Semiempirical Density Functional Tight Binding Research Articles

Exploring the potential of isonicotinohydrazide derivatives in N80 steel corrosion control: An integrated approach through synthesis, modeling, and experimentation in acidic environments

N80 carbon steel (N80CS) is recognized for its superior mechanical properties and cost-effectiveness. However, its susceptibility to corrosion, particularly in hydrochloric acid (HCl) environments, necessitates the exploration of corrosion inhibitors. This research centers on the evaluation of N′-[(Z)-(4-bromophenyl)methylidene]pyridine-4-carbohydrazide (BBI) and N′-[(1Z)− 1-(4-chlorophenyl)ethylidene]pyridine-4-carbohydrazide (CEI), green organic compounds from the isonicotinohydrazide family, as potential eco-friendly and non-toxic inhibitors for N80CS in a 15 wt% HCl solution. An array of investigative methods, including weight loss measurements, electrochemical impedance spectroscopy (EIS), and potentiodynamic polarization (PDP), were employed to examine the corrosion inhibition performance of these compounds for the N80CS surface in a strong HCl medium. Our experimental findings demonstrated that the inhibitors' efficiency was concentration-dependent, enhancing as concentrations ranged from 10−4 mol/L to 5 × 10−3 mol/L. Notably, BBI's inhibitory efficiency varied between 97.6% and 99.28%, while CEI's ranged from 94.31% to 98.44%. PDP curves elucidated the capability of BBI and CEI to control both anodic and cathodic reactions, thereby classifying them as mixed-type corrosion inhibitors. The improved inhibition efficiency was evidenced by the decrease in double-layer capacitance, supporting the formation of a protective layer that delays the corrosion process. Consistent with the Langmuir adsorption isotherm model, our results suggested these inhibitors involved in both physical and chemical interactions with the iron atoms on the steel surface. This protective formation was further corroborated by scanning electron microscopy (SEM) and atomic force microscopy (AFM) analyses, which highlighted a significant reduction in the surface roughness of N80CS. Supplementing our experimental data, theoretical investigations using Density Functional Theory (DFT) and semi-empirical Density functional tight binding (DFTB) simulations were conducted. They confirmed the advantageous reactivity of BBI and CEI, attributable to their molecular structures, which promote facile adsorption onto the Fe(110) surface through covalent bonding. This research provides valuable insights into developing non-toxic and environmentally benign corrosion inhibitors for N80CS in acidic conditions.

Atom Equivalent Energies for the Rapid Estimation of the Heat of Formation of Explosive Molecules from Density Functional Tight Binding Theory.

Atom equivalent energies have been derived from which the gas-phase heat of formation of explosive molecules can be estimated from fast, semiempirical density functional tight binding total energy calculations. The root-mean-square deviation and maximum deviation of the heats of formation from the experimental values for the set of 45 energetic molecules compiled by Byrd and Rice [ J. Phys. Chem. A, 2006, 110, 1005-1013] are 10.4 and 25.5 kcal/mol, respectively, using 4 atom equivalent energies and 7.4 and 15.0 kcal/mol, respectively, using 7 atom equivalent energies. These errors are around a factor of 2-3 larger than those obtained from density functional theory calculations but are smaller than those obtained from other semiempirical electronic structure methods. Heats of formation calculated with density functional tight binding theory using the 4 and 7 atom equivalent energies, the Byrd and Rice scheme, and the atom pair contribution method for a new set of 531 energetic molecules that contain only carbon, hydrogen, nitrogen, and oxygen are provided.

Charge and Exciton Transfer Simulations Using Machine-Learned Hamiltonians.

Quantum-mechanical simulations of charge and exciton transfer in molecular organic materials are a key method to increase our understanding of organic semiconductors. Our goal is to build an efficient multiscale model to predict charge-transfer mobilities and exciton diffusion constants from nonadiabatic molecular dynamics simulations and Marcus-based Monte Carlo approaches. In this work, we apply machine learning models to simulate charge and exciton propagation in organic semiconductors. We show that kernel ridge regression models can be trained to predict electronic and excitonic couplings from semiempirical density functional tight binding (DFTB) reference data with very good accuracy. In simulations, the models could reproduce hole mobilities along the anthracene crystal axes to within 8.5% of the DFTB reference and 34% of the experimental results with only 1000 training data points. Using these models decreased the cost of exciton transfer simulations by one order of magnitude.

