Computational Insights Research Articles

Computational insight on K2AuBiX6 (X = F, Cl, Br, I) double perovskites to comprehensively investigate mechanical, optoelectronic, and thermoelectric features for green energy applications

In this article, we investigated the structural, elastic, electronic, optical, and thermoelectriccharacteristics of K2AuBiX6 (X = F, Cl, Br, and I) using density functional theory (DFT). To verify the stability of the cubic structure tolerance, octahedral factors, and formation energy have been determined. The mechanical stability has been governed by Born stability criteria. These parameters ensure its strength, ductility, brittleness, and anisotropy. The bandgaps of K2AuBiF6, K2AuBiCl6, K2AuBiBr6, and K2AuBiI6 have been determined using the TB-mBJ potential. The calculated values of energy band gaps are 2.88, 2.02, 1.38, and 0.95 eV, respectively. These materials exhibit a broad absorption in visible regions, a refractive index range of around 1–3, and low light scattering, which makes them ideal for optoelectronic applications. In addition, the figure of merit (ZT) values for these compounds at room temperature are 0.76, 0.78, 0.77, and 0.80, ensuring their suitability for use in thermal devices.

Computational, molecular docking and spectroscopic insights of drug–drug interaction between Ibuprofen and Paracetamol

The combination of existing drugs or drug–drug interaction enthralls researcher because of their potential applications in multiple diseases and better efficacy. The present work is undertaken to study the interaction between two drugs, Ibuprofen and Paracetamol, using Density Functional Theory and spectroscopic techniques (Infrared and Raman spectroscopy). The molecular modeling of the two drugs indicates their interaction through intermolecular hydrogen bonds (O34-H53-O2 and (O1-H33-O34), which is observed in Natural Bond Orbital and atoms in molecules analysis of the compound (Ibuprofen + Paracetamol). The experimental Raman, Surface Enhanced Raman Spectroscopy and Infrared spectra of the physical mixture (Ibuprofen + Paracetamol) are found close to their computed wavenumbers. The interacting state, that is, Ibuprofen + Paracetamol is optimized using B3LYP/6-31G ++ (d, p) model under density functional theory framework and different computed quantum chemical parameters such as, dipole moment, ionization energy, electron affinity, electrophilicity index, chemical potential, hardness and the Highest Occupied and Lowest Unoccupied Molecular Orbital energies and energy gaps are calculated and compared to the monomer state of the drugs. The lowering of energy gap and increased in dipole moment of combined drug molecules show potency as an effective hybrid drug. The molecular docking study of the combined drug molecule against the 4PH9 receptor shows a better binding affinity with its residues through hydrogen bonding and hydrophobic interaction.

Computational insights into inhibiting EphA2: Integrating structure-based virtual screening, docking, and molecular dynamics simulations for small molecule discovery.

Elevated expression and dysfunction of ephrin type A receptor-2 (EphA2) have been implicated in the initiation and progression of cancer, metastasis, and unfavorable clinical outcomes. A promising strategy to counteract this dysregulation involves the development of small-molecule inhibitors that target EphA2. Our study focuses on this objective. To initiate Structure-Based Virtual Screening (SBVS), we leveraged an advanced online platform, the Mcule database, which houses an extensive collection of millions of chemical compounds. Using drug similarity filters, we efficiently identified ten thousand potential hits. By further refining the selection through toxicity profiling, we prudently narrowed down the candidates to a more manageable set of 100 molecules. Using the Mcule Single Click, DockThor, and SwissDock tools, we conducted multi-scoring docking assessments of thirty-seven compounds that satisfied the ADME standards. A comprehensive evaluation of Gibbs binding free energy terms, as derived from these docking tools, facilitated the identification of top-ranking docking hits. Remarkably, among the known inhibitors, dasatinib displayed the most robust binding to EphA2 with an average ΔG of -9.0 kcal/mol. Intriguingly, alternatives have emerged in recent years. Notably, small molecules such as Mcule-1579910267 (ΔG: -9.3 kcal/mol), Mcule-1893218381 (ΔG: -9.2 kcal/mol), Mcule-3981378344 (ΔG: -9.3 kcal/mol), and Mcule-8617639093 (ΔG: -9.1 kcal/mol) exhibited a notably strong binding affinity to EphA2, rivaling dasatinib. Subsequently, the four leading ligands along with dasatinib were selected for the MD simulations. Our rigorous analyses during the MD simulation phase encompassing RMSD, RMSF, SASA, ΔGsolv, and Rg underscored the favorable stability of Mcule-8617639093. This compelling evidence ultimately signifies the potential for selective EphA2 inhibition.

