In this study, the conformational potential energy surfaces of Amylmetacresol, Benzocaine, Dopamine, Betazole, and Betahistine molecules were scanned and analyzed using the neural network architecture ANI-2 × and ANI-1ccx, the force field method OPLS, and density functional theory with the exchange-correlation functional B3LYP and the basis set 6-31G(d). The ANI-1ccx and ANI-2 × methods demonstrated the highest accuracy in predicting torsional energy profiles, effectively capturing the minimum and maximum values of these profiles. Conformational potential energy values calculated by B3LYP and the OPLS force field method differ from those calculated by ANI-1ccx and ANI-2x, which account for non-bonded intramolecular interactions, since the B3LYP functional and OPLS force field weakly consider van der Waals and other intramolecular forces in torsional energy profiles. For a more comprehensive analysis, electronic parameters such as dipole moment, HOMO, and LUMO energies for different torsional angles were calculated at two levels of theory, B3LYP/6-31G(d) and ωB97X/6-31G(d). These calculations confirmed that ANI predictions are more accurate than density functional theory calculations with B3LYP functional and OPLS force field for determining potential energy surfaces. This research successfully addressed the challenges in determining conformational potential energy levels and shows how machine learning and deep neural networks offer a more accurate, cost-effective, and rapid alternative for predicting torsional energy profiles.
The molecularly imprinted polymer (MIP) is useful for measuring the amount of riboflavin (vitamin B2), in various samples using UV/Vis instruments. The practical optimization of the MIP synthesis conditions has a number of drawbacks, like the need to spend money, the need to spend time, the use of the compounds that cause contamination, needing laboratory equipment and tools. Using machine learning (ML) to predict the amount of riboflavin absorbance is a creative solution to overcome the problems and shortcomings of optimizing polymer synthesis conditions. In fact, by using the model without needing real work in the laboratory, the optimum laboratory conditions are determined, and as a result the maximized absorption of the riboflavin is obtained. In this paper, MIP was synthesized for selective extraction of the riboflavin, and UV/Vis spectrophotometry was used to quantitatively measure riboflavin absorbance. Various factors affect the performance of the polymer. The effect of six important factors, including the molar ratio of the template, the molar ratio of monomer, the molar ratio of cross-linker, loading time, stirring rate, and pH, were investigated. Then, using ensemble ML algorithms, like gradient boosting (GB), extra trees (ET), random forest (RF), and Ada boost (Ada) algorithms, an accurate model was created to predict the riboflavin absorption. Also, the mutual information feature selection method was used to determine the important features. The results of using feature selection method was shown that variables such as the molar ratio of the template, the molar ratio of the monomer, and the molar ratio of the cross-linker had a high effect on riboflavin absorbance. The GB and Ada boost algorithms performed better than ET and RF algorithms. After tuning the n-estimator hyper parameter (n-estimator = 300), the GB algorithm was shown an excellent performance in predicting the absorbance of riboflavin and the maximum R2-scoring of the model was obtained at 0.965995, the minimum of the mean absolute error (MAE), and mean square error (MSE) of the model respectively were obtained -0.003711 and -0.000078. Therefore, by using the proposed model, it is possible to predict riboflavin absorbance theoretically, and with high accuracy by changing the inputs of model, and using the model instead of working in the lab saves time, money, chemical compounds, and lab ware.
