On the thickness of the double layer in ionic liquids

In this study, we examined the thickness of the electrical double layer (EDL) in ionic liquids using density functional theory (DFT) calculations and molecular dynamics (MD) simulations. We focused on the BF4- anion adsorption from 1-ethyl-3-methylimidazolium tetrafluoroborate (EMImBF4) ionic liquid on the Au(111) surface. At both DFT and MD levels, we evaluated the capacitance-potential dependence for the Helmholtz model of the interface. Using MD simulations, we also explored a more realistic, multilayer EDL model accounting for the ion layering. Concurrent analysis of the DFT and MD results provides a ground for thinking whether the electrical double layer in ionic liquids is one- or multi-ionic-layer thick

Dermic diffusion and stratum corneum: a state of the art review of mathematical models

Transdermal biotechnologies are an ever increasing field of interest, due to the medical and pharmaceutical applications that they underlie. There are several mathematical models at use that permit a more inclusive vision of pure experimental data and even allow practical extrapolation for new dermal diffusion methodologies. However, they grasp a complex variety of theories and assumptions that allocate their use for specific situations. Models based on Fick's First Law found better use in contexts where scaled particle theory Models would be extensive in time-span but the reciprocal is also true, as context of transdermal diffusion of particular active compounds changes. This article reviews extensively the various theoretical methodologies for studying dermic diffusion in the rate limiting dermic barrier, the stratum corneum, and systematizes its characteristics, their proper context of application, advantages and limitations, as well as future perspectives

Coupling of Cyclic Voltammetry and Electrochemical Impedance Spectroscopy for Probing the Thermodynamics of Facilitated Ion Transfer Reactions Exhibiting Chemical Kinetic Hindrances

Mathematical models under conditions of cyclic staircase voltammetry and electrochemical impedance spectroscopy (EIS), which consider the kinetic effects due to the complexation reaction by the facilitated transfer of metal ions at polarized interfaces, are presented. Criteria for qualitative recognition of these kinetic effects from the features of simulated cyclic voltammograms are given. In case of the existence of these effects, only the EIS can bring access to the thermodynamics and kinetics of the complexation chemical reaction. Analytical equations for estimating the thermodynamic parameters by such systems under EIS conditions are evaluated. The theoretical results are compared with the experimental results of the facilitated Cu2+ transfer at the polarized water-1,2-dichlorethane interface, assisted by two phenanthroline-containing macrocycles. In the experimental case where kinetic effects due to the complexation step exist, we show how elegantly EIS can be used as a tool for estimation of the complexation constant of Cu2+ and 5-oxo-2,8-dithia [9],(2,9)-1,10-phenanthrolinophane (PhenOS2)

DFT study of the CO oxidation on the Au(321) surface

The CO oxidation on the Au(321) surface was investigated using spin polarized density functional theory based calculations within the GGA-PW91 exchange-correlation functional. This was done by studying separately the adsorption of isolated CO or CO2 and also the coadsorption of CO + O or CO + O-2 on the Au(321) surface. A periodic supercell approach was used to model the gold surface. The kinetic profile of the oxidation reaction was determined with the climbing image-nudged elastic band method and also with the dimer approach. It was found that CO adsorbs on the clean surface preferably at the kinks, and the same preference exists if atomic or molecular oxygen is coadsorbed on the Au(321) surface. CO2 is weakly adsorbed on Au(321) and appears at large distance from the metal surface. Importantly, the formation of carbonate species or of four atoms compounds, OCOO, adsorbed on the Au(321) surface is thermodynamically favorable from CO and O-2. The reaction of CO oxidation by atomic oxygen occurs almost without any energy cost on a reconstructed surface, whereas moderate barriers of similar to 0.6 eV were computed for the direct reaction with molecular oxygen occurring at the surface steps. These results suggest that the predissociation of the molecular oxygen on the Au(321) surface for the CO oxidation is energetically less favorable than the direct reaction with molecular oxygen. Finally, the products of the oxidation reaction are much more stable than the four atoms compound.publishe

New Mechanistic Insights on Carbon Nanotubes’ Nanotoxicity Using Isolated Submitochondrial Particles, Molecular Docking, and Nano-QSTR Approaches