Synthesis of dihydrocarvone over dendritic ZSM-5 Zeolite: A comprehensive study of experimental, kinetics, and computational insights

This study explores the isomerization of limonene-1,2-epoxide (LE) from kinetic and mechanistic viewpoints, using a dendritic ZSM-5 zeolite (d-ZSM-5) as a highly selective catalyst for the formation of dihydrocarvone (DHC) in the form of diastereoisomers (cis + trans). Ethyl acetate, a green solvent, was used at mild reaction temperatures (50–––70 °C). DHC, which can also be extracted from caraway oil, is widely used as an intermediate for epoxylactone production and as a constituent in flavors and perfumes. Kinetic modeling of LE isomerization was performed using a reaction network with eight parallel reactions and the corresponding rate equations, derived from the assumption of the rate-limiting surface reactions. The large standard errors in the statistical results of some kinetic parameters of the initial data fitting suggested that three of those reactions can be neglected to describe the kinetic model more accurately. This refinement resulted in standard errors in the kinetic parameters lower than ca. 11 %, confirming the statistical reliability of the modified kinetic model. Activation energies of 41.1 and 162 kJ/mol were estimated for the formation of cis-DHC and trans-DHC, respectively. Density Functional Theory (DFT) calculations revealed the preferred pathway for both cis and trans-LE conversion to DHC and carveol. The rate-determining step, carbocation formation (ΔEact = 234 kJ/mol), precedes near-instantaneous dihydrocarvone formation under the studied conditions.

Unveiling the optoelectronic features and physical stability of novel Cs2HgPdI6: Computational insights

In recent years, researchers have been devoted to search for novel stable halide perovskite materials with outstanding photovoltaic performance. Herein, through density functional theory (DFT) calculations, we uncover for the first time the crystal stability, structural parameters, optoelectronic features, and photovolatic performance of Cs2HgPdI6. The Jahn−Teller-distorted Cs2HgPdI6 is detected by its structural feature. The stability of novel Cs2HgPdI6 is completely ensured by means of the DFT calculations. Accurate electronic structure calculations show that Cs2HgPdI6 exhibits an appropriate fundamental gap (1.278 eV). This band gap is mainly determined by the interaction between the I-5p and Pd-4d orbitals. Additionally, Cs2HgPdI6 has good carrier mobility and an ultra-low exciton binding energy. Meanwhile, it also exhibits relatively weak anisotropic optical properties and strong visible-light absorption. The large theoretical conversion efficiency of 31.7 % is illustrated for Cs2HgPdI6. Overall, our research highlights the great potential of this novel compound for photovoltaic applications.

Synthesis of Highly Substituted Oxaboroles from Oxaboranes via a Selective Petasis Borono-Mannich Reaction.

We present a novel and efficient method for the synthesis of highly substituted non-benzofused oxaboroles. Reactions of oxaboranes, morpholine, and salicylaldehyde in toluene heated to 85 °C for 4 h produce the corresponding oxaborole products in yields up to 93%. The process is effective across a diverse substrate scope and can be scaled to produce gram quantities of densely functionalized oxaboroles in excellent yield. Exclusive aryl transfer over vinyl transfer is observed. Computational insights further elucidate the inherent selectivity of this process.

Computational insights into the deoxygenation reaction of biomass-derived phenolic compounds over Ni2P (001) catalysts