The molecularly imprinted polymers are artificial polymers that, during the synthesis, create specific sites for a definite purpose. These polymers due to their characteristics such as stability, easy of synthesis, reproducibility, reusability, high accuracy, and selectivity have many applications. However, the variety of the functional monomers, templates, solvents, and synthesis conditions like pH, temperature, the rate of stirring, and time, limit the selectivity of imprinting. The Practical optimization of the synthetic conditions has many drawbacks, including chemical compound usage, equipment requirements, and time costs. The use of machine learning (ML) for the prediction of the imprinting factor (IF), which indicates the quality of imprinting is a very interesting idea to overcome these problems. The ML has many advantages, for example a lack of human error, high accuracy, high repeatability, and prediction of a large amount of data in the minimum time. In this research, ML was used to predict the IF using non-linear regression algorithms, including classification and regression tree, support vector regression, and k-nearest neighbors, and ensemble algorithms, like gradient boosting (GB), random forest, and extra trees. The data sets were obtained practically in the laboratory, and inputs, included pH, the type of the template, the type of the monomer, solvent, the distribution coefficient of the MIP (KMIP), and the distribution coefficient of the non-imprinted polymer (KNIP). The mutual information feature selection method was used to select the important features affecting the IF. The results showed that the GB algorithm had the best performance in predicting the IF, and using this algorithm, the maximum R2 value (R2 = 0.871), and the minimum mean absolute error (MAE = - 0.982), and mean square error were obtained (MSE = - 2.303).
Molecular dynamic behaviors of poly(N,N-diethylacrylamide) (PDEA) as well as its interfacial properties in water were studied measuring the polymer single chain in a dilute concentration regime via molecular dynamics simulation. The investigation of chain length and temperature impacts on the rate of affinity variation of PDEA to water through calculating non-bonded interactions between them showed that the increment of two mentioned items reduced the polymer hydrophilicity in water. The interactional variation altered the PDEA diffusivity in the solution so that the decrement of PDEA tendency to water enhanced the chain movements because of reducing the interfacial friction between the chain and media, particularly at the transition zone. The chains spatial dimensions, conformation and shape were determined as a function of temperature to evaluate the chain hydrodynamic features. A particular order parameter for the PDEA backbone bonds and distribution of their dihedral angles were calculated to consider entropy of the chains with temperatures. The results indicated that PDEA tended to have a rod conformation with less entropy at lower temperatures and chain lengths. Finally, a novel parameter, < Pθφ(T) >, based on the interfacial structure of water was presented to quantitate the relationship between the thermodynamics of PDEA and its structure and hydrophilicity variation with temperature.
Acrylamides , Polymers , Acrylamides/chemistry , Molecular Dynamics Simulation , Polymers/chemistry , Water/chemistry
Effect of functionalization on stability, solubility, and plasmonic features of gold nanoparticle with the general formula of Au18(SR)14 in water solvent has been studied in this work. Thiol functional groups including 1,1-mercapto-ethyl alcohol, s-cysteamine, thioglycolic acid, and beta-mercaptoethanol have been used. Electronic band-gap, excitation energies, dipole moment, and hardness for all gold nanoparticles in water solvent were investigated using the quantum mechanical approach. Intermolecular forces, radial distribution function (RDF), mean square displacement (MSD), and solvation free energy were calculated by using simulation methods. Electronic band-gap, and excitation energy analysis show that surface modification of gold nanoparticles can change their electronic and plasmonic properties. The analysis of dipole moments indicates that ligands affect the nanoparticle's solubility. An increase of hardness and therefore chemical stability can be observed for functionalized nanoparticles compared to the bare structure. Intermolecular energies analyses suggest that structure with 1,1-mercapto ethyl alcohol ligand has the strongest interaction with the solvent. The analysis of RDF diagrams also indicates that the molecule with 1,1-mercapto ethyl alcohol ligand has the sharpest pick. The slope of the linear part of MSD diagrams that is the criterion of solute's lateral diffusion is the highest value for nanoparticle with 1,1-mercapto ethyl alcohol ligand. Furthermore, functionalization also affects solvation free energy contributions. According to obtained data of quantum mechanical calculations and molecular dynamics simulations, it may be concluded that particle with 1,1-mercapto ethyl alcohol is the best ligand for increasing solubility, stability, and plasmonic functions of Au18(SR)14 structures among the examined ones.
