Tight-binding Density Functional Theory Research Articles

The Impact of Carbon Corrosion Towards Oxygen Reduction Reaction Activity on Atomically Dispersed M-N-C Catalysts

Atomically dispersed Pt group metal free (PGM free) M-N-C catalysts offer a promising pathway towards a clean energy future.1 This class of materials has proven to be a viable substitute for commercial Pt/C to catalyze oxygen reduction reaction (ORR) with similar activity at only a fraction of the raw material cost.2 To gain a wider market adoption, however, M-N-C catalysts need to significantly improve its durability compared to Pt and its alloys in a real-world operating condition. Towards this end, substantial efforts have focused on making more durable M-N-C catalysts while simultaneously maintaining and improving its ORR activity.3,4 As part of the effort to understand the fundamental aspects that control M-N-C catalysts’ durability during ORR condition, we employ a combined approach using first principles density functional theory (DFT) and density functional tight binding theory (DFTB) to identify the impact of carbon corrosion occurring on M-N-C catalyst towards ORR activity. Our starting atomic representation of the ORR active site is the “C10” type local structure composed of FeN4C10 local defect5 embedded in a monolayer graphene support of varying cell size. As carbon corrosion occurs and consequently creating local carbon vacancies surrounding the active site, we then obtain a family of FeN4C11 and FeN4C12 type of local structures. Our DFT calculations of OH binding energy on these corrosion derived structures suggest that the presence of C vacancies and the subsequent H passivation on dangling C introduces elastic structural deformation to various degree that decreases the theoretical ORR limiting potential. This decrease in DFT calculated ORR limiting potential across a family of FeN4C10, FeN4C11, and FeN4C12 local structures can be attributed to a mechanical energy arising from the surface reconstructions. Reference D. A. Cullen et al., Nat Energy, 6, 462–474 (2021).G. Wu, K. L. More, C. M. Johnston, and P. Zelenay, Science, 332, 443–447 (2011).E. F. Holby, G. Wang, and P. Zelenay, ACS Catal., 10, 14527–14539 (2020).T. Patniboon and H. A. Hansen, ACS Catal., 11, 13102–13118 (2021).H. T. Chung et al., Science, 357, 479–484 (2017).

Nonlinear orbital and spin Edelstein effect in centrosymmetric metals

Nonlinear spintronics combines nonlinear dynamics with spintronics, opening up new possibilities beyond linear responses. A recent theoretical work [Xiao et al. Phys. Rev. Lett.130, 166302 (2023)] predicts the nonlinear generation of spin density [nonlinear spin Edelstein effect (NSEE)] in centrosymmetric metals based on symmetry analysis combined with first-principle calculation. This paper focuses on the fundamental role of orbital degrees of freedom for the nonlinear generation in centrosymmetric systems. Using a combination of tight-binding model and density functional theory calculations, we demonstrate that nonlinear orbital density can arise independently of spin–orbit coupling. In contrast, spin density follows through spin–orbit coupling. We further elucidate the microscopic mechanism responsible for this phenomenon, which involves the NSEE induced by electric-field-induced orbital Rashba texture. In addition, we also explore the potential applications of the nonlinear orbital and spin Edelstein effect for magnetic-field-free switching of magnetization.

Band engineering in two-dimensional porphyrin- and phthalocyanine-based covalent organic frameworks: insight from molecular design

Two-dimensional covalent organic frameworks (2D COFs) represent an emerging class of crystalline polymeric networks, characterized by their tunable architectures and porosity, synthetic adaptability, and interesting optical, magnetic, and electrical properties. The incorporation of porphyrin (Por) or phthalocyanine (Pc) core units into 2D COFs provides an ideal platform for exploring the relationship between the COF geometric structure and its electronic properties in the case of tetragonal symmetry. In this work, on the basis of tight-binding models and density functional theory calculations, we describe the generic types of electronic band structures that can arise in tetragonal COFs. Three tetragonal lattice symmetries are examined: the basic square lattice, the Lieb lattice, and the checkerboard lattice. The potential topological characteristics of each lattice are explored. The Por-/Pc-based COFs exhibit characteristic band dispersions that are directly linked to their lattice symmetries and the nature of the frontier molecular orbitals of their building units. We show that the band dispersions in these COFs can be tailored by choosing specific symmetries of the molecular building units and/or by modulating the relative energies of the core and linker units. These strategies can be extended to a wide array of COFs, offering an effective approach to engineering their electronic properties.

