Energy Descriptors Research Articles

Acoustic ambience of two roman theatres in the Cartaginensis province of Hispania

The period of Romanisation of Hispania runs from 218 BCE (Romans landing in Ampurias) to the beginning of the 5th century (entry of the Visigoths into the Iberian Peninsula, replacing the authority of Rome). Throughout this extensive period spanning seven centuries, the territory would be marked with the unmistakable imprint of Roman culture and customs. The imperial era of Roman civilisation witnessed not only the greatest upsurge in the construction of the theatre, but also the export of its model from Rome to the provinces. This work studies the acoustic environment of two Roman theatres of Hispania (present-day Spain and Portugal) located on the east coast of the peninsula that were reference cities of the Cartaginensis province: the theatre of Carthago Nova and the theatre of Saguntum. The acoustic characterisation encompasses a parametric and spatial description of their sound fields and a comparison of their acoustic atmospheres justified by their different states of recovery-rehabilitation. Both theatres especially that of Saguntum, present long reverberation times compared to other theatres of Roman Hispania. As a consequence, their energy descriptors show noticeable differences in the two theatres, whereby the most unfavourable perceptual conditions are presented in the Saguntum theatre with its completely rebuilt stage front. The parametric results are corrobarated through tridimensional energy plots carried out by IRIS diagrams imported into 3D geometrical models of the performance spaces, and therefore further indicate the importance of certain zones in the acoustics of the theatres.

Improvement of Sentinel‐1 Remote Sensing Data Classification by DWT and PCA

This article presents a new alternative for data resource, by applying the proposed methods of Principal Components Analysis (PCA) or of Discrete Wavelet Transformation (DWT) on the VV and VH polarization images of the Sentinel‐1 radar satellite, aiming at a better classification of data. The study area concerns the Houareb site located in the city of Kairouan in central Tunisia. In addition to Sentinel‐1 data, field truth data and the Euclidian Minimum Distance (EMD) criterion were used for classification and validation. Energy descriptors have been proposed in this study for classifications. Cross validation was used to evaluate the results of the classification. The best classification result was achieved using the DWT method applied on VH and VV images with an Overall Precision (OA) of 0.671 and 0.548, respectively, against an OA value of 0.371 and of 0.449 when the PCA method and the Minimum Distance (MDist) classifier were applied on the dual (VV; VH) polarization, respectively. The DWT transformation gives the highest Kappa Precision Coefficient (KPC) of 0.8.

Molecular simulation for adsorption and separation of CH<sub>4</sub>/H<sub>2</sub> in zeolites

Based on the high-throughput calculation method of molecular simulation, except the structures with zero surface area and less than zero adsorption capacity, four geometric descriptors (largest cavity diameter, specific surface area, pore volume and porosity), an energy descriptor (heat of adsorption), adsorption capacity, and adsorption selectivity coefficient of 199 zeolites are obtained. By studying the correlation between structural characteristics and adsorption separation performance, the result shows that when the largest cavity diameter is 6 Å, the surface area is 1400–2100 m<sup>2</sup>·g<sup>–1</sup>, and the pore volume is in a range of 0.2–0.3 cm<sup>3</sup>·g<sup>–1</sup>, the zeolite has the greatest influence on the adsorption capacity and adsorption selectivity for methane molecules. At the same time, it is found that the largest cavity diameter and porosity of zeolite molecular sieves have a positive correlation, and there is also an obvious linear relationship between the CH<sub>4</sub> adsorption selectivity coefficient of the equimolar CH<sub>4</sub>/H<sub>2</sub> mixed component and the single-component CH<sub>4</sub> adsorption capacity. By using the grand canonical Monte Carlo simulation method, physical quantities such as adsorption isotherms and isosteric heats of adsorption for CH<sub>4</sub> and H<sub>2</sub> of three channel-shaped zeolites are obtained. The result shows that the pore structure (surface area and pore volume) of the channel-shaped zeolite has a greater influence on the CH<sub>4</sub> adsorption capacity than the energy effect (heat of adsorption), under the same external environment. Combining with the industrial background of steam methane reforming hydrogen production, the separation and selectivity performance of the CH<sub>4</sub>/H<sub>2</sub> mixed system under different components are further studied. The result reveals that there is no correlation between adsorption selectivity of ultra-microporous zeolite material for CH<sub>4</sub> and bulk pressure or feed ratio. According to the centroid distribution density of gas molecules, it is found that CH<sub>4</sub> preferentially occupies the space of smaller pore windows in the channel-shaped zeolite, while the distribution range of H<sub>2</sub> is larger but there is no unambiguous preferential adsorption site.

