In this work, the group contribution method of Chickos et al. was applied to estimate the fusion enthalpy of isonicotinic acid, and the obtained result(29.2 k J·mol^(-1)) showed a large difference with the value(...In this work, the group contribution method of Chickos et al. was applied to estimate the fusion enthalpy of isonicotinic acid, and the obtained result(29.2 k J·mol^(-1)) showed a large difference with the value(135 k J·mol^(-1)) as reported from literatures and as determined by differential scanning calorimetry(DSC). The results of DSC/TG measurement showed that the phase transition of isonicotinic acid from 187.27 °C to277.47 °C underwent a sublimation process, with a sublimation enthalpy of 128.03 k J·mol^(-1). An efficient analytical technique combining pyrolysis and gas chromatography/mass spectrometry(Py-GC/MS) was used to prove this conclusion.展开更多
The artificial neural network (ANN) and the pattern recognition were applied to study the correlation of enthalpies of fusion for divalent rare earth halides with their microstructural parameters,such as ionic radius ...The artificial neural network (ANN) and the pattern recognition were applied to study the correlation of enthalpies of fusion for divalent rare earth halides with their microstructural parameters,such as ionic radius and electronegativity. The model,represented by a back-propagation netal network, was trained with a 12 set of published data for divalent rare earth halides and then was used to predict the unknown ones. Also the criterion equations were ptesented to determine the enthalpies of fuSion for divalent rare earth halides using pattern recognition in mis work. The results from the model in ANN and criterion equations are in very good agreement with reference data.展开更多
For the first time, for different organic and inorganic compounds possessing the plastic crystalline phase, a new semiempirical equation describing dependence of their fusion enthalpies on such physico-chemical quanti...For the first time, for different organic and inorganic compounds possessing the plastic crystalline phase, a new semiempirical equation describing dependence of their fusion enthalpies on such physico-chemical quantities as normal melting temperature, surface tension, molar volume and critical molar volume is received on the base of the principle of corresponding states and the energy equipartition theorem. Moreover, the proposed equation allows one to take into account the particularities of one-particle molecular rotation in the plastic crystalline phase.展开更多
Poly(ε-caprolactone) (PCL) with different molecular weights was synthesized and characterized by a gelpermeation chromatograph equipped with multiple detector. The melting behavior of PCL was also studied. It was fou...Poly(ε-caprolactone) (PCL) with different molecular weights was synthesized and characterized by a gelpermeation chromatograph equipped with multiple detector. The melting behavior of PCL was also studied. It was found thatthe equilibrium melting points (T_m^0) of PCL samples depend on their molecular weights. Wide angle X-ray diffractionmeasurements (WAXD) and DSC measurements showed that the crystals of the high molecular weight PCLs were moreperfect than those of the low molecular weigh ones. These results demonstrate that the concentration of the end groups ofPCL chains is the main factor that influences the melting behavior. The fusion enthalpy per repeating unit (ΔH_u) wasdetermined to be 11.3 kJ/mol for PCL.展开更多
Accurate prediction of molecular fusion properties is critical for energy-efficient material design and sustainable process optimization,yet remains challenging due to data scarcity and complex thermodynamic interdepe...Accurate prediction of molecular fusion properties is critical for energy-efficient material design and sustainable process optimization,yet remains challenging due to data scarcity and complex thermodynamic interdependencies.This work introduces machine learning tools to address these gaps by combining expert-curated molecular descriptors with deep learning.By systematically evaluating statistical machine learning algorithms and attention-based architectures,optimized models are identified:a SMILES-augmented Transformer-Convolutional Neural Network for fusion temperature and a graph attention network for fusion enthalpy.Prediction power is further validated experimentally on four structure diverse compounds(γ-butyrolactone,methyl octanoate,N-phenylbenzenesulfonamide,and triethylene glycol dimethyl ether).Interpretability analyses reveal that these models prioritize key structures in molecules:attention in textbased models focuses on key atoms while that in graph models focuses on key chemical bonds,aligning with empirical thermodynamic evidences.By providing rapid,interpretable fusion property predictions,this framework can support the development of low-energy phase-change materials and sustainable solvent systems,advancing datadriven green chemistry.展开更多
Subcooled liquid solubility is the water solubility for a hypothetical state of liquid. It is an important parameter for multicomponent nonaqueous phase liquids （NAPLs） containing polycyclic aromatic hydrocarbons （...Subcooled liquid solubility is the water solubility for a hypothetical state of liquid. It is an important parameter for multicomponent nonaqueous phase liquids （NAPLs） containing polycyclic aromatic hydrocarbons （PAHs）, which can exist as liquids even though most of the solutes are solid in their pure form at ambient temperature. So far, subcooled liquid solubilities were estimated from the solid water solubility and fugacity ratio of the solid and （subcooled） liquid phase, but rarely derived from experi- mental data. In our study, partitioning batch experiments were performed to determine the subcooled liquid solubility of PAHs in NAPL-water system. For selected PAH, a series of batch experiments were carried out at increased mole fractions of the target component in the NAPL and at a constant NAPL/ water volume ratio. The equilibrium aqueous PAH concentrations were measured with HPLC and/or GC- MS. The suhcooled liquid solubility was derived by extrapolation of the experimental equilibrium aqueous concentration to a mole fraction of unity. With the derived subcooled liquid solubility, the fugacity ratio and enthalpy of fusion of the solute were also estimated. Our results show a good agreement between the experimentally determined and published data.展开更多
文摘In this work, the group contribution method of Chickos et al. was applied to estimate the fusion enthalpy of isonicotinic acid, and the obtained result(29.2 k J·mol^(-1)) showed a large difference with the value(135 k J·mol^(-1)) as reported from literatures and as determined by differential scanning calorimetry(DSC). The results of DSC/TG measurement showed that the phase transition of isonicotinic acid from 187.27 °C to277.47 °C underwent a sublimation process, with a sublimation enthalpy of 128.03 k J·mol^(-1). An efficient analytical technique combining pyrolysis and gas chromatography/mass spectrometry(Py-GC/MS) was used to prove this conclusion.