Computational modeling of CH4 and CO2 adsorption on monolayer graphenylene: Implications for optoelectronic properties and hydrogen production

Graphenylene (GP) is a two–dimensional carbon allotrope with a hexagonal lattice structure containing periodic pores. The unique arrangement of GP offers potential applications in electronics, optoelectronics, energy storage, and gas separation. Specifically, its advantageous electronic and optical properties, make it a promising candidate for hydrogen production and advanced electronic devices. In this study, we employ a computational chemistry–based modeling approach to investigate the adsorption mechanisms of CH4 and CO2 on monolayer GP, with a specific focus on their effects on optical adsorption and electrical transport properties at room temperature. To simulate the adsorption dynamics as closely as possible to experimental conditions, we utilize the self–consistent charge tight–binding density functional theory (SCC–DFTB). Through semi–classical molecular dynamics (MD) simulations, we observe the formation of H2 molecules from the dissociation of CH4 and the formation of CO + O species from carbon dioxide molecules. This provides insights into the adsorption and dispersion mechanisms of CH4 and CO2 on GP. Furthermore, we explore the impact of molecular adsorption on optical absorption properties. Our results demonstrate that CH4 and CH2 affects drastically the optical adsorption of GP, while CO2 does not significantly affect the optical properties of the two–dimensional material. To analyze electron transport, we employ the open–boundary non–equilibrium Green's function method. By studying the conductivity of GP and graphene under voltage bias up to 300 mV, we gain valuable insights into the electrical transport properties of GP under optical absorption conditions. The findings from our computational modeling approach might contribute to a deeper understanding of the potential applications of GP in hydrogen production and advanced electronic devices.

Modeling the electroluminescence of atomic wires from quantum dynamics simulations.

Static and time-dependent quantum-mechanical approaches have been employed in the literature to characterize the physics of light-emitting molecules and nanostructures. However, the electromagnetic emission induced by an input current has remained beyond the realm of molecular simulations. This is the challenge addressed here with the help of an equation of motion for the density matrix coupled to a photon bath based on a Redfield formulation. This equation is evolved within the framework of the driven-Liouville von Neumann approach, which incorporates open boundaries by introducing an applied bias and a circulating current. The dissipated electromagnetic power can be computed in this context from the time derivative of the energy. This scheme is applied in combination with a self-consistent tight-binding Hamiltonian to investigate the effects of bias and molecular size on the electroluminescence of metallic and semiconducting chains. For the latter, a complex interplay between bias and molecular length is observed: there is an optimal number of atoms that maximizes the emitted power at high voltages but not at low ones. This unanticipated behavior can be understood in terms of the band bending produced along the semiconducting chain, a phenomenon that is captured by the self-consistency of the method. A simple analytical model is proposed that explains the main features revealed by the simulations. The methodology, applied here at a self-consistent tight-binding level but extendable to more sophisticated Hamiltonians such as density functional tight binding and time dependent density functional theory, promises to be helpful for quantifying the power and quantum efficiency of nanoscale electroluminescent devices.

Three distinct conductance states in polycyclic aromatic hydrocarbon derivatives.

