Tight-binding Simulations Research Articles

Implications for electronic structures of S-doped graphene nanoribbons from a DFTB algorithm at atomic scale

Self-consistent charge density functional tight binding simulations were used to provide implications for the effect of S atoms’ doping on geometrical structures and electronic states in armchair graphene nanoribbons with different widths. The geometric configurations, energy, charge density differences, Mulliken charges, and molecular orbitals at HOMO and LUMO energy levels are characterized. Besides the changes of bond length and bond angles, the calculation results indicate that the band structures and bandgaps of the graphene nanoribbons is affected by the nanoribbon width as well as S doping positions, where the ribbons exhibit metallic or semiconductor properties. Doping S atoms result significant changes in the charge density differences and Mulliken charges on the atoms near the doped atom. At the same time, the HOMOs and LUMOs also present differences.

Investigating geometries and electronic states of boron and nitrogen Co-doping graphene nanoribbons from a DFTB algorithm

Self consistent charge-density functional tight binding simulations are used to investigate the effects of doping B and N atoms on structures and electronic states of armchair graphene nanoribbons passivated by H atoms at the ribbon edges. We considered ten different doping configurations of the doping ribbons, which are categorized into two groups based on whether B and N atoms are in the same carbon ring. The geometric configurations, energy, charge density differences, and Mulliken charges are characterized. The co-doping of B and N atoms in the ribbons significantly affects band structures for different doping arrangements. As covalent bonds form between B and C atoms, the Mulliken population on B atoms changes significantly when B and N atoms are located at different positions of the nanoribbons. The electrical information helps us understand how doping can adjust the electronic states of the graphene nanoribbons to meet the various requirements of electronic devices based on these nanoribbons.

Challenges to extracting spatial information about double P dopants in Si from STM images

The design and implementation of dopant-based silicon nanoscale devices rely heavily on knowing precisely the locations of phosphorous dopants in their host crystal. One potential solution combines scanning tunneling microscopy (STM) imaging with atomistic tight-binding simulations to reverse-engineer dopant coordinates. This work shows that such an approach may not be straightforwardly extended to double-dopant systems. We find that the ground (quasi-molecular) state of a pair of coupled phosphorous dopants often cannot be fully explained by the linear combination of single-dopant ground states. Although the contributions from excited single-dopant states are relatively small, they can lead to ambiguity in determining individual dopant positions from a multi-dopant STM image. To overcome that, we exploit knowledge about dopant-pair wave functions and propose a simple yet effective scheme for finding double-dopant positions based on STM images.

Corrosion inhibition performance and adsorption mechanism of new synthesized symmetrical diarylidenacetone-based inhibitor on C38 steel in 15 % HCl medium: Theoretical insight and experimental validation

Despite the engineering potential of using organic substances to protect vulnerable metallic materials from corrosive environments, the interaction mechanisms and adsorption processes that lead to the formation of hybrid materials remain poorly understood. Further research is necessary to elucidate how these organic compounds interact with metallic surfaces and the specific pathways through which they adsorb to form protective layers. Understanding these mechanisms is crucial for developing more effective corrosion-resistant hybrid materials, which could significantly enhance the properties of metallic components and provide excellent electrochemical stability in various industrial applications. This work aims to explore the corrosion performance and interfacial mechanism of two symmetrical diarylidenacetone-based compounds, namely, (1E,4E)-1,5-bis(4-methoxyphenyl) penta-1,4-dien-3-one (MPD) and 2,6-di((E)-benzylidene) cyclohexan-1-one (BZC), in a bid to control the corrosion kinetics of C38 steel in aggressive environment. This assessment integrated experimental, surface, and theoretical explorations. The results of our study revealed the remarkable ability of MPD and BZC molecules to generate a dense, resistant protective film on the C38 steel surface. This protective film acted as a barrier, effectively blocking the penetration of corrosive ions and their interaction with the C38 substrate. The inhibition efficiencies of the investigated products exhibited a consistent rise with increased amounts of additives. The inhibition efficiency reached 95 % for MPD and 90 % for BZC at 10−3 M, as calculated from the fitting Nyquist diagrams. The interaction between the inhibitor and Fe(110) was studied utilizing density functional tight binding (DFTB) and Molecular dynamics simulations (MDS). The results demonstrate the formation of covalent bonds, with the molecules aligning in a parallel orientation of MPD and BZC. This alignment with experimental findings provides strong validation for the efficacy of the inhibitors in corrosion inhibition.

