Borophene, a monolayer of boron atoms, belongs to intensively studied two-dimensional beyond-graphene materials. The B36 borophene nanoflake is a finite size model system, containing a hexagonal vacancy similar to the ones present in (312 and chi 3 borophene sheets. The hydrogen binding performance of B36 decorated with various transition metal atoms is investigated using density functional theory and quantum theory of atoms in molecules. Hydrogen is considered to become one of the crucial energy sources in future, hence, a search for effective hydrogen storage materials is of urge importance. Obtained results suggest that B36 decorated with Co, Ni, Fe, and Cu possess strong affinity to bind the H2 molecule via formation of eta 2-dihydrogen bonds. Among them, the strongest H2 binding is found for Co- and Ni-decorated B36. Furthermore, B36 decorated with Sc and Ti behave like H-H bond breakers while B36 decorated with Zn possess only negligible affinity to bind H2 molecule. The stability of the B36 decorated with Co and Ni is verified by ab initio molecular dynamics. The presented data may also serve as a basis for reference in future large-scale computational studies of borophene-based materials.

This study investigates the structural and dynamic properties of ternary mixtures composed of NaPF6, ethylene carbonate (EC), and the ionic liquid choline glycine (ChGly), with a focus on their potential as electrolytes for supercapacitors. The combination of NaPF6-EC, known for its high ionic conductivity, with the biodegradable and environmentally friendly ChGly offers a promising approach to enhancing electrolyte performance. Through molecular simulations, we analyze how the inclusion of small concentrations of ChGly affects key properties such as density, cohesive energy, and ion mobility. Our findings demonstrate that the NaPF6-EC-ChGly mixture exhibits a complex network of electrostatic interactions and hydrogen bonding, with the glycine anion significantly influencing the liquid structure. In mixtures with small additions of ChGly, we observed an optimal balance of diffusion and ionic mobility. These results highlight the potential of ChGly as a green additive to conventional electrolytes, paving the way for more sustainable and high-performance energy storage devices.

Electrolytes play a crucial role in enhancing the performance of energy storage devices, including batteries and supercapacitors. However, traditional electrolytes, such as aqueous solutions, organic solvents, and ionic liquids, exhibit inherent limitations and challenges. Deep eutectic solvents have recently emerged as promising alternatives due to their environmentally friendly nature and favorable properties. Despite their widespread applications in various domains, their potential as electrolytes remains relatively underexplored. This study investigates three distinct types of deep eutectic solvents derived from different isomers of butanediols combined with choline chloride. Ab initio molecular dynamics simulations are employed to analyze the microstructure of these deep eutectic solvents, focusing on non-covalent electrostatic interactions, hydrogen bonding patterns, and vibrational spectra. The results reveal significant differences in the structural configuration of hydrogen bond acceptors and hydrogen bond donors and their interactions within the deep eutectic solvents. Specifically, the positioning of functional groups in hydrogen bond donors significantly impacts the hydrogen bonding network and the interaction with monoatomic ions. Moreover, the vibrational spectra analysis highlights the existence of hydrogen bonds involving stretching modes of the OH group, as evidenced by redshift deviations. Overall, this study provides valuable insights into the unique features of deep eutectic solvents as potential electrolytes for energy storage applications. The comprehensive analysis of their microstructure and vibrational properties enhances our understanding of deep eutectic solvent utilization and opens avenues for further research in sustainable energy storage.

The accurate prediction of standard vaporization enthalpy (ΔvapHm°) for volatile organic compounds (VOCs) is of paramount importance in environmental chemistry, industrial applications and regulatory compliance. To overcome traditional experimental methods for predicting ΔvapHm° of VOCs, machine learning (ML) models enable a high-throughput, cost-effective property estimation. But despite a rising momentum, existing ML algorithms still present limitations in prediction accuracy and broad chemical applications. In this work, we present a data driven, explainable supervised ML model to predict ΔvapHm° of VOCs. The model was built on an established experimental database of 2410 unique molecules and 223 VOCs categorized by chemical groups. Using supervised ML regression algorithms, the Random Forest successfully predicted VOCs' ΔvapHm° with a mean absolute error of 3.02 kJ mol−1 and a 95% test score. The model was successfully validated through the prediction of ΔvapHm° for a known database of VOCs and through molecular group hold-out tests. Through chemical feature importance analysis, this explainable model revealed that VOC polarizability, connectivity indexes and electrotopological state are key for the model's prediction accuracy. We thus present a replicable and explainable model, which can be further expanded towards the prediction of other thermodynamic properties of VOCs. © 2024 The Authors