Tight-binding model (TBM) and density functional theory (DFT) calculations were employed. Both simulations have demonstrated that the electrical conductance for eight polycyclic aromatic hydrocarbons (PAHs) can be modulated by varying the number of aromatic rings (NAR) within the aromatic derivatives. TBM simulations reveal three distinct conductance states: low, medium and high for the studied PAH derivatives. The three distinct conductance states suggested by TBM are supported by DFT transmission curves, where the low conductance evidenced by T(E) = 0, for benzene, naphthalene, pyrene and anthracene. While azulene and anthanthrene exhibit a medium conductance as T(E) = 1, and tetracene and dibenzocoronene possess a high conductance with T(E) = 2. Low, medium and high values were elucidated according to the energy gap E g and E g gaps are strongly dependent on the NAR in the PAH derivatives. This study also suggests that any PAH molecules are a conductor if E g < 0.20 eV. A linear relationship between the conductance and NAR (G ∝ NAR) was found and conductance follows the order G (benzene, 1 NAR) < G (anthanthrene, 4 NAR) < G (dibenzocoronene, 9 NAR). The proposed study suggests a relevant step towards the practical application of molecular electronics and future device application.

Regioselective On-Surface Synthesis of [3]Triangulene Graphene Nanoribbons.

The integration of low-energy states into bottom-up engineered graphene nanoribbons (GNRs) is a robust strategy for realizing materials with tailored electronic band structure for nanoelectronics. Low-energy zero-modes (ZMs) can be introduced into nanographenes (NGs) by creating an imbalance between the two sublattices of graphene. This phenomenon is exemplified by the family of [n]triangulenes (n ∈ ). Here, we demonstrate the synthesis of [3]triangulene-GNRs, a regioregular one-dimensional (1D) chain of [3]triangulenes linked by five-membered rings. Hybridization between ZMs on adjacent [3]triangulenes leads to the emergence of a narrow band gap, Eg,exp ∼ 0.7 eV, and topological end states that are experimentally verified using scanning tunneling spectroscopy. Tight-binding and first-principles density functional theory calculations within the local density approximation corroborate our experimental observations. Our synthetic design takes advantage of a selective on-surface head-to-tail coupling of monomer building blocks enabling the regioselective synthesis of [3]triangulene-GNRs. Detailed ab initio theory provides insights into the mechanism of on-surface radical polymerization, revealing the pivotal role of Au-C bond formation/breakage in driving selectivity.

Theoretical study of cellobiose conversion by supported metal catalysts

Using density functional theory and metadynamics simulations with density functional tight-binding theory, we study cellobiose hydrolysis and glucose hydrogenation with SiO2-supported Pt and Pd catalysts in hot water, relevant to green cellulose conversion. We found that cellobiose can be hydrolyzed by hydrogen atom adsorbed on metal or proton spilled-over SiO2 to form glucose. Glucose can then be hydrogenated by hydrogen atoms adsorbed at metal/water interface forming sorbitol. The reaction barriers of hydrolysis and hydrogenation at Pt/water interface are lower than at Pd/water interface, which explains an experimental finding that Pt performs better than Pd as a catalyst.

Thermal isomerization rates in retinal analogues using Ab-Initio molecular dynamics.

For a detailed understanding of chemical processes in nature and industry, we need accurate models of chemical reactions in complex environments. While Eyring transition state theory is commonly used for modeling chemical reactions, it is most accurate for small molecules in the gas phase. A wide range of alternative rate theories exist that can better capture reactions involving complex molecules and environmental effects. However, they require that the chemical reaction is sampled by molecular dynamics simulations. This is a formidable challenge since the accessible simulation timescales are many orders of magnitude smaller than typical timescales of chemical reactions. To overcome these limitations, rare event methods involving enhanced molecular dynamics sampling are employed. In this work, thermal isomerization of retinal is studied using tight-binding density functional theory. Results from transition state theory are compared to those obtained from enhanced sampling. Rates obtained from dynamical reweighting using infrequent metadynamics simulations were in close agreement with those from transition state theory. Meanwhile, rates obtained from application of Kramers' rate equation to a sampled free energy profile along a torsional dihedral reaction coordinate were found to be up to three orders of magnitude higher. This discrepancy raises concerns about applying rate methods to one-dimensional reaction coordinates in chemical reactions.

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.

