. Additionally, the AuPd/TiO2 photocatalysts are stable with cycling.

A multi-scale computational investigation of cationic dye interaction with rutile TiO2: An interconnected simulation approach

Metal oxides have increasingly been employed for water pollution remediation. In the present investigation, the adsorptive characteristics of three cationic dyes, rhodamine B (RB), safranin O (SO), and methylene blue (MB), on the (110) surface of rutile titanium dioxide in an aqueous milieu were scrutinized. Utilizing Density Functional Theory (DFT), the reactivity of these organic compounds was evaluated by computing parameters such as molecular frontier orbital energies, energy gap (ΔEgap), electronegativity (χ), chemical hardness (η), chemical softness (σ), electrophilicity (ω), nucleophilicity, electron transfer fraction (ΔN), and Fukui indices. Findings demonstrated that RB exhibited superior reactivity and adsorptive capacity in comparison to MB and SO. Self-Consistent Charge Density-Functional Tight-Binding (SCC-DFTB) simulations revealed that RB engaged in the most potent interactions with the TiO2(110) surface, with interaction energies following the sequence RB (−1.12 eV) > MB (−1.07 eV) > SO (−1.01 eV). Furthermore, the most energetically favorable adsorption configurations for these dyes were elucidated through Molecular Dynamics (MD) simulations. Adsorption energies calculated via MD simulations corroborated that the TiO2 (110) surface possessed high adsorptive capabilities for these cationic dyes, particularly a stronger affinity for RB. The study provides comprehensive insights into the molecular-level interactions between cationic dyes and rutile TiO2, thereby contributing valuable information for the optimization of metal oxide-based water pollution treatment technologies.

First-Principles Models of Polymorphism of Pharmaceuticals: Maximizing the Accuracy-to-Cost Ratio.

Accuracy and sophistication of in silico models of structure, internal dynamics, and cohesion of molecular materials at finite temperatures increase over time. Applicability limits of ab initio polymorph ranking that would be feasible at reasonable costs currently represent crystals of moderately sized molecules (less than 20 nonhydrogen atoms) and simple unit cells (containing rather only one symmetry-irreducible molecule). Extending the applicability range of the underlying first-principles methods to larger systems with a real-life significance, and enabling to perform such computations in a high-throughput regime represent additional challenges to be tackled in computational chemistry. This work presents a novel composite method that combines the computational efficiency of density-functional tight-binding (DFTB) methods with the accuracy of density-functional theory (DFT). Being rooted in the quasi-harmonic approximation, it uses a cheap method to perform all of the costly scans of how static and dynamic characteristics of the crystal vary with respect to its volume. Such data are subsequently corrected to agree with a higher-level model, which must be evaluated only at a single volume of the crystal. It thus enables predictions of structural, cohesive, and thermodynamic properties of complex molecular materials, such as pharmaceuticals or organic semiconductors, at a fraction of the original computational cost. As the composite model retains the solid physical background, it suffers from a minimum accuracy deterioration compared to the full treatment with the costly approach. The novel methodology is demonstrated to provide consistent results for the structural and thermodynamic properties of real-life molecular crystals and their polymorph ranking.

Exploring Molecular Energy Landscapes by Coupling the DFTB Potential with a Tree-Based Stochastic Algorithm: Investigation of the Conformational Diversity of Phthalates.

Exploring the global energy landscape of relatively large molecules at the quantum level is a challenging problem. In this work, we report the coupling of a nonredundant conformational space exploration method, namely, the robotics-inspired iterative global exploration and local optimization (IGLOO) algorithm, with the quantum-chemical density functional tight binding (DFTB) potential. The application of this fast and efficient computational approach to three close-sized molecules of the phthalate family (DBP, BBP, and DEHP) showed that they present different conformational landscapes. These differences have been rationalized by making use of descriptors based on distances and dihedral angles. Coulomb interactions, steric hindrance, and dispersive interactions have been found to drive the geometric properties. A strong correlation has been evidenced between the two dihedral angles describing the side-chain orientation of the phthalate molecules. Our approach identifies low-energy minima without prior knowledge of the potential energy surface, paving the way for future investigations into transition paths and states.