In this paper, I present Diatomic, an open-source Excel application that calculates molar thermodynamic properties for diatomic ideal gases. This application is very easy to use and requires only a limited number of molecular constants, which are freely available online. Despite its simplicity, Diatomic provides methodologies and results that are usually unavailable in general quantum chemistry packages. This application uses the general formalism of statistical mechanics, enabling two models to describe the rotational structure and two models to describe the vibrational structure. In this work, Diatomic was used to calculate standard molar thermodynamic properties for a set of fifteen diatomic ideal gases. A special emphasis was placed on the analysis of four properties (standard molar enthalpy of formation, molar heat capacity at constant pressure, average molar thermal enthalpy, and standard molar entropy), which were compared with experimental values. A molecular interpretation for the molar heat capacity at constant pressure, as an interesting pedagogical application of Diatomic, was also explored in this paper.

Graphene-based materials modified with transition metals, and their potential utilization as hydrogen storage devices, are extensively studied in the last decades. Despite this widespread interest, a comprehensive understanding of the intricate interplay between graphene-based transition metal systems and H2 molecules remains incomplete. Beyond fundamental H2 adsorption, the activation of H2 molecule, crucial for catalytic reactions and hydrogenation processes, may occur on the transition metal center. In this study, binding modes of H2 molecules on the circumcoronene (CC) decorated with Cr or Fe atoms are investigated using the DFT methods. Side-on (eta 2-dihydrogen bond), end-on and dissociation modes of H2 binding are explored for high (HS) and low (LS) spin states. Spin state energetics, reaction energies, QTAIM and DOS analysis are considered. Our findings revealed that CC decorated with Cr (CC-Cr) emerges as a promising material for H2 storage, with the capacity to store up to three H2 molecules on a single Cr atom. End-on interaction in HS is preferred for the first two H2 molecules bound to CC-Cr, while the side-on LS is favored for three H2 molecules. In contrast, CC decorated with Fe (CC-Fe) demonstrates the capability to activate H2 through H-H bond cleavage, a process unaffected by the presence of other H2 molecules in the vicinity of the Fe atom, exclusively favoring the HS state. In summary, our study sheds light on the intriguing binding and activation properties of H2 molecules on graphene-based transition metal systems, offering valuable insights into their potential applications in hydrogen storage and catalysis.

Glycerol (propane-1,2,3-triol), a byproduct of biodiesel production, serves as a valuable precursor for numerous products including hydrogen, propylene glycol (propane-1,2-diol), propane-1,3-diol, lactide, acrolein, hydroxyacetone, pyruvaldehyde, acetaldehyde, ethylene glycol, glyceraldehyde, lactic acid, acetic acid, formic acid, glyceric acid, tartronic acid, oxalic acid, glycolic acid, glyoxylic acid, and pyruvic acid, among others. Utilizing glycerol for the production of these diverse compounds not only enhances the sustainability of biodiesel production but also contributes to the economic viability of the entire process. The primary challenge in realizing the conversion of glycerol into the aforementioned chemicals lies in the need for catalysts with adequate activity, selectivity, and stability for the various processes involved. To address this, researchers have frequently employed cost-effective Ni-Cu-based catalysts in studies focused on glycerol conversion. These catalysts can be effectively modified to adjust their activity, selectivity, and stability, thereby enabling the conversion of glycerol into valuable products. This review provides a comprehensive overview of recent achievements related to Ni-Cu catalysts utilized in glycerol conversion to valuable products. It explores and discusses general principles governing the catalytic properties of these catalysts. Special attention is paid to the modification of the reaction mechanisms by varying catalyst morphology and composition or adjusting reaction conditions. These modifications play a crucial role in achieving the desired products effectively. The knowledge gained on modifying the reaction mechanism by modulating Ni-Cu catalysts can be further utilized in the design of catalysts with improved characteristics for glycerol conversion.