This research sets the scene for understanding the interaction of phenolic molecules (i.e., phenol, o-cresol, m-cresol, and p-cresol) with Ni2P catalyst surface and how their hydrodeoxygenation reaction progresses over the surface. The hydrodeoxygenation process is responsible for removing the oxygen content from the pyrolysis oil compounds, particularly through direct deoxygenation route. Ni2P, which is one of the most common transition metal phosphides, serves as a candidate surface of this study. Two main investigations were carried out including the optimization of (1) adsorption configuration of the phenolic compounds and the (2) net charge distribution between the surface and the adsorbate. According to the adsorption energy studies, the horizontal configuration of the o-cresol molecule on the Ni2P(001) hollow site presented the most optimized and stable configuration with the least negative adsorption energy (−0.26 eV), resulting in the most negative net charge density at −0.286 |e|, as determined by the Bader charge analysis. Upon adsorption on Ni2P(001) surface, o-cresol undergoes significant charge redistribution, where the oxygen atom (-OH group) exhibits a net charge of −1.3443 |e|, indicating electron transfer to the surface. The catalytic pathway proceeded with deoxygenation followed by ring hydrogenation to produce toluene (C7H8), such that C–O bond dissociation has a reaction energy of −0.715 eV, while C–H bond formation step had a reaction energy of 0.011 eV.

Experimental and computational insights of Albizia amara phytoconstituents targeting anthranilate phosphoribosyltransferase from Malassezia globosa

The fungus Malassezia globosa is often responsible for superficial mycoses posing significant treatment challenges because of the unfavourable side effects of available antifungal drugs. To reduce potential hazards to the host and overcome these hurdles, new therapeutic medicines must be developed that selectively target enzymes unique to the pathogen. This study focuses on the enzyme anthranilate phosphoribosyltransferase (AnPRT), which is vital to M. globosa's tryptophan production pathway. To learn more about the function of the AnPRT enzyme, we modeled, validated, and simulated its structure. Moreover, many bioactive components were found in different extracts from the plant Albizia amara after phytochemical screening. Interestingly, at doses ranging from 500 to 2000 µg/ml, the chloroform extract showed significant antifungal activity, with inhibition zones measured between 11.0 ± 0.0 and 25.6 ± 0.6 mm. According to molecular docking analyses, the compounds from the active extract, particularly 2-tert-Butyl-4-isopropyl-5-methylphenol, interacted with the AnPRT enzyme's critical residues, ARG 205 and PHE 214, with an effective binding energy of -4.9 kcal/mol. The extract's revealed component satisfies the requirements for drug-likeness and shows promise as a strong antifungal agent against infections caused by M. globosa. These findings imply that using plant-derived chemicals to target the AnPRT enzyme is a viable path for the creation of innovative antifungal treatments.

Computational insights into the aggregation mechanism and amyloidogenic core of aortic amyloid medin polypeptide

Medin amyloid, prevalent in the vessel walls of 97 % of individuals over 50, contributes to arterial stiffening and cerebrovascular dysfunction, yet our understanding of its aggregation mechanism remains limited. Dividing the full-length 50-amino-acid medin peptide into five 10-residue segments, we conducted individual investigations on each segment's self-assembly dynamics via microsecond-timescale atomistic discrete molecular dynamics (DMD) simulations. Our findings showed that medin1–10 and medin11–20 segments predominantly existed as isolated unstructured monomers, unable to form stable oligomers. Medin31–40 exhibited moderate aggregation, forming dynamic β-sheet oligomers with frequent association and dissociation. Conversely, medin21–30 and medin41–50 segments demonstrated significant self-assembly capability, readily forming stable β-sheet-rich oligomers. Residue pairwise contact frequency analysis highlighted the critical roles of residues 22–26 and 43–49 in driving the self-assembly of medin21–30 and medin41–50, acting as the β-sheet core and facilitating β-strand formation in other regions within medin monomers, expecting to extend to oligomers and fibrils. Regions containing residues 22–26 and 43–49, with substantial self-assembly abilities and assistance in β-sheet formation, represent crucial targets for amyloid inhibitor drug design against aortic medial amyloidosis (AMA). In summary, our study not only offers deep insights into the mechanism of medin amyloid formation but also provides crucial theoretical and practical guidance for future treatments of AMA.

