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We present a theoretical interpretation of the oxygen 1s photoelectron spectrum published by Öhrwall et al. [J. Chem. Phys. 123, 054310 (2005)]. A water cluster that contains 200 molecules was simulated at 215 K using the polarizable AMOEBA force field. The force field predicts longer O...O distances at the cluster surface than in the bulk. Comparisons to ab initio molecular dynamics (MD) simulations indicate that the force field underestimates the degree of surface relaxation. By comparing cluster lineshape models, computed from MD simulations, to the experimental spectrum we find further evidence of surface relaxation. [ABSTRACT FROM AUTHOR]

Free neutral methanol clusters produced by adiabatic expansion have been studied by photoelectron spectroscopy and line shape modeling. The results show that clusters belonging to two distinct size regimes can be produced by changing the expansion conditions. While the larger size regime can be well described by line shapes calculated for clusters consisting of hundreds of molecules, the smaller size regime corresponds to methanol oligomers, predominantly of cyclic structure. There is little contribution from dimers to the spectra. [ABSTRACT FROM AUTHOR]

Single-component clusters of methanol and methyl chloride are produced by adiabatic expansion and their carbon 1s photoelectron spectra are recorded by using synchrotron radiation and a high-resolution electron analyzer. The results have shown that the cluster-to-monomer shift in ionization energy and also the width of the cluster peak are used for distinguishing between hydrogen bonding and weaker electrostatic interactions.

The effective attenuation length (?) is determined to 5.7 ± 1.1 Å at an electronic kinetic energy of 30 eV for carbon disulfide, CS2, from sulphur 2p photoelectron spectroscopy and lineshape modelling of CS2 clusters at a temperature of 150-170 K. The present approach is based on exploring the relation between ? and the cluster-monomer chemical shift and width of the cluster peak. A priori knowledge of the cluster temperature is required. [ABSTRACT FROM AUTHOR]

Abstract: Single-component clusters of methyl chloride and methyl bromide have been produced by adiabatic expansion and their C 1s, Cl 2p and Br 3d photoelectron spectra recorded using synchrotron radiation and a high-resolution electron analyzer. The experimentally observed cluster-to-monomer shifts in core-level ionization energies are interpreted in terms of theoretical models based on molecular dynamics (MD) in conjunction with polarizable force fields developed and validated in the course of this work. MD simulations have also been used to explore the global and local structure of the clusters, providing evidence for a predominance of anti-parallel, head-to-tail arrangement of neighboring molecules. Whereas the cluster-to-monomer shifts are strongly dominated by polarization effects, the polarization contribution is very similar for ionization of carbon and the halogen, respectively. The difference in cluster shifts between the two ionization sites within the same molecule, C vs. Cl or C vs. Br, is thus determined by permanent electrostatic moments, i.e. the magnitude and direction of the permanent dipole moment and the local alignment of dipoles. [Copyright &y& Elsevier]

In this study, we evaluated the physicochemical properties related to the previously reported anticancer activity of a dataset comprising thirty 1,2-dihydropyridine derivatives. We utilized Principal Component Analysis (PCA) to identify the most significant influencing factors. The PCA analysis showed that the first two principal components accounted for 59.91% of the total variance, indicating a strong correlation between the molecules and specific descriptors. Among the 239 descriptors analyzed, 18 were positively correlated with anticancer activity, clustering with the 12 most active compounds based on their IC 50 values. Six of these variables-LogP, Csp3, b_1rotN, LogS, TPSA, and lip_don-are related to drug-likeness potential. Thus, we then ranked the 12 compounds according to these six variables and excluded those violating the drug-likeness criteria, resulting in a shortlist of nine compounds. Next, we investigated the binding affinity of these nine shortlisted compounds with the use of molecular docking towards the PIM-1 Kinase enzyme (PDB: 2OBJ), which is overexpressed in various cancer cells. Compound 6 exhibited the best docking score among the docked compounds, with a docking score of -11.77 kcal/mol, compared to -12.08 kcal/mol for the reference PIM-1 kinase inhibitor, 6-(5-bromo-2-hydroxyphenyl)-2-oxo-4-phenyl-1,2-dihydropyridine-3-carbonitrile. To discover new PIM-1 kinase inhibitors, we designed nine novel compounds featuring hybrid structures of compound 6 and the reference inhibitor. Among these, compound 31 displayed the best binding affinity, with a docking score of -13.11 kcal/mol. Additionally, we performed PubChem database mining using the structure of compound 6 and the similarity search tool, identifying 16 structurally related compounds with various reported biological properties. Among these, compound 52 exhibited the best binding affinity, with a docking score of -13.03 kcal/mol. Finally, molecular dynamics (MD) studies were conducted to confirm the stability of the protein-ligand complexes obtained from docking the studied compounds to PIM-1 kinase, validating the potential of these compounds as PIM-1 kinase inhibitors.

