JBCS

A mixed valence polyoxovanadate and poly(vinyl chloride) forms green homogeneous films, studied by molecular docking.

Ant Colony Optimization method (inspired by the collective behavior of ants in optimizing paths) to optimize one (1D) to five (5D) parameters of an analytical density functional for the ground-state energy of strongly correlated systems. The performance is assessed by the mean relative error (MRE): for 3D and 5D we find MRE ca. 0.8%, an error reduction of 67% compared to the original parametrization (MRE = 2.4%).

Violacein is a natural purple pigment that shows a wide range of bioactivity. The current review addresses different aspects of violacein, such as its production, purification, and biological activities, aiming to enhance its viability for technological applications.

In this paper, the absolute configuration of (+)-hirsutanonol was unambiguously determined by means of optical rotation (OR) and electronic circular dichroism (ECD) chiroptical properties supported by quantum chemical calculations.

Biological results of N-acylhydrazones from isoniazid and aldehydes showed silver(I) complexes with N-acylhydrazones as promising antitubercular drugs with high selectivity index.

This figure represents the physical grinding modifications performed on graphite, using parameters obtained through multivariate analysis, resulting in capacitive graphene and electrochemical tests.

This study investigates the technological reconstruction and chemical composition of fine earthenware from the 18^th and 19^th centuries in Piauí.

Prediction of glycerol electrooxidation potentials using machine learning, with improved feature treatment.

Quantification of polycyclic aromatic hydrocarbons (PAHs) deposited on the personal protective equipment (PPE) of firefighters, during firefighting training.

N-Nitrosamines in cosmetic thermal waters: market analysis and analytical method.

Inorganic nitrogen compounds and BTEX (benzene, toluene, ethylbenzene and xylenes): chemistry of the urban atmosphere and its relationship with air quality and human health.

This review focuses on the development of advanced fluorescent and colorimetric sensors for the detection and removal of cadmium (Cd^II) and chromium (Cr^III,VI) ions from water.

This figure highlights recent advances in the synthesis of bioactive coumarin-1,2,3-triazole hybrids, which show potential in treating infectious diseases, cancer, and Alzheimer's, emphasizing their role in medicinal chemistry.

Kinetic of thermal processes can be accurately determined by combining artificial neural network with thermal analysis techniques.

This figure illustrates the phenol degradation process in a Raceway Pond Reactor using the photo-Fenton reaction. Fe²⁺/H₂O₂ generates hydroxyl radicals (HO•), which degrade phenol into smaller organic acids and CO₂. Sunlight enhances Fe²⁺ regeneration, sustaining radical production. The system ensures continuous degradation through radical propagation and oxidation pathways.

Machine learning uses algorithms and statistical models for defined tasks and learning patterns from data without explicit instructions. Its basic concepts and some applications are reviewed.

A synthesis routine of a mesoporous porphyrin polymer used a block copolymer template-directed method.

Tree core and paired soil samples were collected, digested in a microwave system and analyzed by inductively coupled plasma mass spectrometry (ICP-MS) for their respective total concentrations of Cu, Fe, Mn, Ni, Pb, and Zn. Additionally, soil samples were treated by the Mehlich-1 solution to assess the labile content of the analytes using inductively coupled plasma optical emission spectrometry (ICP-OES).

Steps of graphene oxide (GO)/reduced graphene oxide (rGO) synthesis by electrochemical exfoliation of graphite from discharged batteries due to the use of acidic electrolytes.

Bacillus subtilis TIM27, isolated from mangrove sediments, produced the BiosT27 biosurfactant and the ProT27 subtilisin, exhibiting protease and esterase activities. When tested together as detergent additives, they demonstrated excellent stain removal performance.

A highly efficient hypocrystalline V-P-C catalyst with a porous honeycomb structure is utilized for the continuous production of acrylic acid through glycerol dehydration.

ZnO and Ni-Al-Oxide associated with Ag prismatic nanoplatelets as efficient materials for the photocatalytic degradation of Remazol Black 5 and Methylene Blue.

A review of the functionalities of natural antioxidants with sustainable food packaging.

Representative process of atmospheric degradation study in a semiarid climate of pure poly (butylene adipate-co-terephthalate) films and those with orange oil additives using conventional and machine learning methods.

Phenol degradation was studied by advanced oxidative processes using different approaches and the maxima efficiency obtained was 99% after 120 min.

From chemical compounds to predicting the antitrypanosomal activity of new candidates against Trypanosoma cruzi trypomastigotes.

Machine learning models were used to predict the biological activity of natural products against Schistosoma mansoni. Virtual screening identified 14 promising compounds, which were further analyzed for absorption, distribution, metabolism, excretion and toxicity (ADMET) properties.

This paper advances sustainability by introducing an eco-friendly solvent for perovskite solar cell fabrication, reducing its environmental impact.

This work paper the applications of Natural Language Processing (NLP) and Large Language Models (LLMs) in chemistry and materials science, highlighting their role in chemical entity recognition, reaction prediction, materials discovery, and literature analysis.

Development of a photodynamic inactivation-enhanced air filtration system using nonwoven polypropylene coated with electrospun nanofibers.

The figure illustrates the core components of quantitative structure-activity relationship (QSAR)-Lit, a platform designed to streamline the QSAR modeling process. It encompasses data curation, descriptor calculation, machine learning, and virtual screening, enabling seamless and efficient analysis for drug discovery applications.

A quantum active learning method (QAL) for automatic structural determination of doped materials has been developed and implemented in the QMLMaterial software. QAL uses quantum circuits for data encoding to create quantum machine learning models on-the-fly.

This study employs supervised learning methods, including Partial Least Squares Discriminant Analysis (PLS-DA) with bootstrap resampling and Support Vector Machine (SVM) ensemble, to analyze biogenic volatile organic compounds (BVOCs) emissions in the Atlantic Forest, achieving high classification accuracy.

Full voltammogram analysis through machine learning for enhanced detection in electrochemical immunosensors.

Molecules from the QM-symex database are converted to SMILES (simplified molecular input line entry system) and stored in a new QM-symex-modif dataset with their target properties. The data is processed and used in machine learning models to develop predictive models for photophysical properties.

The blood composition imbalance following coronavirus disease (COVID-19) causes a systematic change in impedance, which can be modelled by multivariate analysis.

Application of machine learning and computational tools to predict antileishmanial activity, emphasizing the synergy of computational and experimental methods in developing novel therapeutic agents.

This study utilizes Quantitative Structure-Activity Relationship (QSAR)-based machine learning models, validated with bioactivity data median inhibitory concentration (IC₅₀) of compounds against Trypanosoma brucei and Trypanosoma cruzi, for screening Food and Drug Administration (FDA)-approved compounds as candidates for repurposing in the treatment of both trypanosomiases.

De novo design of a new lead compound with potential inhibitory effect on monkeypox virus F13 protein (VP37) by deep reinforcement learning and structure-based drug design.

Machine learning combined with virtual screening has enabled the discovery of a significant variety of molecules exhibiting high affinity with shikimate kinase. Subsequent evaluation through molecular dynamics and free energy calculations has facilitated the identification of potential inhibitor candidates.

Machine learning and multivariate statistical analyses identified molecular features correlated with biological activity of phenylpropanoid against Trypanosoma cruzi.