Computational insights into zinc silicate MOF structures: topological modeling, structural characterization and chemical predictions

Metal-organic frameworks (MOFs) play a pivotal role in modern material science, offering unique properties such as flexibility, substantial pore space, distinctive structure, and large surface area. Recently, zinc-based MOFs have attracted significant attention, particularly in the biomedical arena, owing to their versatile applications in drug delivery, biosensing, and cancer imaging. However, there remains a crucial need to explore and understand the structural properties of zinc silicate-based MOFs to fully exploit their potential in various applications. The objective of this study is to address this need by employing topological modeling techniques to characterize zinc silicate networks. Utilizing connection number concept of chemical graph theory and novel AL molecular descriptors, we aim to investigate the structural intricacies of these MOFs. More precisely, zinc silicate-based MOF networks are topologically modeled via novel AL topological indices, and derived mathematical closed form formulae for them. By comparing experimental and calculated values and constructing linear regression models, the predictive capabilities of the proposed descriptors are evaluated. Specifically, the performance of derived topological indices against the physico-chemical properties of octane isomers is assessed, which provide valuable insights into their predictive potential. The findings of this study demonstrated the potential of novel AL indices in predicting a wide range of important physico-chemical properties, further enhancing their practicality in materials science and beyond.

Ligand Controls Excited Charge Carrier Dynamics in Metal-Rich CdSe Quantum Dots: Computational Insights.

Small metal-rich semiconducting quantum dots (QDs) are promising for solid-state lighting and single-photon emission due to their highly tunable yet narrow emission line widths. Nonetheless, the anionic ligands commonly employed to passivate these QDs exert a substantial influence on the optoelectronic characteristics, primarily owing to strong electron-phonon interactions. In this work, we combine time-domain density functional theory and nonadiabatic molecular dynamics to investigate the excited charge carrier dynamics of Cd28Se17X22 QDs (X = HCOO-, OH-, Cl-, and SH-) at ambient conditions. These chemically distinct but regularly used molecular groups influence the dynamic surface-ligand interfacial interactions in Cd-rich QDs, drastically modifying their vibrational characteristics. The strong electron-phonon coupling leads to substantial transient variations at the band edge states. The strength of these interactions closely depends on the physicochemical characteristics of passivating ligands. Consequently, the ligands largely control the nonradiative recombination rates and emission characteristics in these QDs. Our simulations indicate that Cd28Se17(OH)22 has the fastest nonradiative recombination rate due to the strongest electron-phonon interactions. Conversely, QDs passivated with thiolate or chloride exhibit considerably longer carrier lifetimes and suppressed nonradiative processes. The ligand-controlled electron-phonon interactions further give rise to the broadest and narrowest intrinsic optical line widths for OH and Cl-passivated single QDs, respectively. Obtained computational insights lay the groundwork for designing appropriate passivating ligands on metal-rich QDs, making them suitable for a wide range of applications, from blue LEDs to quantum emitters.

Silver/Segphos‐Catalyzed Asymmetric 1,3‐Dipolar Cycloaddition for the Enantioselective Synthesis of Pyrrolidine Spirooxindoles

Enantioselective synthesis of chiral heterocyclic derivatives is an important and challenging topic in the field of synthetic chemistry. In this work, a silver‐catalyzed asymmetric 1,3‐dipolar cycloaddition of glycine iminoesters with 3‐isopropylidene‐2‐oxindoles was developed. The DTBM‐Segphos‐induced spirooxindole cycloaddition reaction was used to synthesize a range of stereodivergent alkyl‐substituted 3‐methylene‐2‐oxindoles, achieving excellent enantioselectivities (up to 99% ee), good diastereoselectivities (up to 20:1 dr), and high yields under mild reaction conditions. Computational insights from DFT calculations indicate that the Michael addition step is crucial in determining the reaction rate and enantioselectivity.

Computational insights into the structural, thermodynamic and transport properties of CaF2-MgF2 binary fluoride system at high temperatures

The structural, thermodynamic and transport properties of the CaF2-MgF2 molten salt system were investigated with ab initio molecular dynamics (AIMD), system-specific neural network interatomic potentials (NNIPs) and universal PreFerred Potentials (PFP). We trained an NNIP model using AIMD data as input and used this potential to efficiently simulate the interactions within a large supercell in a temperature range of 1273–1773 K. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code was employed to validate our trained NNIP model. The Matlantis software with universal PFP is also presented to prove its feasibility for MD calculations and can be considered as a useful alternative simulation tool for higher-order systems where existing potentials are not readily available. We calculated structural and thermodynamic properties including radial distribution function (RDF), angular distribution function (ADF), specific heat capacity, ionic self-diffusivity, and viscosity. Our results indicate that the system exhibited a high degree of structural disorder, with the Ca, Mg, and F ions forming a liquid solution. Using PFP, the positions of the first peak in RDFs for Ca-F and Mg-F pairs are only slightly left-shifted (<0.05 Å), and the estimated viscosity of the melt decreases from 4.613 mPa·s to 1.846 mPa·s with an increase in temperature from 1273 K to 1773 K, in agreement with the NNIP trained specifically for CaF2-MgF2. Our results provide valuable insights into the properties of the CaF2-MgF2 system at high temperatures and serve as predictive models for the development of new electrolytes that could be used for silicon epitaxy by adding silica.

