Development of a QSPR Model for Predicting Soil Sorption of Organic Contaminants Using Chemical Data from PaDEL-Descriptor Software

Predicting soil-water partition coefficients of PFAS using machine learning: Model development, interpretation, and validation.

PER: and polyfluoroalkyl substances (PFAS) are environmentally persistent contaminants, yet experimental determination of their soil-water partition coefficients (Kd) remains costly and time-consuming. In this study, five machine-learning regression models were developed using 2057 literature-derived batch adsorption d...

Quantitative structure-retention relationships (QSRR): Effect of experimental variables on QSRR model performance in HPLC - A critical review.

The QSRR modeling framework enables researchers to use molecular descriptors for predicting chromatographic retention, including HPLC retention based on their physicochemical characteristics, as it can predict chromatographic retentions and not only HPLC retention. QSRR models show low transferability between different...

Prediction of solubility of hydrogen in chemicals using QSPR-based machine learning approach: a comparative study

For the first time, a comprehensive and predictive MLR-based QSPR model has been developed for this target and the predictive capability of the MLR-QSPR model was acceptable for training set.

Filling Ecotoxicity Data Gaps for Plasticizers via an Integrated Framework: Toxicity Prediction, Prioritization, and Hazardous Concentration Derivation.

Plasticizers are widely used polymer additives whose release into aquatic environments poses ecological risks, while their structural diversity challenges conventional toxicological assessment. To address this data gap, an integrated modeling framework was established for hazard assessment and prioritization of plastic...

Small-Sample Prediction and Uncertainty Assessment of Soil Organic Carbon Content in Cropland of the Liaohe Plain Based on the TabPFN Model

Soil organic carbon (SOC) is a key indicator of cropland quality, soil fertility, and the carbon sequestration potential of agroecosystems. Accurate characterization of its spatial distribution is essential for black soil conservation and regional soil carbon management. However, regional-scale SOC prediction is often...

Model-dependent variability in environmental exposure assessment of engineered nanomaterials: A comparison of material flow analysis and multimedia environmental fate models.