Gold , Metal Nanoparticles , Solubility , Solvents , Sulfhydryl Compounds
The dipolar susceptibility of interfacial water and the corresponding interface dielectric constant were calculated from numerical molecular dynamics simulations for neutral and charged states of buckminsterfullerene C60. Dielectric constants in the range 10-22, depending on temperature and solute charge, were found. These values are consistent with recent reports for biological and nanometer-scale interfaces. The hydration water undergoes a structural crossover as a function of the surface charge of the charged fullerene. Its main signatures include the release of dangling O-H bonds pointing toward the solute and the change in the preferential orientations of hydration water from those characterizing hydrophobic to charged substrates. The interface dielectric constant marks the structural transition with a spike showing a Curie-type phenomenology. The computational formalism adopted here provides direct access to interface susceptibility from configurations produced by computer simulations. The required property is the cross-correlation between the radial projection of the dipole moment of the solvation shell with the electrostatic potential of the solvent inside the solute.
Classical molecular dynamics simulations of the hydration thermodynamics, structure, and dynamics of water in hydration shells of charged buckminsterfullerenes are presented in this study. Charging of fullerenes leads to a structural transition in the hydration shell, accompanied by creation of a significant population of dangling O-H bonds pointing toward the solute. In contrast to the well accepted structure-function paradigm, this interfacial structural transition causes nearly no effect on either the dynamics of hydration water or on the solvation thermodynamics. Linear response to the solute charge is maintained despite significant structural changes in the hydration shell, and solvation thermodynamic potentials are nearly insensitive to the altering structure. Only solvation heat capacities, which are higher thermodynamic derivatives of the solvation free energy, indicate some sensitivity to the local hydration structure. We have separated the solvation thermodynamic potentials into direct solute-solvent interactions and restructuring of the hydration shell and analyzed the relative contributions of electrostatic and nonpolar interactions to the solvation thermodynamics.
In this study, molecular dynamics simulations have been used to investigate the behavior of the drug rivastigmine and its carrier so-called poly (n-butyl cyanoacrylate) in the encapsulation process. Polymer modeling, and subsequently the emulsion polymerization model, were applied to analyze drug release in vitro and to justify rivastigmine transport across the blood-brain barrier (BBB) and polymer agglomeration. On the other hand, suitable polymer chain length, encapsulation method, polarity between polymer and drug structure, and finally, pattern of drug released in vitro and in vivo have been investigated to analyze the behavior of drug and polymer accurately. Maximum drug loading was determined based on the modeling of drug encapsulation and comparison of the radius of gyration of polymer (Rg) and distance between center of masses (COMs) of rivastigmine molecules and polymer in equilibrium condition (A°). With the aim of better understanding of drug release, we calculated the Flory-Huggins interaction parameter, diffusion coefficient, and intermolecular interaction energy. The results reveal that more drug molecules remain on the surface of the polymeric structure, with increasing the concentration of rivastigmine molecules from 3 up to 7, but the number of encapsulated drug molecules inside of the polymer remains constant. Also, calculated values of Gibbs free energy indicated that intramolecular interactions of the polymer chain overcome the intermolecular interactions between polymer and drug. Therefore, any extra loading of drug resulted in accumulation on the polymer surface. Graphical abstract Poly (n-butyl cyanoacrylate) containing rivastigmine molecules.
Purpose: Drug delivery has a critical role in the treatment of cancer, in particular, carbon nanotubes for their potential use in various biomedical devices and therapies. From many other materials which could be more biocompatible and biodegradable and which could form single-walled nanotubes, silicon carbide was selected. Methods: To compare two drug delivery systems based on single-walled nanotubes, molecular dynamic simulations were applied and encapsulation behavior of the drug carboplatin was investigated inside the silicon carbide nanotube and the carbon nanotube. Results: Localization of the carboplatin inside the nanotubes indicated that the carboplatin moves throughout the tubes and possesses a greater probability of finding the drug molecule along the nanotubes in the first quarter of the tubes. The energy analysis exhibited the lowest free energy of binding belongs to the encapsulation of the drug carboplatin in the silicon carbide nanotube, about -145 Kcal/mol. Conclusion: The results confirmed that the silicon carbide nanotube is a more suitable model than the carbon nanotube for drug delivery system based on nanotubes as a carrier of platinum-based anticancer drugs.