Water scarcity is a growing global issue, particularly in areas with limited freshwater sources, urging for sustainable water management practices to insure equitable access for all people. One way to address this problem is to implement advanced methods for treating existing contaminated water to offer more clean water. Adsorption through membranes technology is an important water treatment technique, and nanocellulose (NC)-, chitosan (CS)-, and graphene (G)- based aerogels are considered good adsorbents. To estimate the efficiency of dye removal for the mentioned aerogels, we intend to use an unsupervised machine learning approach known as "Principal Component Analysis". PCA showed that the chitosan-based ones have the lowest regeneration efficiencies, along with a moderate number of regenerations. NC2, NC9, and G5 are preferred where there is high adsorption energy to the membrane, and high porosities could be tolerated, but this allows lower removal efficiencies of dye contaminants. NC3, NC5, NC6, and NC11 have high removal efficiencies even with low porosities and surface area. In brief, PCA presents a powerful tool to unravel the efficiency of aerogels towards dye removal. Hence, several conditions need to be considered when employing or even manufacturing the investigated aerogels.

Water scarcity is a global problem affecting millions of people. It can lead to severe economic, social, and environmental consequences. It can also have several impacts on agriculture, industry, and households, leading to a decrease in human quality of life. To address water scarcity, governments, communities, and individuals must work in synergy for the sake of water resources conservation and the implementation of sustainable water management practices. Following this urge, the enhancement of water treatment processes and the development of novel ones is a must. Here, we have investigated the potential of the applicability of "Green Aerogels" in water treatment's ion removal section. Three families of aerogels originating from nanocellulose (NC), chitosan (CS), and graphene (G) are investigated. In order to reveal the difference between aerogel samples in-hand, a "Principal Component Analysis" (PCA) has been performed on the physical/chemical properties of aerogels, from one side, and the adsorption features, from another side. Several approaches and data pre-treatments have been considered to overcome any bias of the statistical method. Following the different followed approaches, the aerogel samples were located in the center of the biplot and were surrounded by different physical/chemical and adsorption properties. This would probably indicate a similar efficiency in the ion removal of the aerogels in-hand, whether they were nanocellulose-based, chitosan-based, or even graphene-based. In brief, PCA has shown a similar efficiency of all the investigated aerogels towards ion removal. The advantage of this method is its capacity to engage and seek similarities/dissimilarities between multiple factors, with the elimination of the shortcomings for the tedious and time-consuming bidimensional data visualization.

Water pollution is caused by multiple factors, such as industrial dye wastewater. Dye-contaminated water can be treated using hydrogels as adsorbent materials. Recently, composite hydrogels containing metal oxide nanoparticles (MONPs) have been used extensively in wastewater remediation. In this study, we use a statistical and artificial intelligence method, based on principal component analysis (PCA) with different applied parameters, to evaluate the adsorption efficiency of 27 different MONP composite hydrogels for wastewater dye treatment. PCA showed that the hydrogel composites CTS@Fe 3 O 4 , PAAm/TiO 2 , and PEGDMA-rGO/Fe 3 O 4 @cellulose should be used in situations involving high pH, time to reach equilibrium, and adsorption capacity. However, as the composites PAAm-co-AAc/TiO 2 , PVPA/Fe 3 O 4 @SiO 2 , PMOA/ATP/Fe 3 O 4 , and PVPA/Fe 3 O 4 @SiO 2 , are preferred when all physical and chemical properties investigated have low magnitudes. To conclude, PCA is a strong method for highlighting the essential factors affecting hydrogel composite selection for dye-contaminated water treatment.

Industrial dye wastewater is one of the major water pollution problems. Adsorbent materials are promising strategies for the removal of water dye contaminants. Herein, we provide a statistical and artificial intelligence study to evaluate the adsorption efficiency of graphene oxide-based hydrogels in wastewater dye removal by applying Principal Component Analysis (PCA). This study aims to assess the adsorption quality of 35 different hydrogels. We adopted different approaches and showed the pros and cons of each one of them. PCA showed that alginate graphene oxide-based hydrogel (without polyvinyl alcohol) had better tolerance in a basic medium and provided higher adsorption capacity. Polyvinyl alcohol sulfonated graphene oxide-based hydrogels are suitable when higher adsorbent doses are required. In conclusion, PCA represents a robust way to delineate factors affecting hydrogel selection for pollutant removal from aqueous solutions.

Squeezing flow is a flow where the material is squeezed out or disfigured within two parallel plates. Such flow is beneficial in various fields, for instance, in welding engineering and rheometry. The current study investigates the squeezing flow of a hybrid nanofluid (propylene glycol-water mixture combined with paraffin wax-sand) between two parallel plates with activation energy and entropy generation. The governing equations are converted into ordinary differential equations using appropriate similarity transformations. The shooting strategy (combined with Runge-Kutta fourth order method) is applied to solve these transformed equations. The results of the conducted parametric study are explained and revealed in graphs. This study uses a statistical tool (correlation coefficient) to illustrate the impact of the relevant parameters on the engineering parameters of interest, such as the surface friction factor at both plates. This study concludes that the squeezing number intensifies the velocity profiles, and the rotating parameter decreases the fluid velocity. In addition, the magnetic field, rotation parameter, and nanoparticle volumetric parameter have a strong negative relationship with the friction factor at the lower plate. Furthermore, heat source has a strong negative relationship with heat transfer rate near the lower plate, and a strong positive correlation with the same phenomena near the upper plate. In conclusion, the current study reveals that the entropy generation is increased with the Brinkman number and reduced with the squeezing parameter. Moreover, the results of the current study verify and show a decent agreement with the data from earlier published research outcomes.