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Prediction of Supercritical CO₂ Solubility with a Thermodynamics-Conditioned Equivariant Graph Neural Network Model
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inferredcites →https://doi.org/10.1002/(sici)1096-987x(199604)17:5/6<490::aid-jcc1>3.0.co;2-popenalex-snapshot
Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94
inferredcites →https://doi.org/10.1007/978-3-031-37196-7_2openalex-snapshot
Graph Neural Networks for Molecules
inferredcites →https://doi.org/10.1007/s12393-023-09343-5openalex-snapshot
Solubility of Food-Relevant Substances in Pure and Modified Supercritical Carbon Dioxide: Experimental Data (2011–Present), Modeling, and Related Applications
inferredcites →https://doi.org/10.1016/0040-4020(80)80168-2openalex-snapshot
Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges
inferredcites →https://doi.org/10.1016/j.chroma.2009.12.019openalex-snapshot
Supercritical fluid extraction: Recent advances and applications
inferredcites →https://doi.org/10.1016/j.ddtec.2020.11.009openalex-snapshot
A compact review of molecular property prediction with graph neural networks
inferredcites →https://doi.org/10.1016/j.ejps.2025.107321openalex-snapshot
High-fidelity prediction of drug solubility in supercritical CO₂ for pharmaceutical applications using advanced computational modeling
inferredcites →https://doi.org/10.1016/j.fluid.2004.01.009openalex-snapshot
Binary and ternary solubilities of disperse dyes and their blend in supercritical carbon dioxide
inferredcites →https://doi.org/10.1016/j.supflu.2003.07.002openalex-snapshot
Solubilities of two steroid drugs and their mixtures in supercritical carbon dioxide
inferredcites →https://doi.org/10.1016/s0378-3812(03)00206-1openalex-snapshot
The high CO2-solubility of per-acetylated α-, β-, and γ-cyclodextrin
inferredcites →https://doi.org/10.1016/s0896-8446(02)00083-9openalex-snapshot
Solubility of 2-ethyl-hexyl-2-ethyl hexanoate in binary and quaternary systems in supercritical carbon dioxide
inferredcites →https://doi.org/10.1016/s0896-8446(03)00116-5openalex-snapshot
Solubility of cholesterol and its esters in supercritical carbon dioxide with and without cosolvents
inferredcites →https://doi.org/10.1016/s0896-8446(04)00112-3openalex-snapshot
Solubility of some inhaled glucocorticoids in supercritical carbon dioxide
inferredcites →https://doi.org/10.1021/acs.iecr.3c03208openalex-snapshot
Prediction of Drug-like Compounds Solubility in Supercritical Carbon Dioxide: A Comparative Study between Classical Density Functional Theory and Machine Learning Approaches
inferredcites →https://doi.org/10.1021/acs.jcim.0c00025openalex-snapshot
Improving Conformer Generation for Small Rings and Macrocycles Based on Distance Geometry and Experimental Torsional-Angle Preferences
inferredcites →https://doi.org/10.1021/acs.jcim.5b00654openalex-snapshot
Better Informed Distance Geometry: Using What We Know To Improve Conformation Generation
inferredcites →https://doi.org/10.1021/acs.jcim.5c00432openalex-snapshot
Improved Solubility Predictions in scCO 2 Using Thermodynamics-Informed Machine Learning Models
inferredcites →https://doi.org/10.1021/acs.jctc.4c01424openalex-snapshot
Analyzing Atomic Interactions in Molecules as Learned by Neural Networks
inferredcites →https://doi.org/10.1021/ci900115yopenalex-snapshot
Comments on the Definition of the Q 2 Parameter for QSAR Validation
inferredcites →https://doi.org/10.1021/j100212a041openalex-snapshot
Solubility of solids and liquids in supercritical gases
inferredcites →https://doi.org/10.1021/ja00051a040openalex-snapshot
UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations
inferredcites →https://doi.org/10.1021/je020218wopenalex-snapshot
Solubilities of the Drugs Benzocaine, Metronidazole Benzoate, and Naproxen in Supercritical Carbon Dioxide
inferredcites →https://doi.org/10.1021/je025575lopenalex-snapshot
Solubility of Artemisinin in Supercritical Carbon Dioxide
inferredcites →https://doi.org/10.1038/s41467-019-08987-4openalex-snapshot
Unmasking Clever Hans predictors and assessing what machines really learn
inferredcites →https://doi.org/10.1038/s41598-024-73543-0openalex-snapshot
Determination of morphine sulfate anti-pain drug solubility in supercritical CO2 with machine learning method
inferredcites →https://doi.org/10.1063/1.555991openalex-snapshot
A New Equation of State for Carbon Dioxide Covering the Fluid Region from the Triple-Point Temperature to 1100 K at Pressures up to 800 MPa
inferredcites →https://doi.org/10.1106/108201302029451openalex-snapshot
Application and Possibilities of Supercritical CO2 Extraction in Food Processing Industry: An Overview
inferredcites →https://doi.org/10.1109/tpami.2021.3115452openalex-snapshot
Higher-Order Explanations of Graph Neural Networks via Relevant Walks
inferredcites →https://doi.org/10.1371/journal.pone.0130140openalex-snapshot
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
inferredcites →https://doi.org/10.3390/molecules31040614openalex-snapshot
Phase Behaviour of Binary Mixtures Involving Near-Critical and Supercritical Carbon Dioxide—A Review
inferredcites →https://doi.org/10.3762/bjoc.10.196openalex-snapshot
Supercritical carbon dioxide: a solvent like no other
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