Spectroscopic and nonlinear optical investigations of biscinnamyl-sulfone derivatives: Computational and experimental insights

Novel geometrically asymmetric biscinnamyl-sulfone compounds (6a-c) with donor-π-conjugated spacer-acceptor functionality were successfully synthesized. This was achieved by coupling cinnamaldehyde precursors with 3,3′-diaminodiphenyl sulfone in dry organic solvents, resulting in high yields. Several spectroscopic techniques were employed to identify the derivatives. The absorption spectra of these compounds exhibited broad bands that spanned up to 120 nm, which can be attributed to their extended conjugation systems. In order to explore the electronic transitions of these materials, Time-Dependent Density-Functional Theory (TD-DFT) with EIFPCM solvation mode was utilized. We computationally investigated the static nonlinear optical (NLO) parameters, including dipole moments (μ), polarizability (α), anisotropic polarizability (Δα), first-order hyperpolarization (β), and second-order hyperpolarization (γ). Although the new structures possess different functional groups, they displayed similar electronic potentials when their molecular electrostatic potentials were plotted. These potentials are crucial in stabilizing the molecules in crystal systems through noncovalent forces such as C-H⋯π stacking and hydrogen bonding. They also provide insights into the electronic assessments and energetics of these individual forces. By estimating the frontier orbitals, we gained an understanding of the intramolecular charge transfer in the compounds. Energy gap values were determined using the orbitals of density of states method and experimentally via the Tauc method. The computational and experimental results were in good agreement. Lastly, we examined the influence of different protic and aprotic solvents on the absorption bands of compound 6b, as an example. This compound showed a significant bathochromic shift of 41 nm upon changing the solvent from acetic acid to dimethyl sulfoxide.

Computational Insights for Electrocatalytic Synthesis of Glycine

Computational Insights for Electrocatalytic Synthesis of Glycine

Computational insights from the thermal spike model into mesoporous silica behavior during swift heavy ion irradiation

Mesoporous silica materials are pivotal in various scientific domains due to their unique properties and versatile applications. However, understanding their response to irradiation, particularly from Swift Heavy Ions (SHI), remains limited. We address this gap by investigating experimental mesoporous silica behavior under 12 MeV Carbon and 92 MeV Xenon bombardment using the Three-Dimensional Thermal Spike Model (3DTS) simulation. Our computational simulations reveal localized heating effects and provide mechanistic insights into experimental observations, shedding light on pore closure and different observed damage patterns. This study is the first application of this model to porous silica and deepens our knowledge of the mechanism of structural evolution under ion bombardment.

Identifying key genes against rutin on human colorectal cancer cells via ROS pathway by integrated bioinformatic analysis and experimental validation

Colorectal cancer (CRC) poses a significant global health challenge, characterized by substantial prevalence variations across regions. This study delves into the therapeutic potential of rutin, a polyphenol abundant in fruits, for treating CRC. The primary objectives encompass identifying molecular targets and pathways influenced by rutin through an integrated approach combining bioinformatic analysis and experimental validation. Employing Gene Set Enrichment Analysis (GSEA), the study focused on identifying potential differentially expressed genes (DEGs) associated with CRC, specifically those involved in regulating reactive oxygen species, metabolic reprogramming, cell cycle regulation, and apoptosis. Utilizing diverse databases such as GEO2R, CTD, and Gene Cards, the investigation revealed a set of 16 targets. A pharmacological network analysis was subsequently conducted using STITCH and Cytoscape, pinpointing six highly upregulated genes within the rutin network, including TP53, PCNA, CDK4, CCNEB1, CDKN1A, and LDHA. Gene Ontology (GO) analysis predicted functional categories, shedding light on rutin's potential impact on antioxidant properties. KEGG pathway analysis enriched crucial pathways like metabolic and ROS signaling pathways, HIF1a, and mTOR signaling. Diagnostic assessments were performed using UALCAN and GEPIA databases, evaluating mRNA expression levels and overall survival for the identified targets. Molecular docking studies confirmed robust binding associations between rutin and biomolecules such as TP53, PCNA, CDK4, CCNEB1, CDKN1A, and LDHA. Experimental validation included inhibiting colorectal cell HT-29 growth and promoting cell growth with NAC through MTT assay. Flow cytometric analysis also observed rutin-induced G1 phase arrest and cell death in HT-29 cells. RT-PCR demonstrated reduced expression levels of target biomolecules in HT-29 cells treated with rutin. This comprehensive study underscores rutin's potential as a promising therapeutic avenue for CRC, combining computational insights with robust experimental evidence to provide a holistic understanding of its efficacy.

