Journal of chemical information and modeling
Dec 15, 2025
Chemical reactions in solution are central to biological function, synthetic chemistry, and materials design. Accurate modeling of these systems is essential for obtaining mechanistic insights but remains computationally demanding. Hybrid machine-lea...
Reliable prediction of drug solubility in supercritical carbon dioxide (scCO₂) is crucial for the efficient design of pharmaceutical processes, including particle engineering and supercritical fluid-based extraction. Given that experimental determina...
This study focuses on predicting the solubility of paracetamol and density of solvent using temperature (T) and pressure (P) as inputs. The process for production of the drug is supercritical technique in which the focus was on theoretical investigat...
Journal of chemical information and modeling
Sep 11, 2025
Transferable neural network potentials (NNP) are undergoing rapid development. Many practical applications of NNPs focus on single molecules; e.g., using NNPs as a fast replacement for quantum chemical methods for dihedral angle scans in force field ...
Journal of chemical information and modeling
Sep 3, 2025
Existing methods for adsorption energy prediction primarily focus on individual molecules or static molecular pairs, lacking the capabilities to model the diverse spatial configurations found in complex solution systems. While traditional data sets a...
Analysis of small-molecule drug solubility in binary solvents at different temperatures was carried out via several machine learning models and integration of models to optimize. We investigated the solubility of rivaroxaban in both dichloromethane a...
Journal of chemical information and modeling
Aug 4, 2025
Carbon capture through physical solvents reduces energy consumption and lowers environmental impact compared with conventional chemical absorption methods. Typical properties for solvent screening are solubility and selectivity. However, they require...
Journal of chemical information and modeling
Jul 22, 2025
Automated data curation for niche scientific topics, where data quality and contextual accuracy are paramount, poses significant challenges. Bidirectional contextual models such as BERT and ELMo excel in contextual understanding and determinism. Howe...
Journal of chemical information and modeling
Jul 10, 2025
Solubility prediction is crucial for drug development and materials science, yet existing models struggle with generalizability across diverse solvents and temperatures. This study develops a novel solubility prediction model, DMPNN-MoE, which integr...
For analysis of crystallization, the solubility of drug in solvents should be correlated to input parameters. In this investigation, the solubility of salicylic acid as drug model in a variety of solvents is predicted through the utilization of multi...
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