Catalytic mechanism and selectivity prediction for syngas conversion over pure and K-promoted Mo2C catalysts

Density functional theory (DFT) calculations were performed to reveal the intricate pathways of syngas conversion over Mo2C catalysts. Our computational results show that CO activation occurs preferably via its hydrogenation to HCO on the Mo2C (001) surface. The Mo-Mo bridge site is found to be the active site, and ethanol formation involves the HCO*, H2CO, CH2, CH3, CH3CHO, and CH3CH2O intermediates. Product selectivity in this reaction is mainly affected by reaction steps involving CH2, and ethanol yield is limited by the high energy barriers of CH3+CHO coupling and C2H5O hydrogenation. Since K has been experimentally shown to be an outstanding promoter for increasing alcohol selectivity, we further investigated the effect of the K promoter to the catalytic performance of the Mo2C catalyst. Compared to the pure Mo2C (001) surface, K-Mo2C (001) promotes the activity of the CH3+CHO coupling. To give a semi-quantitative estimate for the product selectivity, we used the effective energy barrier difference (ΔEeff) between CH2+CH2 coupling and CH3+CHO coupling as an energy descriptor. The ΔEeff value of the K-Mo2C (001) surface is significantly greater than that of the pristine surface, indicating higher selectivity of ethanol over the K-promoted surface, which is consistent with the experimental observation. Furthermore, comparing the Mo2C(001) and (100) surfaces, we find that the Mo2C (001) surface exhibits better activity toward CO activation, whereas the Mo2C (100) surface favors the CC coupling reaction.

Thermodynamic factors for locally non-neutral, concentrated electrolytic fluids

A constitutive framework is created to parameterize the composition-dependent parts of thermodynamic differentials that undergird the diffusion driving forces in non-neutral electrolytic fluids. The definition of a novel two-ion secondary reference state allows us to formulate a neutralizable composition basis, in which one natural composition variable is replaced by the molar excess charge. This basis is conjugate to a set of energy descriptors we call core potentials, among which Maxwell relations and Gibbs–Duhem constraints take simple forms that isolate charge effects. Core potentials derive from intensive measures of energy and composition, a refinement of Kokotov's twin-potential scheme that enables applications to materials wherein properties vary spatially. Matrix representations are constructed for the transformations that interconvert among Guggenheim (electrochemical), Smyrl–Newman (quasielectrostatic), and core potentials. These transformations reveal how the Guggenheim and Smyrl–Newman formalisms can be extended to handle charge-imbalanced microscopic equilibria. The core-potential framework is naturally parameterized in terms of conventional electroneutral thermodynamic factors, but also includes an independent set of new electrostatic colligative properties that can account for an additional equation of state governing molar charge. Consistent thermodynamic parameterizations are derived for electrolytes that obey the ideal-solution approximation and electrolytes that follow Poisson–Boltzmann theory. We explicitly develop constitutive equations for the species electrochemical-potential differentials within a chemically nonideal binary solution of a symmetrical-valence electrolyte that also satisfies the Poisson–Boltzmann charge–potential relation.

Structure, conformational dynamics, quantum mechanical studies and potential biological activity analysis of multiple sclerosis medicine ozanimod

Ozanimod is a newly formulated drug used to manage relapsing multiple sclerosis. Here, we use computational chemistry tools to study the structure and various physio-chemical properties of the molecule. We applied the dispersion corrected ωB97XD functional with DGDZVP as a basis set and DEF2SV as a fitting set to determine the geometry of the molecule. Potential energy scan predicts that the most stable conformer is stable by 8.15 kcal/mol with respect to the eclipsed conformation. Time dependent density functional theory (TD-DFT) with CAM-B3LYP and the same basis sets were used to study the electronic spectra in methanol solvent. Non covalent interactions, average local ionization energy, and energy descriptors helped in predicting the reactivity and stability of the molecule. The compound also had excellent non-linear optical properties when compared to the standard material urea. Screening for biological activity followed by molecular docking studies suggested that ozanimod interacts with three proteins responsible for autoimmune disorders.