Analytical Modeling of [001] Orientation in Silicon Trigate Rectangular Nanowire Using a Tight-Binding Model

AbstractIn the realm of electronics, the performance of Silicon Trigate Rectangular Nanowires (Si-TRNW) and the structural characteristics of &lt;001&gt; orientation using tight-binding models have been analyzed. The fast algorithm based on the tight-binding model for Trigate Silicon nanowires yielded a remarkable ION/IOFF ratio of 1.49 × 1010 and leakage current (ILeak or IOFF) of 3.7 × 10−17μA. Furthermore, a maximum conduction band energy level (Ecmax) of −0.003 eV and a Subthreshold Slope (SS) of 120 mV has been obtained for a channel length of 15 nm. At an energy level of 3 eV, a high Transmission coefficient, T(ε), of 4 has been attained using the E-k dispersion method. This analysis also involved the calculation of three ∆ valleys pertinent to the channel’s effectiveness in &lt;001&gt; orientation, with proximity nearer to 1 m0. The Schrodinger-Poisson equation has been analyzed with the Ballistic transport along the [001] z-direction in channel potential. A comparative assessment has been also performed between the lateral dimensions of rectangular nanowires with equal energy levels, utilizing both the tight-binding model and Density Functional Theory (DFT) techniques. In some high-frequency applications, a high transmission coefficient is beneficial to maximize the amount of energy or information that gets transmitted. Reducing leakage current would offer a technological pathway for performance improvement of high-frequency applications. The high ON-current (ION) has been obtained through the DFT approach between source and drain terminals is particularly desirable for applications demanding for fast switching speeds and high-performance computing. The strengths of both methods in hybrid approaches is a common strategy to achieve simulations that are both accurate and efficient. Notably, the nanowires subjected to hydrostatic strain, exhibiting enhanced mobility and exceptional electrostatic integrity, emerged as pivotal components for forthcoming technology nodes. This research augments the potential feasibility of strain-based Si nanowires, even at the 3 nm scale, in subsequent technological advancements.

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.

Hydrogen irradiation-driven computational surface chemistry of lithium oxide and hydroxide.

We have investigated, using molecular dynamics, the surface chemistry of hydrogen incident on the amorphous and crystalline lithium oxide and lithium hydroxide surfaces upon being slowed down by a collision cascade and retained in the amorphous surface of either Li2O or LiOH. We looked for the bonding of H to the resident structures in the surface to understand a possible chain of chemical reactions that can lead to surface transformation upon H atom impact. Our findings, using Density-Functional Theory (DFT) trained ReaxFF force field/electronegativity equalization method potentials, stress the importance of inclusion of polarization in the dynamics of a Li-O-H system, which is also illustrated by DFT energy minimization and quantum-classical molecular dynamics using tight binding DFT. The resulting polar-covalent chemistry of the studied systems is complex and very sensitive to the instantaneous positions of all atoms as well as the ratio of concentrations of various resident atoms in the surface.

Functionalized carbophenes as high-capacity versatile gas adsorbents: An ab initio study

This study employs density functional theory (DFT) and density functional tight-binding theory (DFTB) to determine the adsorption properties of carbon dioxide (CO2), methane (CH4), and dihydrogen (H2) in carbophenes functionalized with carboxyl (COOH), amine (NH2), nitro (NO2), and hydroxyl (OH) groups. We demonstrate that carbophenes are promising candidates as adsorbents for these gasses. Carbophenes have larger CO2 and CH4 adsorption energies than other next-generation solid-state capture materials. Yet, the low predicted desorption temperatures mean they can be beneficial as air scrubbers in confined spaces. Functionalized carbophenes have H2 adsorption energies usually observed in metal-containing materials. Further, the predicted desorption temperatures of H2 from carbophenes lie within the DOE Technical Targets for Onboard Hydrogen Storage for Light-Duty Vehicles (DOEHST) operating temperature range. The possibility of tailoring the degree of functionalization in combination with selecting sufficiently open carbophene structures that allow for multiple strong interactions without steric hindrance (crowding) effects, added to the multiplicity of possible functional groups alone or in combination, suggests that these very light materials can be ideal adsorbates for many gases. Tailoring the design to specific adsorption or separation needs would require extensive combinatorial investigations.