Investigating Si (100) surface patterns as well as electrical states through integrating molecular dynamics simulations with density functional tight binding at atomic level

The present work performs molecular dynamics simulations within model potential’s framework to investigate surface atoms’ rearrangements, loading states, and stress distribution in Si (100) surface on heating, and then single point energy calculations for the obtained atomic packing structures of Si substrates are used to obtain electrical information through self-consistent charge density functional tight binding approach. From analysis of Lode-Nadai parameters, atomic stress, visually packing images, Mulliken charges of atoms, Mulliken electron populations on atomic orbitals, differential charge densities, and chemical potentials for substrates, the knowledge of surface patterns, micro-loading states on the atoms and electrical states are obtained. The simulation results show the positions of vacancies have a significant impact on the rearrangements of the surface atoms. The appropriate selection of vacancy positions could be helpful in designing patterns of Si (100) surface. The vacancies in the subsurface or deeper atomic layers present migrations, where the migrations are more likely to occur at higher temperatures. There are stress concentration area and apparent charge transfers for the atoms forming dimers and neighboring atoms around the vacancies, and the differential charge densities in the surface atoms also present significant differences. These substrates with different surface patterns have different chemical potentials.

A computational study of rectification behavior of doped α-graphyne nanotubes

α-graphyne is a carbon nanosheet with sp and sp2 hybridization. This sheet is a hexagonal semi-metal like graphene. In this paper, we roll α-graphyne sheet and build zigzag nanotubes with three different size (n = 5, 6, 7). We used density functional tight binding (DFTB) to compute the band structures of nanotubes. The results show that the gap energies for n = 5, 6, 7 are about 0.648, 0.115, 0.309 eV, respectively. We add impurity atoms such as boron (B) and nitrogen (N) to nanotube. We found that the band gap energy of these doped nanotubes decrease. In addition, the structures that carbon atoms with sp2 hybridization replaced by impurity atoms are more stable. For the first time, we build two doped nanotube diodes at low (M1 model) and high (M2 model) concentration and compute current-voltage (I–V) curves with non-equilibrium Green's functions (NEGF). The I–V curves of doped nanotubes show non-linear asymmetric behavior. Form I–V curves, we compute rectification ratio and negative differential resistance (NDR). The low doped zigzag nanotube with n = 5 (M1 model) shows the highest rectification ratio (about 12.236 × 104) at 0.3 V. In addition, the rectification ratio of this diode at high concentration (M2) is about 3.67 × 103 at 0.6 V. The I–V curve of M2 model illustrations a notably negative differential resistance (NDR) at reverse bias. The ratio of current at peak to current at valley is about 26.83. To describe the I–V curves, we used transmission spectrum, the band structures of electrodes and the density of states (DOS) of central scattering region. In general, transition occurs when the energy levels of three regions (left electrode, scattering and right electrode) overlap.

Corrosion Inhibition of Expired Cefazolin Drug on Copper Metal in Dilute Hydrochloric Acid Solution: Practical and Theoretical Approaches.

In this work, we studied the corrosion of Cu metal in 0.5 mol L-1 HCl and the inhibition effect of the expired Cefazolin drug. The inhibition efficiency (IE) of Cefazolin varied according to its concentration in solution. As the Cefazolin concentration increased to 300 ppm, the IE increased to 87% at 298 K and decreased to 78% as the temperature increased to 318 K. The expired drug functioned as a mixed-type inhibitor. The adsorption of the drug on the copper surface followed Temkin's adsorption model. The magnitudes of the standard free energy change (ΔGoads) and adsorption equilibrium constant (Kads) indicated the spontaneous nature and exothermicity of the adsorption process. Energy dispersive X-ray (EDX) and scanning electron microscopy (SEM) techniques showed that the drug molecules were strongly attached to the Cu surface. The electrochemical frequency modulation (EFM), potentiodynamic polarization (PP), and electrochemical impedance spectroscopy (EIS) results were in good agreement with the results of the weight loss (WL) method. The density functional tight-binding (DFTB) and Monte Carlo (MC) simulation results indicated that the expired drug bound to the copper surface through the lone pair of electrons of the heteroatoms as well as the π-electrons of the tetrazole ring. The adsorption energy between the drug and copper metal was -459.38 kJ mol-1.