Calculation of the UV Spectrum and Electrophilic Reactive Sites of Fentanyl Molecule Based on the Density Functional Theory

The theoretical calculation of fentanyl molecule based on DFT is of great significance to understand the properties. The initial conformations were searched by molclus software and two reasonable conformations were selected. The structural optimization of fentanyl using DFT/B3LYP/6-311+G(d,p) method by Gaussian16. Based on this, the first 50 excited states are calculated by using TD-DFT with methanol as the solvent. Multiwfn 3.6 was used to calculate its electrical parameters such as electrostatic potential, average local ionization energy, Fukui function and dual descriptor and draw UV spectrum. From the UV spectrum, the maximum absorption peak is located at 188 nm, which is mainly formed by the σ → σ* transition of the C–C, C–H bond. From the analysis of electrical parameters, the nitrogen atom (N18) on the piperidine ring is an electrophilic reactive site, and it is easily attacked by an electrophilic reagent so that the phenethyl group is replaced by a hydrogen atom to form norfentanyl.

Structural aspects, conformational preference and other physico-chemical properties of Artesunate and the formation of self-assembly with graphene quantum dots: A first principle analysis and surface enhancement of Raman activity investigation

Artesunate and its derivatives belong to a family of compounds that are highly effective against Malaria. This drug is active against several other conditions like neurodegerative diseases and cancer. The compound forms a metabolite dihydroartemisinine, which contain an endoperoxide bridge that is stimulated by heme iron leading to oxidative stress, protein and nucleic acid synthesis inhibition, morphologic changes and reduced growth and survival of parasites. This manuscript examines the structure and conformational preferences of the compound and investigates the energy and reactivity descriptors using computational simulations. Studies indicates that the compound forms stable self-assemblies with graphene quantum dots and modified graphene quantum dots, where the more stable complex was formed with the modified system. This self-assembly formation leads to enhancement in Raman activity of the compound after complex formation, hence can be used an analytical tool for the detection of the compound in a mixture. Natural bond orbital analysis examines the various intramolecular electron delocalisations. This drug is found to be a nonlinear optically active compound with respect to standards materials like urea and paranitroacetanilide. We also report the non covalent interactions present in the molecule, reduced density gradient, Lapalcian electron density and local information entropy of the molecule.

Learning What Makes Catalysts Good

Machine learning has proven a powerful tool for accelerating the computational characterization of energy materials. The neural-network approach by Lu et al. allows bypassing time-consuming first principles calculations for the design of catalysts based on high-entropy alloys. This work is an example of a growing number of case studies identifying descriptors of catalytic performance using machine learning instead of physical intuition.

Spectral analysis and detailed quantum mechanical investigation of some acetanilide analogues and their self-assemblies with graphene and fullerene.

Spectroscopic analysis and different quantum mechanical studies of four pharmaceutically active compounds phenacetin, p-acetanisidide, 4'-butoxyacetanilide, and 4'-(3-chloropropoxy)acetanilide are reported in this manuscript. Simulated IR spectrum of these compounds was compared with experimentally available data, and essential functional group assignments were made. We also report the frontier orbital properties and other derived local energy descriptors which talks about the relative stability and reactivity. Photovoltaic efficiency of the compounds was studied from the simulated electronic spectra. The compound was found to interact with graphene and fullerene, to form molecular self-assembly. These self-assemblies showed tremendous enhancement in various physicochemical properties when compared with its constituents. The nature of the interactions between studied chemical species was discussed with the help of chemical reactivity principles. Biological activity of the compounds was predicted using molecular docking studies. It is interesting to see that on adsorption with a graphene/fullerene surface, all adsorbed complex shows enhancement in the Raman activity giving surface enhanced Raman spectra (SERS). This can be used for the detection of these drugs in a pharmacological or biological sample. Interestingly the graphene/fullerene drug molecular assembly shows enhanced biological activity when compared with individual drug molecules. Graphical abstract.

Zn(II) Complex of Plant Phenolic Chlorogenic Acid: Antioxidant, Antimicrobial and Structural Studies.

The structure of the Zn(II) complex of 5-caffeoylquinic acid (chlorogenic acid, 5-CQA) and the type of interaction between the Zn(II) cation and the ligand were studied by means of various experimental and theoretical methods, i.e., electronic absorption spectroscopy UV/Vis, infrared spectroscopy FT-IR, elemental, thermogravimetric and density functional theory (DFT) calculations at B3LYP/6-31G(d) level. DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), FRAP (ferric reducing antioxidant power), CUPRAC (cupric reducing antioxidant power) and trolox oxidation assays were applied in study of the anti-/pro-oxidant properties of Zn(II) 5-CQA and 5-CQA. The antimicrobial activity of these compounds against Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, Salmonella enteritidis and Candida albicans was tested. An effect of Zn(II) chelation by chlorogenic acid on the anti-/pro-oxidant and antimicrobial activities of the ligand was discussed. Moreover, the mechanism of the antioxidant properties of Zn(II) 5-CQA and 5-CQA were studied on the basis of the theoretical energy descriptors and thermochemical parameters. Zn(II) chlorogenate showed better antioxidant activity than chlorogenic acid and commonly applied natural (L-ascorbic acid) and synthetic antioxidants (butylated hydroxyanisol (BHA) and butylated hydroxytoluene (BHT)). The pro-oxidant activity of Zn(II) 5-CQA was higher than the ligand and increased with the rise of the compound concentration The type of Zn(II) coordination by the chlorogenate ligand strongly affected the antioxidant activity of the complex.

