<jats:p> Ionic liquids (ILs) are a unique class of electrolytes, which characteristics make them suitable for use in solar cells, supercapacitors, and fuel cells<jats:sup>1</jats:sup>. Due to the appealing properties such as good electrochemical stability, low vapour pressure, high concentration of ions and the lack of solvent, they have been under intense study since the early 2000s. Although numerous theoretical<jats:sup>2,3</jats:sup>, computational<jats:sup>4,5</jats:sup>, and experimental studies<jats:sup>6,7</jats:sup> have shed light on the interfacial properties of ILs, which differ noticeably from the aqueous electrolytes, multiple open questions remain. One such problem is how the interfacial capacitance is affected by the ambient temperature, as studies have shown both positive and negative temperature dependences<jats:sup>8,9</jats:sup>. Understanding the temperature dependence of interfacial capacitance is crucial as it is relevant for the description of energy storage and is one of the few quantities, which can be estimated both experimentally and computationally.</jats:p> <jats:p>In this study, we combine the density functional theory (DFT) calculations with molecular dynamics (MD) simulations of graphene (Gr) | EMImBF<jats:sub>4</jats:sub> IL interface to explain the effect of temperature on capacitance. MD simulations allow us to investigate the probable distribution of ions near the electrode’s surface and relate the changes of ILs structure to the capacitance using the interfacial bilayer model (IBL). We show that the increase of temperature affects the capacitance near the potential of zero charge by attenuating the overscreening without a notable change in the IL interfacial structure. The characteristic peaks and plateaus in the capacitance potential dependence are explained through the concepts of IL layering and saturation of the second IL layer described in the IBL. Using the DFT calculations, we estimate the impact of the quantum capacitance of Gr on the total interfacial capacitance and its temperature dependence. By accounting for the limiting quantum capacitance, the total interfacial capacitance was significantly altered in the case of the Gr electrode, as the effect of the temperature was dampened, and a V-shaped capacitance curve was obtained.</jats:p> <jats:p>Acknowledgements:</jats:p> <jats:p>This work was supported by the Estonian Research Council grant PSG249 and by the EU through the European Regional Development Fund under project TK141 (2014-2020.4.01.15-0011). The financial support from FCT/MCTES through the Portuguese national funds, project No. UID/QUI/50006/2021 (LAQV@REQUIMTE) is also acknowledged.</jats:p> <jats:p>References:</jats:p> <jats:p>1 D. R. MacFarlane, N. Tachikawa, M. Forsyth, J. M. Pringle, P. C. Howlett, G. D. Elliott, J. H. Davis, M. Watanabe, P. Simon and C. A. Angell, <jats:italic>Energy Environ. Sci.</jats:italic>, 2014, <jats:bold>7</jats:bold>, 232–250.</jats:p> <jats:p>2 A. A. Kornyshev, <jats:italic>J. Phys. Chem. B</jats:italic>, 2007, <jats:bold>111</jats:bold>, 5545–5557.</jats:p> <jats:p>3 Z. A. H. Goodwin and A. A. Kornyshev, <jats:italic>Electrochem. Commun.</jats:italic>, 2017, <jats:bold>82</jats:bold>, 129–133.</jats:p> <jats:p>4 M. Salanne, <jats:italic>Phys. Chem. Chem. Phys.</jats:italic>, 2015, <jats:bold>17</jats:bold>, 14270–14279.</jats:p> <jats:p>5 I. V. Voroshylova, H. Ers, V. Koverga, B. Docampo-Álvarez, P. Pikma, V. B. Ivaništšev and M. N. D. S. Cordeiro, <jats:italic>Electrochim. Acta</jats:italic>, 2021, <jats:bold>379</jats:bold>, 138148.</jats:p> <jats:p>6 L. Siinor, K. Lust and E. Lust, <jats:italic>J. Electrochem. Soc.</jats:italic>, 2010, <jats:bold>157</jats:bold>, F83.</jats:p> <jats:p>7 V. Lockett, M. Horne, R. Sedev, T. Rodopoulos and J. Ralston, <jats:italic>Phys. Chem. Chem. Phys.</jats:italic>, 2010, <jats:bold>12</jats:bold>, 12499–12512.</jats:p> <jats:p>8 F. Silva, C. Gomes, M. Figueiredo, R. Costa, A. Martins and C. M. Pereira, <jats:italic>J. Electroanal. Chem.</jats:italic>, 2008, <jats:bold>622</jats:bold>, 153–160.</jats:p> <jats:p>9 M. Drüschler, N. Borisenko, J. Wallauer, C. Winter, B. Huber, F. Endres and B. Roling, <jats:italic>Phys. Chem. Chem. Phys.</jats:italic>, 2012, <jats:bold>14</jats:bold>, 5090–5099. </jats:p>

Aim: Our previous results suggest that phenyl/naphthylacetyl pentanoic acid derivatives may exhibit dual MMP-2 and HDAC8 inhibitory activities and show effective cytotoxic properties. Methodology: Here, 13 new compounds (C1-C13) were synthesized and characterized. Along with these new compounds, 16 previously reported phenyl/napthylacetyl pentanoic acid derivatives (C14-C29) were biologically evaluated. Results: Compounds C6 and C27 showed good cytotoxicity against leukemia cell line Jurkat E6.1. The mechanisms of cytotoxicity of these compounds were confirmed by DNA deformation assay and reactive oxygen species assay. MMP-2 and HDAC8 expression assays suggested the dual inhibiting property of these two compounds. These findings were supported by results of molecular docking studies. In silico pharmacokinetic properties showed compounds C6 and C27 have high gastrointestinal absorption. Conclusion: This study highlights the action of phenyl/naphthylacetyl pentanoic acid derivatives as anticancer agents.

