Vibrational Analysis of Manganese(II) Oxalates Hydrates: An In Silico Statistical Approach.

The experimental and computational vibrational study for three different manganese(II) oxalates hydrates was explored. The elucidation of IR and Raman spectra were discussed based on their structural singularity; in the same way, they establish some interesting relations between them in the field of computational and statistical approaches. The density functional theory (DFT) computational approach was conducted for accurate prediction and interpretation of the intermolecular effects based on experimental and calculated IR and Raman spectra in the solid-state data in combination with multivariate statistical technique. The proposed computational scheme was also explored for the case of the isolated-molecule model. The goals of the study were to access the accuracy of the proposed procedure for solid-state calculations along with electron calculations for the isolated molecules and to reveal the similarities within the groups of objects by the cluster analysis (CA) techniques and two-way CA for the data. The presented simulation procedure should be very valuable for exploring and to classify other oxalate compounds.

Chemometric Assessment of Soil Pollution and Pollution Source Apportionment for an Industrially Impacted Region around a Non-Ferrous Metal Smelter in Bulgaria.

The present study deals with the assessment of pollution caused by a large industrial facility using multivariate statistical methods. The primary goal is to classify specific pollution sources and to apportion their involvement in the formation of the total concentration of the chemical parameters being monitored. This aim is accomplished by intelligent data analysis based on cluster analysis, principal component analysis and principal component regression analysis. Five latent factors are found to explain over 80% of the total variance of the system being conditionally named "organic", "non-ferrous smelter", "acidic", "secondary anthropogenic contribution" and "natural" factor. The apportionment models designate the contribution of the identified sources quantitatively and help in the interpretation of risk assessment and management actions. Since the study takes into account pollution uptake from soil to a cabbage plant, the data interpretation could help in introducing biomonitoring aspects of the assessment. The chemometric expertise helps in revealing hidden relationships between the objects and the variables involved to achieve a better understanding of specific pollution events in the soil of a severely industrially impacted region.

Iron oxide nanoparticles - In vivo/in vitro biomedical applications and in silico studies.

The review presents a broad overview of the biomedical applications of surface functionalized iron oxide nanoparticles (IONPs) as magnetic resonance imaging (MRI) agents for sensitive and precise diagnosis tool and synergistic combination with other imaging modalities. Then, the recent progress in therapeutic applications, such as hyperthermia is discussed and the available toxicity data of magnetic nanoparticles concerning in vitro and in vivo biomedical applications are addressed. This review also presents the available computer models using molecular dynamics (MD), Monte Carlo (MC) and density functional theory (DFT), as a basis for a complete understanding of the behaviour and morphology of functionalized IONPs, for improving NPs surface design and expanding the potential applications in nanomedicine.

Chemometrics Expertise in the Links Between Ecotoxicity and Physicochemical Features of Silver Nanoparticles: Environmental Aspects.

Studies of the ecotoxicological aspects of nanomaterials in aquatic environments are scarce. Given the growing variety of nanoparticles (NPs), along with the diversity of aquatic species and environments, the key to promoting sound risk assessment in nanoecotoxicology is understanding the mechanisms that govern the fate of NPs in aquatic environments and their behavior at the NP-biota interface. In this paper, data collected from the literature on ecotoxicological effects observed in aquatic species is discussed and analyzed using multivariate statistics techniques. We expand the knowledge of the environmental impact of silver NPs (AgNPs) by testing the acute toxicity of 47 AgNPs on crustacean eukaryotic organisms (Daphnia magna, Thamnocephalus platyurus, and D. galeata). Physicochemical properties, stabilization agents, toxicological end points, and test media were monitored as adding-outcome factors for the evaluation of environmental effects due to exposure to NPs. The chemometrics expertise performed by the use of hierarchical and nonhierarchical cluster analysis and principal component analysis revealed specific links between the ecotoxicology and the physicochemical features of NPs and helped in creating specific patterns of NPs discriminated by ecotoxicity levels and physicochemical parameters.