Based on Wertheim's second order thermodynamic perturbation theory (TPT2), equations of state (EOSs) are presented for the fluid and solid phases of tangent, freely jointed spheres. It is considered that the spheres interact with each other through the Weeks-Chandler-Anderson (WCA) potential. The developed TPT2 EOS is the sum of a monomeric reference term and a perturbation contribution due to bonding. MC NVT simulations are performed to determine the structural properties of the reference system in the reduced temperature range of 0.6 ≤ T* ≤ 4.0 and the packing fraction range of 0.1 ≤ η ≤ 0.72. Mathematical functions are fitted to the simulation results of the reference system and employed in the framework of Wertheim's theory to develop TPT2 EOSs for the fluid and solid phases. The extended EOSs are compared to the MC NPT simulation results of the compressibility factor and internal energy of the fully flexible chain systems. Simulations are performed for the WCA chain system for chain lengths of up to 15 at T* = 1.0, 1.5, 2.0, 3.0. Across all the reduced temperatures, the agreement between the results of the TPT2 EOS and MC simulations is remarkable. Overall Average Absolute Relative Percent Deviation at T* = 1.0 for the compressibility factor in the entire chain lengths we covered is 0.51 and 0.77 for the solid and fluid phases, respectively. Similar features are observed in the case of residual internal energy.
Simple and accurate expressions are presented for the equation of state (EOS) and absolute Helmholtz free energy of a system composed of simple atomic particles interacting through the repulsive Lennard-Jones potential model in the fluid and solid phases. The introduced EOS has 17 and 22 coefficients for fluid and solid phases, respectively, which are regressed to the Monte Carlo (MC) simulation data over the reduced temperature range of 0.6≤T*≤6.0 and the packing fraction range of 0.1 ≤ η ≤ 0.72. The average absolute relative percent deviation in fitting the EOS parameters to the MC data is 0.06 and 0.14 for the fluid and solid phases, respectively. The thermodynamic integration method is used to calculate the free energy using the MC simulation results. The Helmholtz free energy of the ideal gas is employed as the reference state for the fluid phase. For the solid phase, the values of the free energy at the reduced density equivalent to the close-packed of a hard sphere are used as the reference state. To check the validity of the predicted values of the Helmholtz free energy, the Widom particle insertion method and the Einstein crystal technique of Frenkel and Ladd are employed. The results obtained from the MC simulation approaches are well agreed to the EOS results, which show that the proposed model can reliably be utilized in the framework of thermodynamic theories.
Encapsulation of cisplatin anticancer drug into the single walled (10, 0) carbon nanotube and (10, 0) boron-nitride nanotube was investigated by quantum mechanical calculations and Monte Carlo Simulation in aqueous solution. Solvation free energies and complexation free energies of the cisplatin@ carbon nanotube and cisplatin@ boron-nitride nanotube complexes was determined as well as radial distribution functions of entitled compounds. Solvation free energies of cisplatin@ carbon nanotube and cisplatin@ boron-nitride nanotube were -4.128kcalmol(-1) and -2457.124kcalmol(-1) respectively. The results showed that cisplatin@ boron-nitride nanotube was more soluble species in water. In addition electrostatic contribution of the interaction of boron- nitride nanotube complex and solvent was -281.937kcalmol(-1) which really more than Van der Waals and so the electrostatic interactions play a distinctive role in the solvation free energies of boron- nitride nanotube compounds. On the other hand electrostatic part of the interaction of carbon nanotube complex and solvent were almost the same as Van der Waals contribution. Complexation free energies were also computed to study the stability of related structures and the free energies were negative (-374.082 and -245.766kcalmol(-1)) which confirmed encapsulation of drug into abovementioned nanotubes. However, boron-nitride nanotubes were more appropriate for encapsulation due to their larger solubility in aqueous solution.