<jats:p>Fullerenes are reactive as dienophiles in Diels–Alder reactions. Their distinctive molecular shape and properties result in interesting and sometimes elusive reaction patterns. Herein, to contribute to the understanding of fullerene reactivity, we evaluate the energies of reactions for Diels–Alder cycloadditions of C60, C70, and IC60MA with anthracene (Ant), by means of DFT computational analysis in vacuum and solution. The methods used showed little differentiation between the reactivity of the different fullerenes. The C70-Ant adducts where addition takes place near the edge of the fullerene were found to be the most stable regioisomers. For the IC60MA-Ant adducts, the calculated energies of reaction increase in the order: equatorial &gt; trans-3 &gt; trans-2 ≈ trans-4 ≈ trans-1 &gt; cis-3 &gt; cis-2. The change in the functional suggests the existence of stabilizing dispersive interactions between the surface of the fullerene and the addends. HOMA (harmonic oscillator model of aromaticity) analysis indicated an increase in aromaticity in the fullerene hexagons adjacent to the bonded addend. This increase is bigger in the rings of bisadduct isomers that are simultaneously adjacent to both addends, which helps explain the extra stability of the equatorial isomers. Solvation by m-xylene decreases the exothermicity of the reactions studied but has little distinguishing effect on the possible isomers. Thermal corrections reduce the exothermicity of the reactions by ~10 kJ∙mol−1.</jats:p>

Modern industrialization has led to the creation of a wide range of organic chemicals, especially in the form of multicomponent mixtures, thus making the evaluation of environmental pollution more difficult by normal methods. In this paper, we attempt to use forward stepwise multiple linear regression (MLR) and nonlinear radial basis function neural networks (RBFNN) to establish quantitative structure-activity relationship models (QSARs) to predict the toxicity of 79 binary mixtures of aquatic organisms using different hypothetical descriptors. To search for the proper mixture descriptors, 11 mixture rules were performed and tested based on preliminary modeling results. The statistical parameters of the best derived MLR model were N-train = 62, R-2 = 0.727, RMS = 0.494, F = 159.537, Q(LOO)(2) = 0.727, and Q(pred)(2) = 0.725 for the training set; and N-test = 17, R-2 = 0.721, RMS = 0.508, F = 38.773, and q(ext)(2) = 0.720 for the external test set. The RBFNN model gave the following statistical results: N-train = 62, R-2 = 0.956, RMS = 0.199, F = 1279.919, Q(LOO)(2) = 0.955, and Q(pred)(2) = 0.855 for the training set; and N-test = 17, R-2 = 0.880, RMS = 0.367, F = 110.980, and q(ext)(2) = 0.853 for the external test set. The quality of the models was assessed by validating the relevant parameters, and the final results showed that the developed models are predictive and can be used for the toxicity prediction of binary mixtures within their applicability domain.

Carbon dioxide capture and storage is one of the primary mitigation approaches endorsed by current global climate change policies, since it is the largest contributing gas to the greenhouse effect. Recently, deep eutectic solvents (DESs) have been found as promising green solvents for CO(2 )capture, particularly in industrial applications. Compared to conventional ionic liquids, for example, DESs display similar solvent properties but they are far cheaper, easier to prepare, and greener. Yet their major drawback is linked to their high viscosity that impedes management not fulfilling industrial demands. Further efforts are thus required to develop new DES solvents that hold together high capacity for CO2 uptake and low viscosity. In this work, we adopted a desirability-based decision approach to jointly handle these two conflicting properties. We began by setting up Quantitative Structure-Property Relationships (QSPR) models for uncovering the two properties based on a dataset of known binary DESs. Then, desirability functions derived from the individual QSPR models were found and combined into an overall desirability-based criterion that was applied to screen and rank two libraries, one comprising experimentally reported DESs and another one with newly designed DESs. The latter enabled us to propose novel efficient DESs for CO2 uptake, i.e., with the most suitable trade-offs between CO2 absorption capacity and viscosity. Finally, but most importantly, this work demonstrates the usefulness of the desirability based approach for the rational discovery of deep eutectic solvents or other materials to suit particular sustainable applications.

Designing a science activity for middle school children is a challenging task, especially if it aims to be interdisciplinary. One may ask if it is possible to craft a positive learning experience from different areas such as history of science, chemistry, or ethics. In this paper, we argue it can be achieved if we use the right tools to engage a young audience. A combination of gamification, hands-on activities, and storytelling techniques was successfully used, providing a unique form to approach chemistry and ethics subjects in an "edutainment" format. The result is a game that challenges participants to solve a crime, while addressing chemistry topics to gather pieces of evidence and facing science-related ethical conundrums. In our pilot study, participants evaluated this activity positively, identifying the innovation and entertaining features as the most relevant in their gaming experience.

<jats:p>The development of new materials based on hydroxyapatite has undergone a great evolution in recent decades due to technological advances and development of computational techniques. The focus of this review is the various attempts to improve new hydroxyapatite-based materials. First, we comment on the most used processing routes, highlighting their advantages and disadvantages. We will now focus on other routes, less common due to their specificity and/or recent development. We also include a block dedicated to the impact of computational techniques in the development of these new systems, including: QSAR, DFT, Finite Elements of Machine Learning. In the following part we focus on the most innovative applications of these materials, ranging from medicine to new disciplines such as catalysis, environment, filtration, or energy. The review concludes with an outlook for possible new research directions.</jats:p>

AKT, is a serine/threonine protein kinase comprising three isoforms-namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT' inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.