Hot carriers from intra- and interband transitions in gold-silver alloy nanoparticles

Hot electrons and holes generated from the decay of localised surface plasmons in metallic nanoparticles can be harnessed for applications in solar energy conversion and sensing. In this paper, we study the generation of hot carriers in large spherical gold-silver alloy nanoparticles using a recently developed atomistic modelling approach that combines a solution of Maxwell’s equations with large-scale tight-binding simulations. We find that hot-carrier properties depend sensitively on the alloy composition. Specifically, nanoparticles with a large gold fraction produce hot carriers under visible light illumination while nanoparticles with a large silver fraction require higher photon energies to produce hot carriers. Moreover, most hot carriers in nanoparticles with a large gold fraction originate from interband transitions which give rise to energetic holes and ‘cold’ electrons near the Fermi level. Increasing the silver fraction enhances the generation rate of hot carriers from intraband transitions which produce energetic electrons and ‘cold’ holes. These findings demonstrate that alloy composition is a powerful tuning parameter for the design of nanoparticles for applications in solar energy conversion and sensing that require precise control of hot-carrier properties.

Molecular insights into the interactions between PEG carriers and drug molecules from Celastrus hindsii: a multi-scale simulation study

Efficient drug delivery is crucial for the creation of effective pharmaceutical treatments, and polyethylene glycol (PEG) carriers have been emerged as promising candidates for this purpose due to their bio-compatibility, enhancement of drug solubility, and stability. In this study, we utilized molecular simulations to examine the interactions between PEG carriers and selected drug molecules extracted from Celastrus hindsii: Hindsiilactone A, Hindsiiquinoflavan B, Maytenfolone A, and Celasdin B. The simulations provided detailed insights into the binding affinity, stability, and structural properties of these drug molecules when complexed with PEG carriers. A multi-scale approach combining density functional theory (DFT), extended tight-binding (xTB), and molecular dynamics (MD) simulations was conducted to investigate both unbound and bound states of PEG/drug systems. The results from DFT and xTB calculations revealed that the unbound complex has an unfavorable binding free energy, primarily due to negative contributions of delta solvation free energy and entropy. The MD simulations provided more detailed insights into the interactions between PEG and drug molecules in water solutions. By integrating the findings from the multi-scale simulations, a comprehensive picture of the unbound and bound states of PEG and drug systems were obtained. This information is valuable for understanding the molecular mechanisms governing the binding of drugs in PEG-based delivery platforms, and it contributes to the rational design and optimization of these systems.

Adsorption of aminomethylphosphonic acid on pristine graphene and graphene doped with transition metals: A theoretical study

Aminomethylphosphonic acid (AMPA), a glyphosate breakdown product, exhibits environmental persistence, raising concerns. This study investigates AMPA adsorption on pristine and transition metal-doped graphene using quantum theory of atoms in molecules calculations. Results revealed favorable adsorption energies for pristine graphene, significantly enhanced by doping, with Co-doped graphene exhibiting the highest adsorption energy. Interactions were predominantly physisorption, and doping did not significantly alter graphene’s electronic structure. Tight-binding dynamics simulations demonstrated efficient AMPA adsorption on doped graphene, with Co exhibiting the strongest binding affinity. These findings highlight the potential of transition metal-doped graphene as an effective adsorbent for removing AMPA from water sources.

A Multiscale Simulation on Aluminum Ion Implantation-Induced Defects in 4H-SiC MOSFETs

Aluminum (Al) ion implantation is one of the most important technologies in SiC device manufacturing processes due to its ability to produce the p-type doping effect, which is essential to building p–n junctions and blocking high voltages. However, besides the doping effect, defects are also probably induced by the implantation. Here, the impacts of Al ion implantation-induced defects on 4H-SiC MOSFET channel transport behaviors are studied using a multiscale simulation flow, including the molecular dynamics (MD) simulation, density functional theory (DFT) calculation, and tight-binding (TB) model-based quantum transport simulation. The simulation results show that an Al ion can not only replace a Si lattice site to realize the p-doping effect, but it can also replace the C lattice site to induce mid-gap trap levels or become an interstitial to induce the n-doping effect. Moreover, the implantation tends to bring additional point defects to the 4H-SiC body region near the Al ions, which will lead to more complicated coupling effects between them, such as degrading the p-type doping effect by trapping free hole carriers and inducing new trap states at the 4H-SiC bandgap. The quantum transport simulations indicate that these coupling effects will impede local electron transports, compensating for the doping effect and increasing the leakage current of the 4H-SiC MOSFET. In this study, the complicated coupling effects between the implanted Al ions and the implantation-induced point defects are revealed, which provides new references for experiments to increase the accepter activation rate and restrain the defect effect in SiC devices.