A density functional tight-binding based strategy for modeling ion bombardment and its application to Ar bombardment of silicon nitride

In many modern applications, it is important to understand mechanisms of non-equilibrium chemistry and physics that are driven by low energy ion bombardment of solid surfaces. However, the study of these processes has been challenging as it demands a relatively unique balance between chemical fidelity and computational cost. To this end, we have proposed and constructed a new, high-throughput simulation pipeline based on density functional tight binding simulations. Additionally, we have extended the parameter set pbc-0-3 with the addition of Ar, thereby enabling the simulation of Ar bombardment. This pipeline was then applied to study the structural and compositional evolution of silicon nitride (SiN) under Ar bombardment. We identified a possible rate limiting step of bombardment-driven sputtering of SiN and suggested underlying mechanisms of Si and N removal. Damage from the bombardment, including generation of surface defects and Ar implantation, are further discussed. These findings and the newly developed simulation framework will serve as a useful foundation for further research in processes driven by ion bombardment.

Assessment of Hydrazone Derivatives for Enhanced Steel Corrosion Resistance in 15 wt.% HCl Environments: A Dual Experimental and Theoretical Perspective.

This study evaluates the corrosion inhibition capabilities of two novel hydrazone derivatives, (E)-2-(5-methoxy-2-methyl-1H-indol-3-yl)-N'-(4-methylbenzylidene)acetohydrazide (MeHDZ) and (E)-N'-benzylidene-2-(5-methoxy-2-methyl-1H-indol-3-yl)acetohydrazide (HHDZ), on carbon steel in a 15 wt.% HCl solution. A comprehensive suite of analytical techniques, including gravimetric analysis, potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM), demonstrates their significant inhibition efficiency. At an optimal concentration of 5 × 10-3 mol/L, MeHDZ and HHDZ achieve remarkable inhibition efficiencies of 98% and 94%, respectively. EIS measurements reveal a dramatic reduction in effective double-layer capacitance (from 236.2 to 52.8 and 75.3 µF/cm2), strongly suggesting inhibitor adsorption on the steel surface. This effect is further corroborated by an increase in polarization resistance and a significant decrease in corrosion current density at optimal concentrations. Moreover, these inhibitors demonstrate sustained corrosion mitigation over extended exposure durations and maintain effectiveness even under elevated temperatures, highlighting their potential for diverse operational conditions. The adsorption process of these inhibitors aligns well with the Langmuir adsorption isotherm, implying physicochemical interactions at the carbon steel surface. Density functional tight-binding (DFTB) calculations and molecular dynamics simulations provide insights into the inhibitor-surface interaction mechanism, further elucidating the potential of these hydrazone derivatives as highly effective corrosion inhibitors in acidic environments.

The Effect of 8,5'-Cyclo 2'-deoxyadenosine on the Activity of 10-23 DNAzyme: Experimental and Theoretical Study.

The in vivo effectiveness of DNAzymes 10-23 (Dz10-23) is limited due to the low concentration of divalent cations. Modifications of the catalytic loop are being sought to increase the activity of Dz10-23 in physiological conditions. We investigated the effect of 5'S or 5'R 5',8-cyclo-2'deoxyadenosine (cdA) on the activity of Dz10-23. The activity of Dz10-23 was measured in a cleavage assay using radiolabeled RNA. The Density Functional Tight Binding methodology with the self-consistent redistribution of Mulliken charge modification was used to explain different activities of DNAzymes. The substitution of 2'-deoxyadenosine with cdA in the catalytic loop decreased the activity of DNAzymes. Inhibition was dependent on the position of cdA and its absolute configuration. The order of activity of DNAzymes was as follows: wt-Dz > ScdA5-Dz ≈ RcdA15-Dz ≈ ScdA15-Dz > RcdA5-Dz. Theoretical studies revealed that the distance between phosphate groups at position 5 in RcdA5-Dz was significantly increased compared to wt-Dz, while the distance between O4 of dT4 and nonbonding oxygen of PO2 attached to 3'O of dG2 was much shorter. The strong inhibitory effect of RcdA5 may result from hampering the flexibility of the catalytic loop (increased rigidity), which is required for the proper positioning of Me2+ and optimal activity.