Predicting the Catalytic Activity of Surface Oxidation Reactions by Ionization Energies

Developing a descriptor to understand the reactivity of a catalyst is critical in achieving the rational design of heterogeneous catalysts. Ideally, the descriptor should be simple, predictive, as ...

Spectral analysis and DFT investigation of some benzopyran analogues and their self-assemblies with graphene

Spectroscopic analysis and different quantum mechanical studies of four phramaceutically active flavanoid compounds, 5,7-dihydroxy-3-(4-hydroxyphenyl)-4H-chromen-4-one (genistein) (F1), 5,7-dihydroxy-2-(4-hydroxyphenyl)-4H-chromen-4-one (apigenin) (F2), 5,6,7-trihydroxy-2-phenyl-4H-chromen-4-one (baicalein) (F3) and 2-(3,4-dihydroxyphenyl)-3,7-dihydroxy-4H-chromen-4-one (fisetin) (F4) are reported in this manuscript using DFT/B3LYP/6-311++G(d,p) level of theory. Simulated IR spectrum of these compounds was compared with experimentally available data, and essential functional group assignments were made. NBO studies helped to study the various intramolecular electron delocalisation possible in the molecule. We also report the frontier orbital properties and other derived local energy descriptors which talks about the relative stability and reactivity of the compounds. The photovoltaic efficiency of the compounds was studied from the simulated electronic spectra. The compound was found to interact with graphene, to form molecular self-assembly. These self-assemblies showed tremendous enhancement in various physicochemical properties when compared with its constituents. Biological activity of the compounds were predicted using molecular docking studies.

Structural study of letrozole and metronidazole and formation of self-assembly with graphene and fullerene with the enhancement of physical, chemical and biological activities

Letrozole and metronidazole are two commonly used drugs for the management of breast cancer and parasitic infections, respectively. This manuscript attempts to study their structure, geometry, search for stable conformers using relaxed potential energy scan, spectral properties, quantum mechanical properties like energy and reactivity descriptors, intra molecular electron transfer properties, non-linear properties etc using various computational tools. It is found that these compounds will form a self-assembly with graphene sheets and fullerenes and exhibit a surface-enhanced Raman spectra and enhancement in non-linear optical properties when compared to the single molecule. The electronic absorption behavior of the compounds was studied using TD-DFT method. Global chemical reactivity descriptors and activity sites toward electrophilic and nucleophilic attack have been discussed. Studies of intra molecular electron transfer gave information about the relative stability of the compounds. Molecular docking studies indicate that the pure compounds and their self-assemblies with graphene have excellent biological activities. Communicated by Ramaswamy H. Sarma

Stretching force constants as descriptors of energy and geometry of F···HF hydrogen bonds.

In this work applicability of proton donor group stretching vibration force constants ks and intermolecular stretching force constants kσ for evaluations of hydrogen bond strength and geometry are discussed. For a set of 30 complexes with F···HF hydrogen bonds in a wide range 0.5-48kcal/mol by means of quantum chemical calculations equilibrium geometries, complexation energies, vibrational frequencies and corresponding force constants were calculated (MP2/aug-cc-pVTZ). It is shown, that properties of a hydrogen bond are more strictly correlated with the values of force constants than with vibrational frequencies. Easy-to-use equations for estimations of hydrogen bond energy ∆E and geometry (rFH, rFF) based on ks and kσ values are proposed.

Structural, electronic and catalytic properties of bimetallic PtnAgn (n=1–7) clusters

The geometrical, electronic and catalytic properties of PtnAgn (n = 1–7) clusters are investigated by means of density functional theory (DFT) computations. The ground state structures are obtained by a structure search procedure based in the simulated annealing method. In general, the PtnAgn clusters adopt structures with Pt cluster motifs at the central position surrounded by silver islands. We found that the Pt4Ag4 and Pt6Ag6 clusters have a closed shell geometric structure and are the most stable clusters in this series. The bimetallic cluster reactivity is investigated by using the ionization potential, electron affinity, the d-band center, and the adsorption energy descriptors, respectively. However, it turns out that the reactivity of these systems is more sensitive to the chemical element on the cluster surface exhibiting a local reactivity. The different reactive sites on the cluster surface can be explained by the molecular electrostatic potential surface. In the PtnAgn alloys, the Pt species perform similar interactions with a CO molecule in comparison to the unary Pt clusters, whereas the Ag species issue weaker interactions, increasing the catalyst resistance. In this context, the bimetallic clusters may serve as potential candidates for hydrogenation reactions. Furthermore, the distinct charge reorganization on the PtnAgn alloys is useful for incorporating a lower number of noble metals in order to achieve an increased catalytic and selectivity capabilities. Theoretical data on the infrared spectra of the clusters is also provided.