Antineoplastic Agents/chemistry , Boron Compounds/chemistry , Cisplatin/chemistry , Models, Chemical , Nanotubes, Carbon/chemistry , Nanotubes, Carbon/ultrastructure
Molecular dynamics (MD) simulation has been applied to investigate a drug delivery system based on boron nitride nanotubes, particularly the delivery of platinum-based anticancer drugs. For this propose, the behavior of carboplatin drugs inserted in boron nitride nanotubes (BNNT) as a carrier was studied. The diffusion rate of water molecules and carboplatin was investigated inside functionalized and pristine boron nitride nanotubes. The penetration rate of water and drug in functionalized BNNT was higher than that in pristine BNNT due to favorable water-mediated hydrogen bonding in hydroxyl edge-functionalized BNNT. Additionally, the encapsulation of multiple carboplatin drugs inside functionalized boron nitride nanotubes with one to five drug molecules confined inside the nanotube cavity was examined. At high drug loading, the hydrogen bond formation between adjacent drugs and the non-bonded van der Waals interaction between carboplatin and functionalized BNNT inner surface were found to be influential in drug displacement within the functionalized BNNT cavity for higher drug-loading capacity.
Antineoplastic Agents/chemistry , Boron Compounds/chemistry , Carboplatin/chemistry , Nanotubes/chemistry , Water/chemistry , Computer Simulation , Diffusion , Drug Delivery Systems , Models, Chemical , Models, Molecular , Molecular Structure
According to the critical role of drug delivery in the treatment of diseases of the central nervous system (CNS), the selection of a suitable carrier plays an important role in the greater effectiveness of drugs. Due to good biocompatibility, biodegradability and low toxicity of polymeric nanoparticles, especially poly(n-butylcyanoacrylate) (PBCA) and Chitosan, these nanoparticles are considered as efficient carriers in drug delivery to the brain. In order to investigate the compatibility of these two polymers with different degrees of polymerization versus a Tacrine unit as the most well known drug for the treatment of Alzheimer's disease, molecular dynamics simulation (MD) is used as a principal tool for studying molecular systems. Interaction energy of the polymer/Tacrine systems, the radius of gyration of the Chitosan and PBCA during the simulation time, solubility and Flory-Huggins interaction parameters has been calculated. According to the results, the Tacrine molecule exhibited higher compatibility with PBCA than Chitosan. Moreover, the interaction between the Tacrine molecules and PBCA nanoparticles became stronger by increasing the length of polymer chain while it was not observed as a regular trend for Chitosan/Tacrine systems. By using these MD simulations, it is possible to find the most appropriate polymer as an efficient drug carrier. We note that the methodology applied here for modeling the polymer/Tacrine system is not restricted to the specific formulations of Tacrine and Chitosan (or PBCA) in the current work and can be extended to various other traditional or new drugs and different polymer drug carriers.
Chitosan/chemistry , Drug Carriers/chemistry , Enbucrilate/chemistry , Nanoparticles/chemistry , Tacrine/chemistry , Molecular Dynamics Simulation , Polymerization
The infamous chronic neurodegenerative disease, Alzheimer's, that starts with short-term memory loss and eventually leads to gradual bodily function decline which has been attributed to the deficiency in brain neurotransmitters, acetylcholine, and butylcholine. As a matter of fact, design of compounds that can inhibit cholinesterases activities (acetylcholinesterase and butylcholinesterase) has been introduced as an efficient method to treat Alzheimer's. Among proposed compounds, bis(7)tacrine (B7T) is recognized as a noteworthy suppressor for Alzheimer's disease. Recently a new analog of B7T, cystamine-tacrine dimer is offered as an agent to detain Alzheimer's complications, even better than the parent compound. In this study, classical molecular dynamic simulations have been employed to take a closer look into the modes of interactions between the mentioned ligands and both cholinesterase enzymes. According to our obtained results, the structural differences in the target enzymes active sites result in different modes of interactions and inhibition potencies of the ligands against both enzymes. The obtained information can help to investigate those favorable fragments in the studied ligands skeletons that have raised the potency of the analog in comparison with the parent compound to design more potent multi target ligands to heal Alzheimer's disease.