Theoretical Insights into the Structure of the Aminotris(Methylenephosphonic Acid) (ATMP) Anion: A Possible Partner for Conducting Ionic Media

We present a computational characterisation of Aminotris(methylenephosphonic acid) (ATMP) and its potential use as an anionic partner for conductive ionic liquids (ILs). We argue that for an IL to be a good candidate for a conducting medium, two conditions must be fulfilled: (i) the charge must be transported by light carriers; and (ii) the system must maintain a high degree of ionisation. The result trends presented herein show that there are molecular ion combinations that do comply with these two criteria, regardless of the specific system used. ATMP is a symmetric molecule with a total of six protons. In the bulk phase, breaking the symmetry of the fully protonated state and creating singly and doubly charged anions induces proton transfer mechanisms. To demonstrate this, we used molecular dynamics (MD) simulations employing a variable topology approach based on the reasonably reliable semiempirical density functional tight binding (DFTB) evaluation of the atomic forces. We show that, by choosing common and economical starting compounds, we can devise a viable prototype for a highly conductive medium where charge transfer is achieved by proton motion.

Anisotropic Hydrolysis Susceptibility in Deformed Polydimethylsiloxanes.

Chemical reactions involving the polydimethylsiloxane (PDMS) backbone can induce significant network rearrangements and ultimately degrade macro-scale mechanical properties of silicone components. Using two levels of quantum chemical theory, we identify a possible electronic driver for chemical susceptibility in strained PDMS chains and explore the complicated interplay between hydrolytic chain scissioning reactions, mechanical deformations of the backbone, water attack vector, and chain mobility. Density functional theory (DFT) calculations reveal that susceptibility to hydrolysis varies significantly with the vector for water attacks on silicon backbone atoms, which matches strain-induced anisotropic changes in the backbone electronic structure. Efficient semiempirical density functional tight binding (DFTB) calculations are shown to reproduce DFT predictions for select reaction pathways and facilitate more exhaustive explorations of configuration space. We show that concerted strains of the backbone must occur over at least a few monomer units to significantly increase hydrolysis susceptibility. In addition, we observe that sustaining tension across multiple monomer lengths by constraining molecular degrees of freedom further enhances hydrolysis susceptibility, leading to barrierless scission reactions for less substantial backbone deformations than otherwise. We then compute chain scission probabilities as functions of the backbone degrees of freedom, revealing complicated configurational interdependencies that impact the likelihood for hydrolytic degradation. The trends identified in our study suggest simple physical descriptions for the synergistic coupling between local mechanical deformation and environmental moisture in hydrolytic degradation of silicones.

Numerical Optimization of Density Functional Tight Binding Models: Application to Molecules Containing Carbon, Hydrogen, Nitrogen, and Oxygen.

New parametrizations for semiempirical density functional tight binding (DFTB) theory have been developed by the numerical optimization of adjustable parameters to minimize errors in the atomization energy and interatomic forces with respect to ab initio calculated data. Initial guesses for the radial dependences of the Slater-Koster bond integrals and overlap integrals were obtained from minimum basis density functional theory calculations. The radial dependences of the pair potentials and the bond and overlap integrals were represented by simple analytic functions. The adjustable parameters in these functions were optimized by simulated annealing and steepest descent algorithms to minimize the value of an objective function that quantifies the error between the DFTB model and ab initio calculated data. The accuracy and transferability of the resulting DFTB models for the C, H, N, and O system were assessed by comparing the predicted atomization energies and equilibrium molecular geometries of small molecules that were not included in the training data from DFTB to ab initio data. The DFTB models provide accurate predictions of the properties of hydrocarbons and more complex molecules containing C, H, N, and O.

A Monte Carlo Resampling Approach for the Calculation of Hybrid Classical and Quantum Free Energies.

Hybrid free energy methods allow estimation of free energy differences at the quantum mechanics (QM) level with high efficiency by performing sampling at the classical mechanics (MM) level. Various approaches to allow the calculation of QM corrections to classical free energies have been proposed. The single step free energy perturbation approach starts with a classically generated ensemble, a subset of structures of which are postprocessed to obtain QM energies for use with the Zwanzig equation. This gives an estimate of the free energy difference associated with the change from an MM to a QM Hamiltonian. Owing to the poor numerical properties of the Zwanzig equation, however, recent developments have produced alternative methods which aim to provide access to the properties of the true QM ensemble. Here we propose an approach based on the resampling of MM structural ensembles and application of a Monte Carlo acceptance test which in principle, can generate the exact QM ensemble or intermediate ensembles between the MM and QM states. We carry out a detailed comparison against the Zwanzig equation and recently proposed non-Boltzmann methods. As a test system we use a set of small molecule hydration free energies for which hybrid free energy calculations are performed at the semiempirical Density Functional Tight Binding level. Equivalent ensembles at this level of theory have also been generated allowing the reverse QM to MM perturbations to be performed along with a detailed analysis of the results. Additionally, a previously published nucleotide base pair data set simulated at the QM level using ab initio molecular dynamics is also considered. We provide a strong rationale for the use of the Monte Carlo Resampling and non-Boltzmann approaches by showing that configuration space overlaps can be estimated which provide useful diagnostic information regarding the accuracy of these hybrid approaches.