Efficient computation of optical excitations in two-dimensional materials with the Xatu code

Here we describe an efficient numerical implementation of the Bethe-Salpeter equation to obtain the excitonic spectrum of semiconductors. This is done on the electronic structure calculated either at the simplest tight-binding level or through density functional theory calculations based on local orbitals. We use a simplified model for the electron-electron interactions which considers atomic orbitals as point-like orbitals and a phenomenological screening. The optical conductivity can then be optionally computed within the Kubo formalism. Our results for paradigmatic two-dimensional materials such as hBN and MoS2, when compared with those of more sophisticated first-principles methods, are excellent and envision a practical use of our implementation beyond the computational limitations of such methods. Program summaryProgram Title: XatuCPC Library link to program files:https://doi.org/10.17632/kj4rt95pvc.1Developer's repository link:https://github.com/alejandrojuria/xatuLicensing provisions: GPLv3Programming language: C++, Fortran, PythonNature of problem: The exciton spectrum is obtained as the solution of the Bethe-Salpeter equation for insulators and semi-conductors. Constructing the equation involves determining the screening of the electrostatic interaction and then determining the matrix elements of the interaction kernel, which are computationally-intensive tasks, specially if one takes a purely ab-initio approach.Solution method: The Bethe-Salpeter equation can be efficiently set up and solved assuming that the basis of the reference electronic structure calculation, obtained either from tight-binding models or density functional theory with actual localized orbitals, corresponds to point-like localized orbitals. This, in addition to using an effective screening instead of computing the dielectric constant, allows to obtain the interaction kernel at very low computational cost and, thereof, the exciton spectrum as well as the light absorption of materials.Additional comments including restrictions and unusual features: The code requires using at least C++11, given that it uses version-specific features. All linear algebra routines have been delegated to the Armadillo library.

Density functional theory and quantum mechanics studies of 2D carbon nanostructures (graphene and graphene oxide) for Lenalidomide anticancer drug delivery

This research was carried out to examine nanomaterials for the delivery of a Lenalidomide (LND) anticancer agent. LND has primarily been used to treat cancer patients. To this point, the drug distribution of LND was evaluated in this study using two typical nanostructure models, graphene (G) and graphene oxide (GOx). To obtain the necessary findings of singular and interacting models, density functional theory (DFT), density functional tight binding theory (DFTB+), Monte Carlo (MC), and Molecular Dynamic (MD) calculations were conducted. For the studied model systems, stabilized structures and associated electronic features were assessed. Formation possibilities for both LND@G and LND@GOx complex models were discovered, and the associated complex interactions were studied using features of the quantum theory of atoms in the molecule (QTAIM). Variations in the levels of frontier molecular orbitals also suggested the interaction of LND with G and GOxstructures. As a result, the obtained results showed that the studied complex models of LND@G and LND@GOx were suitable for carrying out the desired drug delivery processes using acceptable nano-based surfaces as carriers.

Study of the energy spectrum of a few one-dimensional and quasi one-dimensional lattices through tight binding and density functional theory

A graphene nanoribbon (GNR) is a strip of carbon atoms having sp2 hybridization. It has wide application in nanoelectronics and opto-electronics. Usual fields of application are found in field effect transistors, interconnects, logic gates, sensors, energy storage, and photovoltaics. A single unit graphene nanoribbon is a long strip of graphene rings. Such a GNR structure may be seen as two one-dimensional carbon chains that are suitable connected with bonds. We have done tight binding calculations and density functional theory simulation of carbon chains. We study the single bond and double bond one-dimensional carbon chain and the alternate bond (t1-t2), also called a bond order system in one dimension and quasi one-dimensional chain. We find evidence for the emergence of multiple gaps in the energy spectrum of these systems. We have mapped the alternate bond system to the Su–Schrieffer–Heeger model (with a small modification) in one dimension and quasi one dimension. This is the first time such a mapping has been attempted and a comprehensive theoretical and computational study of these chains has been performed.