Alzheimer Disease , Cholinesterase Inhibitors/chemistry , Cholinesterases/chemistry , Cystamine/chemistry , Models, Molecular , Tacrine/analogs & derivatives , Alzheimer Disease/drug therapy , Binding Sites , Catalytic Domain , Cholinesterase Inhibitors/pharmacology , Humans , Hydrogen Bonding , Ligands , Molecular Conformation , Molecular Docking Simulation , Molecular Dynamics Simulation , Protein Binding , Structure-Activity Relationship , Tacrine/chemistry
Molecular dynamics simulations were applied to investigate interfacial adhesion between functionalized polyethylene (fPE) and functionalized graphene (fG) surfaces. In order to functionalize the PE and graphene surfaces, various types of functional groups were covalently bonded on the surfaces in a random manner. Adhesion between fPE and fG surfaces was evaluated by the calculation of work of separation (Wsep), while the interfaces were not allowed to relax. According to the simulation results, the combination of the atomic roughness effect and the electronic properties of the functional groups had influence on the adhesion between PE and graphene. The effect of surface reorganization was also investigated by devoting sufficient time for relaxation of the interface. The adhesion in the relaxed interfaces was evaluated via the work of adhesion (Wadh). Relaxation of the interface caused to decrease the atomic roughness of the PE surface, which enhanced adhesion in all of the systems compared to their unrelaxed models. In addition to surface flattening, relaxation also brought about an increase in the atomic density at the interface, which led to enhance the van der Waals interaction and increase interfacial adhesion.
Some of new azo-based metal-free dyes with different π-conjugation spacers, such as carbazole, fluorene, pyrrole, thiophene, furan and thiazole, have been investigated with density functional theory (DFT) and time-dependent DFT (TDDFT) calculations. Theoretical calculations allow us to quantify factors such as light harvesting efficiency (LHE), electron injection driving force (ΔG(inject)) and the weight of the LUMO orbital on the carboxylic group (QLUMO) related to the short-circuit photocurrent density (Jsc), and to evaluate both charge recombination between the semiconductor conduction band electrons and the oxidized dyes and/or electrolyte, and also the shift of the conduction band of the semiconductor as a result of the adsorption of the dyes onto the semiconductor surface, associated with the open-circuit photovoltage (Voc). According to the results, we could predict that how the π-conjugation spacers influence the Jsc as well as the Voc of DSSCs. Among these dyes, the carbazole and fluorene-based dyes (dyes 1 and 2) show the highest LHE, ΔG(inject), QLUMO, and the slowest recombination rate. Consequently, the obtained results show that the carbazole and fluorene-based dyes could have the better Jsc and Voc compared to the other dyes.