Single-walled carbon nanotubes can induce mitochondrial F0F1-ATPase nanotoxicity through inhibition. To completely characterize the mechanistic effect triggering the toxicity, we have developed a new approach based on the combination of experimental and computational study, since the use of only one or few techniques may not fully describe the phenomena. To this end, the in vitro inhibition responses in submitochondrial particles (SMP) was combined with docking, elastic network models, fractal surface analysis, and Nano-QSTR models. In vitro studies suggest that inhibition responses in SMP of F0F1-ATPase enzyme were strongly dependent on the concentration assay (from 3 to 5 µg/mL) for both pristine and COOH single-walled carbon nanotubes types (SWCNT). Besides, both SWCNTs show an interaction inhibition pattern mimicking the oligomycin A (the specific mitochondria F0F1-ATPase inhibitor blocking the c-ring F0 subunit). Performed docking studies denote the best crystallography binding pose obtained for the docking complexes based on the free energy of binding (FEB) fit well with the in vitro evidence from the thermodynamics point of view, following an affinity order such as: FEB (oligomycin A/F0-ATPase complex) = −9.8 kcal/mol > FEB (SWCNT-COOH/F0-ATPase complex) = −6.8 kcal/mol ~ FEB (SWCNT-pristine complex) = −5.9 kcal/mol, with predominance of van der Waals hydrophobic nano-interactions with key F0-ATPase binding site residues (Phe 55 and Phe 64). Elastic network models and fractal surface analysis were performed to study conformational perturbations induced by SWCNT. Our results suggest that interaction may be triggering abnormal allosteric responses and signals propagation in the inter-residue network, which could affect the substrate recognition ligand geometrical specificity of the F0F1-ATPase enzyme in order (SWCNT-pristine > SWCNT-COOH). In addition, Nano-QSTR models have been developed to predict toxicity induced by both SWCNTs, using results of in vitro and docking studies. Results show that this method may be used for the fast prediction of the nanotoxicity induced by SWCNT, avoiding time- and money-consuming techniques. Overall, the obtained results may open new avenues toward to the better understanding and prediction of new nanotoxicity mechanisms, rational drug design-based nanotechnology, and potential biomedical application in precision nanomedicineThis research was funded by FCT/MCTES through national funds (Michael González-Durruthy, Riccardo Concu, and M. Natália D.S. Cordeiro), grant UID/QUI/50006/2020, as well as by Xunta de Galicia (Juan M. Ruso), grant ED41E2018/08S

Intrinsic structure and dynamics of the water/nitrobenzene interface

In this paper we present results of a detailed and systematic molecular dynamics study of the water/nitrobenzene interface. Using a simple procedure to eliminate fluctuations of the interface position, we are able to obtain true intrinsic profiles for several properties (density, hydrogen bonds, molecular orientation, etc.) in the direction perpendicular to the interfacial plane. Our results show that both water and organic inter-facial molecules form a tightly packed layer oriented parallel to the interface, with reduced mobility in the perpendicular direction. Beyond this layer, water quickly restores its bulk structure, while nitrobenzene exhibits structural anisotropies that extend further into the bulk region: Water molecules that protrude farthest into the organic phase point one hydrogen atom in the direction perpendicular to the interface, forming a hydrogen bond with a nitrobenzene oxygen. By fitting both the global and the intrinsic density profiles, we obtain estimates for the total and intrinsic interface widths, respectively. These are combined with capillary wave theory to produce a self-consistent method for the calculation of the inter-facial tension. Values calculated using this method are in very good agreement with direct calculations from the components of the pressure tensor

Machine learning-driven prediction of deep eutectic solvents’ heat capacity for sustainable process design

Funding Information: This work received financial support from FCT/MCTES (UIDB/50006/2020 DOI 10.54499/UIDB/50006/2020) through national funds. This work received financial support from FCT/MCTES (LA/P/0008/2020 DOI 10.54499/LA/P/0008/2020, UIDP/50006/2020 DOI 10.54499/UIDP/50006/2020, and UIDB/50006/2020 DOI 10.54499/UIDB/50006/2020), through national funds. The authors also acknowledge FCT by funding CEEC projects 2020.01423.CEECIND/CP1596/CT0003 and 10.54499/2022.05803.CEECIND/CP1725/CT0003. Publisher Copyright: © 2024 The Author(s)Heat capacity, a crucial physical property for chemical processes, is often understudied in Deep Eutectic Solvents (DESs), which in turn are promising green alternatives to environmentally hazardous conventional solvents. This work addresses this gap by developing a machine learning model to predict DES heat capacity and identify key structural features influencing it. We employed a dataset of 530 DESs with corresponding experimental heat capacity values. Quantum-chemical COSMO-RS-based descriptors, capturing detailed information about DES structures, were calculated for each data point. Various machine learning algorithms, namely k-Nearest Neighbours (kNN), Random Forests (RF), Neural Network Multilayer Perceptron (MLP), and Support Vector Machines (SVM) were explored alongside a linear model (Multiple Linear Regression, MLR). Hyperparameter optimisation ensured all models were fine-tuned for optimal performance. The most successful model, based on the MLP technique, achieved remarkably low Average Absolute Relative Deviation (AARD) values of 0.500 % and 3.999 % for the training and test sets, respectively. This signifies a significant improvement in prediction accuracy compared to traditional methods. Furthermore, by applying a SHapley Additive exPlanations (SHAP) analysis, we identified the most crucial structural factors within DES components that govern their heat capacity. This comprehensive investigation offers valuable insights that can pave the way for an efficient design of novel DESs in the future.publishersversionpublishe

