AIMC Topic: Models, Chemical

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Machine learning prediction of DOC-water partitioning coefficients for organic pollutants from diverse DOM origins.

Environmental science. Processes & impacts Jul 16, 2025
This study aims to improve predictions and understanding of dissolved organic carbon-water partitioning coefficients (), a crucial parameter in environmental risk assessment. A dataset encompassing 709 datapoints across 190 unique organic pollutants ...
Organic Chemicals Environmental Monitoring Machine Learning Models, Chemical Humic Substances Water Pollutants, Chemical Carbon
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Modeling Soil pH at regional scale using environmental covariates and machine learning algorithm.

Environmental monitoring and assessment Jun 24, 2025
Soil pH serves as a critical indicator of soil chemistry and fertility, and mapping its spatial distribution holds significant importance for effective crop management. Digital soil mapping (DSM) is a commonly employed method for making rapid and cos...
Models, Chemical Hydrogen-Ion Concentration Algorithms Soil Environmental Monitoring Support Vector Machine Machine Learning
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Influence of descriptor database selection on modeling retention factors in capillary micellar and microemulsion electrokinetic chromatography using the solvation parameter model.

Journal of chromatography. A Apr 25, 2025
Abraham's solvation parameter model has been widely used to model retention in capillary micellar and microemulsion electrokinetic chromatography systems. To fit or predict retention factors in separation systems experimentally determined compound de...
Databases, Chemical Machine Learning Databases, Factual Emulsions Models, Chemical Chromatography, Micellar Electrokinetic Capillary Micelles
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Transforming molecular cores, substituents, and combinations into structurally diverse compounds using chemical language models.

European journal of medicinal chemistry Apr 10, 2025
Transformer-based chemical language models (CLMs) were derived to generate structurally and topologically diverse embeddings of core structure fragments, substituents, or core/substituent combinations in chemically proper compounds, representing a de...
Drug Design Molecular Structure Models, Chemical
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Explainable no-code OECD-compliant machine learning models to predict the mutagenic activity of polycyclic aromatic hydrocarbons and their radical cation metabolites.

The Science of the total environment Mar 18, 2025
Polycyclic aromatic hydrocarbons (PAHs) are persistent pollutants with well-known genotoxic and mutagenic effects, posing risks to ecosystems and human health. Their hydrophobic nature promotes accumulation in soils and aquatic environments, increasi...
Polycyclic Aromatic Hydrocarbons Mutagens Models, Chemical Environmental Pollutants Organisation for Economic Co-Operation and Development Machine Learning Mutagenicity Tests Risk Assessment Cations Environmental Monitoring
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Data-Driven Modeling and Design of Sustainable High Tg Polymers.

International journal of molecular sciences Mar 18, 2025
This paper develops a machine learning methodology for the rapid and robust prediction of the glass transition temperature (Tg) for polymers for the targeted application of sustainable high-temperature polymers. The machine learning framework combine...
Glass Machine Learning Polymers Models, Chemical Transition Temperature
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Current experimental, statistical, and mechanistic approaches to optimizing biomolecule separations in aqueous two-phase systems.

Journal of chromatography. A Mar 17, 2025
Aqueous two-phase systems (ATPS) have been used to purify a range of biomolecules, including small molecules, monoclonal antibodies, viruses, and whole cells. They are known for selective separations, creating a stabilizing, low-shear environment, an...
Thermodynamics Proteins Models, Chemical Water Models, Statistical
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Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes.

Journal of inorganic biochemistry Mar 10, 2025
Predicting the solubility and lipophilicity of platinum(II, IV) complexes is essential for prioritizing potential anticancer candidates in drug discovery. This study introduces the first publicly available online model for predicting the solubility o...
Antineoplastic Agents Solubility Models, Chemical Organoplatinum Compounds Platinum
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Predicting surface soil pH spatial distribution based on three machine learning methods: a case study of Heilongjiang Province.

Environmental monitoring and assessment Mar 8, 2025
Comprehensive and accurate acquisition of surface soil pH spatial distribution information is essential for monitoring soil degradation and providing scientific guidance for agricultural practices. This study focused on Heilongjiang Province in China...
Models, Chemical Hydrogen-Ion Concentration Environmental Monitoring Support Vector Machine Soil China Machine Learning
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Physics-informed machine learning for automatic model reduction in chemical reaction networks.

Scientific reports Mar 7, 2025
Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computati...
Humans Machine Learning Models, Chemical Algorithms Amyloid beta-Peptides Computer Simulation Kinetics Alzheimer Disease
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