Dirac cones in bipartite square-octagon lattice: A theoretical approach.

Dirac cones are difficult to achieve in a square lattice with full symmetry. Here, we have theoretically investigated a bipartite tetragonal lattice composed of tetragons and octagons using both Tight-Binding (TB) model and density functional theory (DFT) calculations. The TB model predicts that the system exhibits nodal line semi-metallic properties when the on-site energies of all atoms are identical. When the on-site energies differ, the formation of an elliptical Dirac cone is predicted. Its physical properties (anisotropy, tilting, merging, and emerging) can be regulated by the hopping energies. An exact analytical formula is derived to determine the position of the Dirac point by the TB parameters, and a criterion for the existence of Dirac cones is obtained. The "divide-and-coupling" method is applied to understand the origin of the Dirac cone, which involves dividing the bands into several groups and examining the couplings among inter-groups and intra-groups. Various practical systems computed by DFT methods, e.g., t-BN, t-Si, 4,12,2-graphyne, and t-SiC, are also examined, and they all possess nodal lines or Dirac cones as predicted by the TB model. The results provide theoretical foundation for designing novel Dirac materials with tetragonal symmetry.

Shadow Molecular Dynamics and Atomic Cluster Expansions for Flexible Charge Models.

A shadow molecular dynamics scheme for flexible charge models is presented where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-separated density functional theory. The interatomic potential, including the atomic electronegativities and the charge-independent short-range part of the potential and force terms, is modeled by the linear atomic cluster expansion (ACE), which provides a computationally efficient alternative to many machine learning methods. The shadow molecular dynamics scheme is based on extended Lagrangian (XL) Born-Oppenheimer molecular dynamics (BOMD) [Eur. Phys. J. B 2021, 94, 164]. XL-BOMD provides stable dynamics while avoiding the costly computational overhead associated with solving an all-to-all system of equations, which normally is required to determine the relaxed electronic ground state prior to each force evaluation. To demonstrate the proposed shadow molecular dynamics scheme for flexible charge models using atomic cluster expansion, we emulate the dynamics generated from self-consistent charge density functional tight-binding (SCC-DFTB) theory using a second-order charge equilibration (QEq) model. The charge-independent potentials and electronegativities of the QEq model are trained for a supercell of uranium oxide (UO2) and a molecular system of liquid water. The combined ACE+XL-QEq molecular dynamics simulations are stable over a wide range of temperatures both for the oxide and for the molecular systems and provide a precise sampling of the Born-Oppenheimer potential energy surfaces. Accurate ground Coulomb energies are produced by the ACE-based electronegativity model during an NVE simulation of UO2, predicted to be within 1 meV of those from SCC-DFTB on average during comparable simulations.

Adaptive Peptide Molecule as the Promising Highly-Efficient Gas-Sensor Material: In Silico Study.

Gas sensors are currently employed in various applications in fields such as medicine, ecology, and food processing, and serve as monitoring tools for the protection of human health, safety, and quality of life. Herein, we discuss a promising direction in the research and development of gas sensors based on peptides-biomolecules with high selectivity and sensitivity to various gases. Thanks to the technique developed in this work, which uses a framework based on the density-functional tight-binding theory (DFTB), the most probable adsorption centers were identified and used to describe the interaction of some analyte molecules with peptides. The DFTB method revealed that the physical adsorption of acetone, ammonium, benzene, ethanol, hexane, methanol, toluene, and trinitrotoluene had a binding energy in the range from -0.28 eV to -1.46 eV. It was found that peptides may adapt to the approaching analyte by changing their volume up to a maximum value of approx. 13%, in order to confine electron clouds around the adsorbed molecule. Based on the results obtained, the prospects for using the proposed peptide configurations in gas sensor devices are good.