A critical assessment of methods for the intrinsic analysis of liquid interfaces: 2. density profiles

Substantial improvements in the molecular level understanding of fluid interfaces have recently been achieved by recognizing the importance of detecting the intrinsic surface of the coexisting condensed phases in computer simulations (i.e., after the removal of corrugations caused by capillary waves) and by developing several methods for identifying the molecules that are indeed located at the boundary of the two phases. In our previous paper [J. Phys. Chem. C 2010, 114, 11169], we critically compared those methods in terms of reliability, robustness, and computation speed. Once the intrinsic surface of a given phase is detected, various profiles, such as the density profiles of the components, can be calculated relative to this intrinsic surface rather than to the macroscopically planar Gibbs dividing surface. As a continuation of our previous study, here we present a detailed and critical comparison of various methods that can be used to calculate intrinsic density profiles once the full set of truly interfacial molecules has been identified. Two of the methods, the Fourier function and the Voronoi tessellation, are already described in the literature; two other methods, the covering surface and the triangular interpolation, are newly proposed algorithms; one method, the modified grid-based intrinsic profile (GIP) method, is an improvement over an existing procedure. The different methods are again compared in terms of accuracy and computational cost. On the basis of this comparison, we propose a fast and accurate protocol to be routinely used for intrinsic surface analyses in computer simulations

Targeting Beta-Blocker Drug–Drug Interactions with Fibrinogen Blood Plasma Protein: A Computational and Experimental Study

In this work, one of the most prevalent polypharmacology drug–drug interaction events that occurs between two widely used beta-blocker drugs—i.e., acebutolol and propranolol—with the most abundant blood plasma fibrinogen protein was evaluated. Towards that end, molecular docking and Density Functional Theory (DFT) calculations were used as complementary tools. A fibrinogen crystallographic validation for the three best ranked binding-sites shows 100% of conformationally favored residues with total absence of restricted flexibility. From those three sites, results on both the binding-site druggability and ligand transport analysis-based free energy trajectories pointed out the most preferred biophysical environment site for drug–drug interactions. Furthermore, the total affinity for the stabilization of the drug–drug complexes was mostly influenced by steric energy contributions, based mainly on multiple hydrophobic contacts with critical residues (THR22: P and SER50: Q) in such best-ranked site. Additionally, the DFT calculations revealed that the beta-blocker drug–drug complexes have a spontaneous thermodynamic stabilization following the same affinity order obtained in the docking simulations, without covalent-bond formation between both interacting beta-blockers in the best-ranked site. Lastly, experimental ultrasound density and velocity measurements were performed and allowed us to validate and corroborate the computational obtained resultsThis research was funded by FCT/MCTES through national funds (Michael González-Durruthy, Riccardo Concu, and M. Natália D.S. Cordeiro), grant UID/QUI/50006/2020, as well as by Xunta de Galicia (Juan M. Ruso), grant ED41E2018/08S

Effect of the exchange-correlation potential on the transferability of Bronsted-Evans-Polanyi relationships in heterogeneous catalysis

As more and more accurate density functional methods emerge, the transferability of Bronsted-Evans-Polanyi (BEP) relationships obtained with previous models is an open question. In this work, BEP relationships derived from different density functional theory based calculations are analyzed to answer this question. In particular, BEP relationships linking the activation energy of O-H bond breaking reactions taking place on metallic surfaces with the adsorption energy of the reaction products are chosen as a case study. These relationships are obtained with the widely used Perdew-Wang (PW91) generalized gradient approximation (GGA) exchange-correlation functional and with the more accurate meta-GGA Tao-Perdew Staroverov-Scuseria (TPSS) one. We provide compelling evidence that BEP relationships derived from PW91 and TPSS functionals are essentially coincidental. This finding validates previously published BEP relationships and indicates that the reaction activation energy barrier can be obtained by the determination of the energy reaction descriptor value at the less computationally demanding GGA level; an important aspect to consider in future studies aimed at the computational design of catalysts :with improved characteristics