Reinforcement learning for in silico determination of adsorbate-substrate structures.

Reinforcement learning (RL) methods have helped to define the state of the art in the field of modern artificial intelligence, mostly after the breakthrough involving AlphaGo and the discovery of novel algorithms. In this work, we present a RL method, based on Q-learning, for the structural determination of adsorbate@substrate models in silico, where the minimization of the energy landscape resulting from adsorbate interactions with a substrate is made by actions on states (translations and rotations) chosen from an agent's policy. The proposed RL method is implemented in an early version of the reinforcement learning software for materials design and discovery (RLMaterial), developed in Python3.x. RLMaterial interfaces with deMon2k, DFTB+, ORCA, and Quantum Espresso codes to compute the adsorbate@substrate energies. The RL method was applied for the structural determination of (i) the amino acid glycine and (ii) 2-amino-acetaldehyde, both interacting with a boron nitride (BN) monolayer, (iii) host-guest interactions between phenylboronic acid and β-cyclodextrin and (iv) ammonia on naphthalene. Density functional tight binding calculations were used to build the complex search surfaces with a reasonably low computational cost for systems (i)-(iii) and DFT for system (iv). Artificial neural network and gradient boosting regression techniques were employed to approximate the Q-matrix or Q-table for better decision making (policy) on next actions. Finally, we have developed a transfer-learning protocol within the RL framework that allows learning from one chemical system and transferring the experience to another, as well as from different DFT or DFTB levels.

Biginelli dihydropyrimidines carrying azole rings: Synthesis, computational studies, and evaluation of alpha‐glucosidase inhibitory and antimicrobial activities

In the current study, we designed three novel compounds by merging two valuable nitrogen-containing pharmacophores, namely dihydropyrimidine (DHPM) and azole, within a single molecule. To obtain the target molecules, azole-linked benzaldehydes were initially synthesized via nucleophilic aromatic substitution reaction between 4-fluorobenzaldehyde and pyrazole, imidazole, or 1,2,4-triazole. Afterward, Biginelli reaction was applied to yield azole-carrying DHPMs. Following structural confirmation, the obtained compounds were tested for their alpha (α)-glucosidase inhibitory and antimicrobial activities. According to the biological data, DHPM-P and DHPM-T showed strong inhibition values whereas DHPM-I failed to effectively inhibit the α-glucosidase enzyme. This situation was explained by molecular docking studies of all compounds into the binding site of alpha-glucosidase. The title compounds also presented moderate antibacterial and antifungal activities. Computational methods based on density functional tight binding (DFTB) and density functional theory (DFT) calculations, along with molecular dynamics (MD) simulations were used to analyze the reactive properties of the compounds. A combination of DFTB and DFT calculations was applied to obtain the lowest energy conformations of the molecules. Further computational analysis included calculations of local reactivity descriptors, such as molecular electrostatic potential and average local ionization energy, by applying DFT calculations. DFT calculations were also used to study intramolecular non-covalent interactions. MD simulations were employed to understand how the title molecules behave in water and to obtain their solubility parameters.

Strategic design of a rare trigonal symmetric luminescent covalent organic framework by linker modification

We designed a trigonal symmetric imine-linked covalent organic framework (COF), TFPC-DAB, with control over the angularity of the building units, where a bent C2-symmetric diamine, such as 1,3-diaminobenzene (1,3-DAB or DAB), with an exo-angle of 120° was used instead of those with an exo-angle of 180°, in combination with a C3-symmetric trialdehyde, such as tri(4-formylphenoxy)cyanurate (TFPC). Its synthesis was accomplished by reacting the building units in a mixture of mesitylene/dioxane/6 M acetic acid under solvothermal conditions. The phase purity, thermal stability, and porosity of TFPC-DAB were established by various analytical techniques. Utilizing the Density Functional Tight Binding (DFTB+) simulation and Pawley refinement, the best fit of the small angle x-ray pattern was found to have an AA stacking of TFPC-DAB in the trigonal space group P3 with low refinement parameters. Such smart materials are in huge demand to detect hazardous corrosive chemicals, such as HCl and NH3. The dual features of electron deficient π-acidic triazine moiety and heteroatoms (N/O) from TFPC and electron rich phenyl units from DAB embodied in the framework enhance its luminescent property and thereby make it suitable for solvent-based HCl and NH3 sensing. The detection limits for HCl and NH3 in methanol were found to be 14 and 82 ppb, respectively. The effect of solvent polarity on the sensing studies was observed with much lower detection limits in dioxane: 2.5 and 11 ppb for HCl and NH3, respectively. A detailed theoretical calculation using density functional theory and configurational bias Monte Carlo modules was conducted for understanding interactions between the COF and HCl or NH3 analytes.