文摘The artificial neural network (ANN) and the pattern recognition were applied to study the correlation of enthalpies of fusion for divalent rare earth halides with their microstructural parameters,such as ionic radius and electronegativity. The model,represented by a back-propagation netal network, was trained with a 12 set of published data for divalent rare earth halides and then was used to predict the unknown ones. Also the criterion equations were ptesented to determine the enthalpies of fuSion for divalent rare earth halides using pattern recognition in mis work. The results from the model in ANN and criterion equations are in very good agreement with reference data.
文摘For the first time, for different organic and inorganic compounds possessing the plastic crystalline phase, a new semiempirical equation describing dependence of their fusion enthalpies on such physico-chemical quantities as normal melting temperature, surface tension, molar volume and critical molar volume is received on the base of the principle of corresponding states and the energy equipartition theorem. Moreover, the proposed equation allows one to take into account the particularities of one-particle molecular rotation in the plastic crystalline phase.
文摘Poly(ε-caprolactone) (PCL) with different molecular weights was synthesized and characterized by a gelpermeation chromatograph equipped with multiple detector. The melting behavior of PCL was also studied. It was found thatthe equilibrium melting points (T_m^0) of PCL samples depend on their molecular weights. Wide angle X-ray diffractionmeasurements (WAXD) and DSC measurements showed that the crystals of the high molecular weight PCLs were moreperfect than those of the low molecular weigh ones. These results demonstrate that the concentration of the end groups ofPCL chains is the main factor that influences the melting behavior. The fusion enthalpy per repeating unit (ΔH_u) wasdetermined to be 11.3 kJ/mol for PCL.
基金supported by the National Key Research&Development Program of China(Grant No.2024YFA1510302)the National Natural Science Foundation of China(NSFC)(Grant Nos.22478110 and 22208098).
文摘Accurate prediction of molecular fusion properties is critical for energy-efficient material design and sustainable process optimization,yet remains challenging due to data scarcity and complex thermodynamic interdependencies.This work introduces machine learning tools to address these gaps by combining expert-curated molecular descriptors with deep learning.By systematically evaluating statistical machine learning algorithms and attention-based architectures,optimized models are identified:a SMILES-augmented Transformer-Convolutional Neural Network for fusion temperature and a graph attention network for fusion enthalpy.Prediction power is further validated experimentally on four structure diverse compounds(γ-butyrolactone,methyl octanoate,N-phenylbenzenesulfonamide,and triethylene glycol dimethyl ether).Interpretability analyses reveal that these models prioritize key structures in molecules:attention in textbased models focuses on key atoms while that in graph models focuses on key chemical bonds,aligning with empirical thermodynamic evidences.By providing rapid,interpretable fusion property predictions,this framework can support the development of low-energy phase-change materials and sustainable solvent systems,advancing datadriven green chemistry.
基金financial support by the Deutsche Forschungsgemeinschaft as part of the research unit"Transport and Reactions in Porous Media"(HA 3453/6-2)
文摘Subcooled liquid solubility is the water solubility for a hypothetical state of liquid. It is an important parameter for multicomponent nonaqueous phase liquids （NAPLs） containing polycyclic aromatic hydrocarbons （PAHs）, which can exist as liquids even though most of the solutes are solid in their pure form at ambient temperature. So far, subcooled liquid solubilities were estimated from the solid water solubility and fugacity ratio of the solid and （subcooled） liquid phase, but rarely derived from experi- mental data. In our study, partitioning batch experiments were performed to determine the subcooled liquid solubility of PAHs in NAPL-water system. For selected PAH, a series of batch experiments were carried out at increased mole fractions of the target component in the NAPL and at a constant NAPL/ water volume ratio. The equilibrium aqueous PAH concentrations were measured with HPLC and/or GC- MS. The suhcooled liquid solubility was derived by extrapolation of the experimental equilibrium aqueous concentration to a mole fraction of unity. With the derived subcooled liquid solubility, the fugacity ratio and enthalpy of fusion of the solute were also estimated. Our results show a good agreement between the experimentally determined and published data.