Identification of novel inhibitory candidates against two major Flavivirus pathogens via CADD protocols: in silico analysis of phytochemical binding, reactivity, and pharmacokinetics against NS5 from ZIKV and DENV

Zika and dengue virus are flaviviruses which with the passage of time have become a serious challenge affecting millions of people around the world. To lessen the impact of these viral infections globally and to combat these virus-associated epidemics in the future, new medical findings and pharmacological approaches are needed. The phytochemicals extracted from a variety of various plants consist of amazing medicinal properties and can be used in the production of novel anti-viral drugs. The two domains of NS5 protein (NS5 MTase and NS5 RdRp) can be targeted in the clinical trials to produce effective novel inhibitors against Zika and dengue fever. Herein, we aim at using a wide variety of phytochemicals (n = 2035) as inhibitors against NS5 protein from DENV and ZIKV. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of the selected compounds were studied to evaluate the pharmacological characteristics. Molecular docking was carried out to determine the binding properties of these ligands with NS5 protein and reactivity was analyzed using molecular orbital energy descriptors. A total of 108 compounds were found suitable in ADMET and from 108 compounds, 35 compounds with the highest in the case of NS5 MTase from ZIKV and DENV were selected. While for NS5 RdRp, 29 compounds were selected. Those compounds, which exhibited remarkable binding affinities values against the proteins of both the ZIKV and 4 serotypes of DENV simultaneously, were predominantly selected in this study. It is concluded that these compounds can be used in clinical trials for the production of a mutual anti-viral drug against both DENV and ZIKV.

Machine-Learning Assisted Screening of Energetic Materials.

In this work, machine learning (ML), materials informatics (MI), and thermochemical data are combined to screen potential candidates of energetic materials. To directly characterize energetic performance, the heat of explosion ΔHe is used as the target property. The critical descriptors of cohesive energy, averaged over all constituent elements and the oxygen balance, are found by forward stepwise selection from a large number of possible descriptors. With them and a theoretically labeled ΔHe training data set, a satisfactory surrogate ML model is trained. The ML model is applied to large databases ICSD and PubChem to predict ΔHe. At the gross-level filtering by the ML model, 2732 molecular candidates based on carbon, hydrogen, nitrogen, and oxygen (CHNO) with high ΔHe values are predicted. Afterward, a fine-level thermochemical screening is carried out on the 2732 materials, resulting in 262 candidates with TNT equivalent power index Pe(TNT) greater than 1.5. Raising Pe(TNT) further to larger than 1.8, 29 potential candidates are found from the 2732 materials, all are new to the current reservoir of well-known energetic materials.

Rediscovering Tuning Product Selectivity by an Energy Descriptor: CH4 Formation and C1–C1 Coupling on the FCC Co Surface

Despite extensive research work, how to control the chain growth by C1–C1 coupling on the catalysts of Fischer–Tropsch synthesis (FTS) remains an unsolved problem. The activity, chain growth, and s...

Texture Evaluation of Automotive Coatings by Means of a Gonio-Hyperspectral Imaging System Based on Light-Emitting Diodes

Sparkle and graininess are textural effects that appear as intrinsic spatial features of coatings containing goniochromatic pigments, whereas others such as mottling are undesired outcomes. In this study, we present new methods for the evaluation of sparkle, graininess and mottling of automotive coatings through images acquired with a novel gonio-hyperspectral imaging system based on light-emitting diodes with extended spectral sensitivity beyond the visible range (368–1309 nm). A novel analysis of sparkle that considered the amount of sparkling spots was used. Graininess was quantified through a novel statistical descriptor based on the energy descriptor computed from the histogram. A new index was proposed for an enhanced detection of mottling based on the analysis of striping, which was better observed and quantified in the infrared range. Spectral assessments showed a strong relationship with color and spectral reflectance for graininess and mottling. In conclusion, the results showed that these new spatial and spectral methods are a suitable, alternative and potential approach for the assessment of these textural features.