Electrical field enhanced CO2 permeation through a carbon molecular sieve membrane: A combined density functional based tight binding and computational fluid dynamics study

An important challenge in membrane technology for gas separation is to simultaneously improve their permeability and selectivity. Often, the increase in one performance leads to the decline of the other. This study presents a solution to that problem by utilizing electrical field coupling to improve CO2 permeation through a nitrile-containing poly (arylene-ether-ketone) (PEK-C(CN)) carbon molecular sieve membrane. Density functional based tight binding simulations of CO2, CH4, and N2 adsorption on PEK-C(CN) monolayer were conducted without and with electric field. The findings revealed that the electric field strength and orientation affected the molecules bond lengths, atomic charges, and bond angles. Investigation of their adsorption energy dominantly favored CO2 adsorption. Analysis of the partial density of states confirmed that adsorption interactions with the membrane were due to CO2 responses to the applied electric field. It additionally proved the electrical stability of PEK-C(CN) membrane. Computational fluid dynamics simulations of gas permeation through PEK-C(CN) membrane were performed without and with electric field. Results indicated an average pore distribution around 0.5 nm. The velocity flow distribution aided locate the interconnected pores, bringing to the fore the dominant transportation paths of gas molecules. It was uncovered that although the application of an electric field significantly improved the membrane gas permeability, it was not necessarily beneficial to its selectivity. −5 V was determined to be the optimum potential for an improvement of CO2 permeability from 57.32 Barrer (no field) to 15924.91 Barrer, while also enhancing the selectivity. This work demonstrates the benefits of the electric field and its promising application in gas separation processes.

Unlocking and optimizing the thermodynamic potential of tetragonal Si and Ge: Strategies and insights from a tight-binding simulation framework for material engineering

This study theoretically explores the effects of external fields and doping on the electronic and thermoelectric properties of tetragonal silicon (T-Si) and tetragonal germanium (T-Ge) structures using a tight-binding model, Green’s function formalism, and the Kubo formula. External parameters modify the positions and intensities of the density of states (DOS) peaks, influencing charge carrier excitation and conductivity trends. Applying bias voltage introduces zero-intensity regions in thermal conductivity due to band gap opening, reducing thermal properties. In contrast, chemical potential and magnetic field significantly enhance thermal properties by increasing intensity and shifting the peak position. T-Ge exhibits higher thermal properties than T-Si across the selected parameter ranges. The findings highlight the potential for optimizing and enhancing the thermoelectric properties of tetragonal structures through external controllable parameters.

Prolonged Exciton Lifetime Is Achieved in Porphyrin Nanoring by Template Engineering: A Nonadiabatic Tight Binding Approach.

Porphyrin nanoring has been attracting immense attention due to its light harvesting capacity and potential applications in optical, catalysis, sensor, and electronic devices. We demonstrate by nonadiabatic quantum dynamics simulations that the photovoltaic efficiency can be enhanced by template engineering. Altering the hexadentate template (T6) with two tridentate templates (2T3) within the porphyrin ring (P6) cavity accelerated the electron transfer twice and suppressed the electron-hole recombination by nearly three times. The atomistic tight-binding simulation rationalized the dynamics by different localizations of charge of the band edge states, changes in nonadiabatic coupling, alteration in quantum coherence, and involvement of diverse electron-phonon vibrational modes. Further 2T3 templates more strongly hold the P6 ring than T6, reducing the structural fluctuation. As a result, the nonadiabatic coupling becomes weaker and suppresses the carrier recombination. Current atomistic simulation presents a template engineering strategy to enhance the exciton lifetime along with ultrafast charge separation, crucial factors for photovoltaic applications.

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.

Surface Depassivation via B-O Dative Bonds Affects the Friction Performance of B-Doped Carbon Coatings.

Boron doping of diamond-like carbon coatings has multiple effects on their tribological properties. While boron typically reduces wear in cutting applications, some B-doped coatings show poor tribological performance compared with undoped films. This is the case of the tribological tests presented in this work in which an alumina ball is placed in frictional contact with different undoped and B-doped amorphous carbon coatings in humid air. With B-doped coatings, a higher friction coefficient at a steady state with respect to their undoped counterparts was observed. Estimates of the average contact shear stress based on experimental friction coefficients, surface topographies, and Persson's contact theory suggest that the increased friction is compatible with the formation of a sparse network of interfacial ether bonds leading to a mild cold-welding friction regime, as documented in the literature. Tight binding and density functional theory simulations were performed to investigate the chemical effect of B-doping on the interfacial properties of the carbon coatings. The results reveal that OH groups that normally passivate carbon surfaces in humid environments can be activated by boron and form B-O dative bonds across the tribological interfaces, leading to a mild cold-welding friction regime. Simulations performed on different tribological pairs suggest that this mechanism could be valid for B-doped carbon surfaces in contact with a variety of materials. In general, this study highlights the impact that subtle modifications in surface and interface chemistry caused by the presence of impurities can have on macroscopic properties, such as friction and wear.