A computational insight to an old concept: The Mills–Nixon effect

The Mills-Nixon (MN) effect in trisannelated benzenes (1–10) is analyzed by Wiberg bond order (WBO), bond lengths alteration (ΔBL), Nucleus Independent Chemical (NICS), Harmonic Oscillator Model of Aromaticity (HOMA), and Localized orbital locator (LOL) analyses in B3LYP/6–311++G (d,p) level of theory. Coulomb repulsion, antiaromatic instability, angle strain and ring strain were the significant factors in the MN effect creation in the studied structures. The obtained results showed that the aromaticity is decreased in the benzene ring is in the 8 > 9 > 3 > 1 > 7 > 2 > 6 > 5 > 10 > 4 order and the strongest MN effect is seen in structure 4.

Computational insights into popsilicene as a new planar silicon allotrope composed of 5–8–5 rings

Silicon-based two-dimensional (2D) materials have garnered significant attention due to their unique properties and potential applications in electronics, optoelectronics, and other advanced technologies. Here, we present a comprehensive investigation of a novel silicon allotrope, Popsilicene (Pop-Si), derived from the structure of Popgraphene. Using density functional theory and ab initio molecular dynamics simulations, we explore the thermal stability, mechanical and electronic properties, and optical characteristics of Pop-Si. Our results demonstrate that Pop-Si exhibits good thermal stability at 1000 K. Electronic structure calculations reveal that Pop-Si is metallic, with a high density of states at the Fermi level. Furthermore, our analysis of the optical properties indicates that Pop-Si has pronounced UV–Vis optical activity, making it a promising candidate for optoelectronic devices. Mechanical property assessments show that Pop-Si has Young’s modulus ranging from 10 to 92 GPa and a Poisson’s ratio of 0.95. These results combined suggest its potential for practical applications.

Sustainable Aviation Fuel Molecules from (Hemi)Cellulose: Computational Insights into Synthesis Routes, Fuel Properties, and Process Chemistry Metrics.

Production of sustainable aviation fuels (SAFs) can significantly reduce the aviation industry's carbon footprint. Current pathways that produce SAFs in significant volumes from ethanol and fatty acids can be costly, have a relatively high carbon intensity (CI), and impose sustainability challenges. There is a need for a diversified approach to reduce costs and utilize more sustainable feedstocks effectively. Here, we map out catalytic synthesis routes to convert furanics derived from the (hemi)cellulosic biomass to alkanes and cycloalkanes using automated network generation with RING and semiempirical thermochemistry calculations. We find >100 energy-dense C8-C16 alkane and cycloalkane SAF candidates over 300 synthesis routes; the top three are 2-methyl heptane, ethyl cyclohexane, and propyl cyclohexane, although these are relatively short. The shortest, least endothermic process chemistry involves C-C coupling, oxygen removal, and hydrogen addition, with dehydracyclization of the heterocyclic oxygens in the furan ring being the most endothermic step. The global warming potential due to hydrogen use and byproduct CO2 is typically 0.7-1 kg CO2/kg SAF product; the least CO2 emitting routes entail making larger molecules with fewer ketonization, hydrogenation, and hydrodeoxygenation steps. The large number of SAF candidates highlights the rich potential of furanics as a source of SAF molecules. However, the structural dissimilarity between reactants and target products precludes pathways with fewer than six synthetic steps, thus necessitating intensified processes, integrating multiple reaction steps in multifunctional catalytic reactors.