Transition State Theory-Inspired Neural Network for Estimating the Viscosity of Deep Eutectic Solvents
Liu‐Ying Yu, Gao‐Peng Ren, Xiao‐Jing Hou, Ke‐Jun Wu, Yuchen He
Abstract
of 0.9805). Compared with the traditional machine learning methods, the TSTiNet has better generalization ability and dramatically reduces the maximum relative deviation of prediction under the constraints of the thermodynamic formulation. It requires only the structural information on DESs and is the most accurate and reliable model available for DESs viscosity prediction.
Topics & Concepts
ViscosityArtificial neural networkDeep eutectic solventMultilayer perceptronEutectic systemPerceptronGeneralizationComputer scienceApproximation errorEquation of stateThermodynamicsArtificial intelligenceAlgorithmMaterials scienceMathematicsPhysicsMathematical analysisComposite materialAlloyIonic liquids properties and applicationsPhase Equilibria and ThermodynamicsElectrochemical Analysis and Applications