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.

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.

Interfacial properties of a ZnO/PTFE composite from density functional tight-binding simulations.

Metal-oxide-reinforced plastic nanocomposites are widely used in high-tech industries, but the reinforcement mechanism of the metal oxide is not fully understood. Here we investigate the interfacial properties of a zinc-oxide-reinforced amorphous polytetrafluoroethylene (a-PTFE) composite as a prototype for such composites using superlattice modeling and density functional tight-binding molecular dynamics simulations. To study the ZnO/a-PTFE composites, the superlattice supercells are built using a ZnO (112̄0) surface supercell and a-PTFE layer with an experimental density of 1.8 g cm-3 and various thicknesses. Our calculations demonstrate that the binding energy between ZnO and a-PTFE is negative, indicating their attractive binding, and electron accumulation occurs in the middle space between ZnO and a-PTFE, as well as around ZnO, evidencing that the newly formed interfacial chemical bonds are partially covalent. We further reveal that the tensile stress and elastic moduli of the ZnO/a-PTFE superlattice increases with increasing ZnO fraction, with values placed between those of ZnO and a-PTFE, which confirms the enhancement of the mechanical strength of the composites by incorporating ZnO into the a-PTFE matrix. This work provides a design guideline for developing high-performance metal-oxide-reinforced plastic composites.

Size effects on atomic collapse in the dice lattice.

We study the role of size effects on atomic collapse of charged impurity in the flat band system. The tight-binding simulations are made for the dice lattice with circular quantum dot shapes. It is shown that the mixing of in-gap edge states with bound states in impurity potential leads to increasing the critical charge value. This effect, together with enhancement of gap due to spatial quantization, makes it more difficult to observe the dive-into-continuum phenomenon in small quantum dots. At the same time, we show that if in-gap states are filled, the resonant tunneling to bound state in the impurity potential might occur at much smaller charge, which demonstrates non-monotonous dependence with the size of sample lattice. In addition, we study the possibility of creating supercritical localized potential well on different sublattices, and show that it is possible only on rim sites, but not on hub site. The predicted effects are expected to naturally occur in artificial flat band lattices.

Investigating the effect of electrostatic field on electronic structures of C58N2 molecules from SCC-DFTB simulations

Self-consistent charge density functional tight-binding simulations are performed to investigate the effect of externally electrostatic field on nitrogen-doped fullerene C58N2 molecules. Based on the obtained geometric structures of twenty-three C58N2 configurations, electric field is applied to six selected configurations. We analyze the effects of the direction and strength of the electric field on the HOMO and LUMO energy levels, chemical potential, energy gap, dipole moment, Mulliken populations on atoms, and the variations of molecular orbitals at HOMO and LUMO energy levels of these configurations. The calculation results show that the electric field can change them. The effects of the electric field on the Mulliken charge distribution on the atoms in each configuration present complex patterns, and changing electric field’s direction and strength significantly affect the molecular orbitals. Here, variation of electric field direction can change the phase of molecular orbitals of the configuration having relatively high energy, and the change in the strength of the electric field has a more pronounced effect on the electron distribution at the LUMO levels.

Multifidelity Machine Learning for Molecular Excitation Energies.

The accurate but fast calculation of molecular excited states is still a very challenging topic. For many applications, detailed knowledge of the energy funnel in larger molecular aggregates is of key importance, requiring highly accurate excitation energies. To this end, machine learning techniques can be a very useful tool, though the cost of generating highly accurate training data sets still remains a severe challenge. To overcome this hurdle, this work proposes the use of multifidelity machine learning where very little training data from high accuracies is combined with cheaper and less accurate data to achieve the accuracy of the costlier level. In the present study, the approach is employed to predict vertical excitation energies to the first excited state for three molecules of increasing size, namely, benzene, naphthalene, and anthracene. The energies are trained and tested for conformations stemming from classical molecular dynamics and density functional based tight-binding simulations. It can be shown that the multifidelity machine learning model can achieve the same accuracy as a machine learning model built only on high-cost training data while expending a much lower computational effort to generate the data. The numerical gain observed in these benchmark test calculations was over a factor of 30 but certainly can be much higher for high-accuracy data.