Azo Compounds/chemistry , Quantum Theory , Solar Energy
The structure and dynamics of water confined in single-walled silicon carbon nanotubes (SWSiCNTs) are investigated using molecular dynamics (MD) simulations. The density of water inside SWSiCNTs is reported, and an equation is suggested to predict the density of water inside SWSiCNTs. Interestingly, the water diffusion coefficients (D) here are larger compared with those in SWCNTs and single-walled boron-nitride nanotubes (SWBNNTs). Furthermore, water inside zigzag SWCNTs has a lower diffusion coefficient than water inside armchair SWCNTs. A thorough analysis of the density profiles, hydrogen bonding, and water molecule orientation inside SWSiCNTs is presented to explore the mechanism behind the diffusive behavior of water observed here. It is shown here, by mean square displacement (MSD) analysis, that water molecules inside SWSiCNTs diffuse with a ballistic motion mechanism for up to 500ps. Additionally it is confirmed here for the first time that water molecules confined in the SWSiCNTs with diameters of less than 10Å obey the single-file diffusion mechanism at time scales in excess of 500ps. The orientation of water molecules inside SWSiCNTs could be a good explanation for the difference between the diffusion coefficient in (6,6) and (10,0) SWSiCNTs. Finally, a PMF analysis explains the difficulty of water entrance into SWSiCNTs and also the different water self-diffusion inside armchair and zigzag SWSiCNTs. These results are motivating reasons to use SWSiCNTs in nanoscale biochannels, for instance, in drug-delivery applications.
Carbon Compounds, Inorganic/chemistry , Molecular Dynamics Simulation , Nanotubes, Carbon/chemistry , Silicon Compounds/chemistry , Water/chemistry , Diffusion , Hydrogen Bonding , Models, Chemical , Specific Gravity
Due to the importance of soluble nanotubes in biological systems, computational research on DNA base functionalized nanotubes is of interest. This study presents the quantitative results of Monte Carlo simulations of Li-doped silicon carbide nanotubes and its nucleic acid base complexes in water. Each species was first modeled by quantum mechanical calculations and then Monte Carlo simulations were applied to study their properties in aqueous solution. Solvation free energies were computed to indicate the solvation behavior of these compounds. The computations show that solvation free energies of the complexes of DNA bases with Li-doped SiC nanotubes are in the order: thymine > cytosine > adenine > guanine. The results of complexation free energies were also used to study the stability of related structures, which indicate that thymine-Li-doped SiC nanotubes produce the most stable compound among the four DNA base complexes.
Carbon Compounds, Inorganic/chemistry , DNA/chemistry , Nanotubes/chemistry , Silicon Compounds/chemistry , Adenine/chemistry , Computer Simulation , Cytosine/chemistry , Guanine/chemistry , Kinetics , Lithium/chemistry , Monte Carlo Method , Quantum Theory , Solutions , Thermodynamics , Thymine/chemistry , Water
In this study, the mechanism of the temperature-dependent phase transition of confined water inside a (9,9) single-walled carbon nanotube (SWCNT) was studied using the hierarchical multi-scale modeling techniques of molecular dynamics (MD) and density functional theory (DFT). The MD calculations verify the formation of hexagonal ice nanotubes at the phase transition temperature T(c)=275K by a sharp change in the location of the oxygen atoms inside the SWCNT. Natural bond orbital (NBO) analysis provides evidence of considerable intermolecular charge transfer during the phase transition and verifies that the ice nanotube contains two different forms of hydrogen bonding due to confinement. Nuclear quadrupole resonance (NQR) and nuclear magnetic resonance (NMR) analyses were used to demonstrate the fundamental influence of intermolecular hydrogen bonding interactions on the formation and electronic structure of ice nanotubes. In addition, the NQR analysis revealed that the rearrangement of nano-confined water molecules during the phase transition could be detected directly by the orientation of ¹7O atom EFG tensor components related to the molecular frame axes. The effects of nanoscale confinements in ice nanotubes and water clusters were analyzed by experimentally observable NMR and NQR parameters. These findings showed a close relationship between the phase behavior and orientation of the electronic structure in nanoscale structures and demonstrate the usefulness of NBO and NQR parameters for detecting phase transition phenomena in nanoscale confining environments.
Electrons , Hydrogen/chemistry , Nanotubes, Carbon/chemistry , Oxygen/chemistry , Water/chemistry , Hydrogen Bonding , Ice , Magnetic Resonance Spectroscopy , Molecular Dynamics Simulation , Phase Transition , Quantum Theory , Static Electricity , Temperature