Self-Cleaning and Charge Transport Properties of Foils Coated with Acrylic Paint Containing TiO2 Nanoparticles

The study comprehensively investigates the design and performance of self-cleaning surfaces fabricated by coating aluminum foil with an acrylic paint matrix enriched with different content of titanium dioxide (TiO2) nanoparticles. The main goal was to assess the self-cleaning characteristics of the surfaces obtained. This study employs scanning electron microscopy (SEM) to analyze the morphology of TiO2-modified acrylic surfaces, revealing spherical particles. Raman spectroscopy elucidates signatures characterizing TiO2 incorporation within the acrylic matrix, providing comprehensive insights into structural and compositional changes for advanced surface engineering. Alternating current (AC) impedance spectroscopy was used to assess selected charge transport properties of produced self-cleaning surfaces, allowing us to gain valuable insights into the material’s conductivity and its potential impact on photocatalytic performance. The self-cleaning properties of these tiles were tested against three frequently used textile dyes, which are considered to pose a serious environmental threat. Subsequently, improving self-cleaning properties was achieved by plasma treatment, utilizing a continuous plasma arc. The plasma treatment led to enhanced charge separation and surface reactivity, crucial factors in the self-cleaning mechanism. To deepen our comprehension of the reactive properties of dye molecules and their degradation dynamics, we employed a combination of density functional tight binding (DFTB) and density functional theory (DFT) calculations. This investigation lays the foundation for advancing self-cleaning materials with extensive applications, from architectural coatings to environmental remediation technologies.

Investigating corrosion failure in N80 carbon Steel: Experimental and theoretical insights into isonicotinohydrazide derivatives as inhibitors in acidic conditions

This research work is a detailed analysis of the failure mechanisms related to the corrosion of N80 carbon steel (N80-CS) in an acidic environment (15 wt% HCl), commonly encountered in oil and gas industry pipelines. The study investigates the corrosion failure, focusing on the interactions with two isonicotinohydrazide derivatives, namely N'-[(Z)-furan-2-ylmethylidene]pyridine-4-carbohydrazide (FMI) and N'-[(Z)-phenylmethylidene]pyridine-4-carbohydrazide (BIH). A combination of experimental and theoretical methods, including weight loss (WL), electrochemical analysis, Field Emission Scanning Electron Microscopy (FE-SEM), Atomic Force Microscopy (AFM), Density Functional Tight Binding (DFTB) semi-empirical calculations, frontier molecular orbital analyses, Fukui function studies, and molecular dynamics simulations, was utilized to identify the corrosion and corrosion inhibition behavior of N80-CS. Experimental findings demonstrated that the inhibition performance of FMI and BIH increased proportionally with the concentration of these inhibitors, demonstrating inhibition efficiencies of 95 %, and 98 %, respectively. This performance was reflected by the enhancement of polarization resistance and a significant reduction in corrosion current density at optimum concentrations. Additionally, they demonstrated exceptional corrosion protection capabilities over prolonged immersion times (up to 5 days) and only a moderate decrease in efficiency with increasing temperature, highlighting their robustness under varying operating conditions. The adsorption behavior of these inhibitors was observed to be in agreement with the Langmuir adsorption model, suggesting physicochemical interactions occurring at the N80-CS surface, specifically covalent bonding. Theoretical studies from DFT, molecular dynamics, and DFTB strengthened experimental results, confirming strong interactions between the inhibitors’ atoms and the surface. Through the integrative experimental and theoretical approach of this study, a comprehensive understanding of the mechanisms and inhibition performance of these studied compounds was achieved. The findings can serve as an invaluable resource towards the development of more efficient corrosion inhibitors, further contributing to the broader field of corrosion and prevention strategies.