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RESEARCH PAPER · Energy · 2019

Machine learning for predicting thermodynamic properties of pure fluids and their mixtures

Yuanbin Liu, Weixiang Hong, Bing Cao

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Machine learning for predicting thermodynamic properties of pure fluids and their mixturesOriginalMolecular dynamics simulation and theoretical study on heat capacities of supercritical H2O/CO2 mixtures35Thermodynamic models for H2O–CO2–H2 mixtures in near-critical and supercritical regions of water21Molecular dynamics simulation study used in systems with supercritical water17Viscosity Measurements of the H2–CO2, H2–CO2–CH4, and H2–H2O Mixtures and the H2–CO2–CH4–CO–H2O System at 280–924 K and 0.7–33.1 MPa with a Capillary Apparatus44Thermodynamic Calculations of the Critical Points of the H2–CO2–CH4–CO–H2O System9Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid33PVT Measurements of the H 2 –CO 2 –CH 4 –CO–H 2 O System at 740–939 K and 18.1–34.7 MPa with an Isochoric Apparatus and the Development of a Virial Equation of State14Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O398A data-driven model for thermodynamic properties of a steam generator under cycling operation22A machine learning model for predicting the minimum miscibility pressure of CO2 and crude oil system based on a support vector machine algorithm approach110A co-training style semi-supervised artificial neural network modeling and its application in thermal conductivity prediction of polymeric composites filled with BN sheets32Predicting entropy and heat capacity of hydrocarbons using machine learning54Machine learning approach for the prediction and optimization of thermal transport properties71Open Catalyst 2020 (OC20) Dataset and Community Challenges765A Review of Experimental Researches on the Thermophysical Properties of Hydrogen-Containing Mixtures at High Temperatures and High Pressures13Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning1Aviation Turbine Fuel Thermal Conductivity: A Predictive Approach Using Entropy Scaling-Guided Machine Learning with Experimental Validation12Multiscale Graph Attention Neural Networks for Mapping Materials and Molecules beyond Short-Range Interatomic Correlations0Modeling the Solubility of Sulfur in Sour Gas Mixtures Using Improved Support Vector Machine Methods12Multi support vector models to estimate solubility of Busulfan drug in supercritical carbon dioxide31Predicting Diffusion Coefficients of Binary and Ternary Supercritical Water Mixtures via Machine and Transfer Learning with Deep Neural Network26MolNet‐3D: Deep Learning of Molecular Representations and Properties from 3D Topography7Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review65The calibration for many-body dissipative particle dynamics by using back-propagation neural networks1Machine learning of consistent thermodynamic models using automatic differentiation33Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks8Enhancing thermal transport in multilayer structures: A molecular dynamics study on Lennard-Jones solids13Machine learning-based optimization of air-cooled heat sinks24Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization10Dielectric constant prediction of pure organic liquids and their mixtures with water based on interpretable machine learning22A molecular dynamics study of evaporation of multicomponent stationary and moving fuel droplets in multicomponent ambient gases under supercritical conditions10Towards predicting liquid fuel physicochemical properties using molecular dynamics guided machine learning models28Predicting gas production by supercritical water gasification of coal using machine learning54A machine learning approach for the surrogate modeling of uncertain distributed process engineering models20PREDICTING DRY GAS SEALS RELIABILITY WITH MACHINE LEARNING TECHNIQUES DEVELOPED FROM SCARCE DATA0Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods17Application of data mining in gas injection methods2Estimation of Breakdown Voltage of Epoxy/SiO2 Nanocomposites Insulators Using Machine Learning Algorithm0Neuro-fuzzy Approach based Prediction of Thermodynamic Properties of Steam4A Diversified End-to-End Machine Learning Approach for Thermo-Fluids’ Properties Prediction1Machine Learning Applications in Chemical Kinetics and Thermochemistry9SPT-NRTL: A physics-guided machine learning model to predict thermodynamically consistent activity coefficients73Self-heating optimization of integrated system of supercritical water gasification of biomass for power generation using artificial neural network combined with process simulation12Combining Machine Learning with Physical Knowledge in Thermodynamic Modeling of Fluid Mixtures73Assessment of machine learning algorithms for predicting autoignition and ignition delay time in microscale supercritical water oxidation process13Acceleration of Numerical Simulations with Deep Learning : Application to Thermodynamic Equilibrium Calculations0Applications of machine learning in supercritical fluids research47Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy40Data-driven methods for diffusivity prediction in nuclear fuels14A data-driven model to determine the infiltration characteristics of air curtains at building entrances10Dielectric and Mechanical Properties Improvement of High Voltage XLPE Using Micro and Nano Aluminum Oxide Filler0Transient Flow Characteristics of High-Pressure Hydrogen-Containing Mixtures During Discharge Through Orifices0Graph attention neural networks for mapping materials and molecules beyond short-range interatomic correlations7Revolutionizing physics: a comprehensive survey of machine learning applications25Strategy of Coupling Artificial Intelligence with Thermodynamic Mechanism for Predicting Complex Polymer Viscosities17A bayesian deep learning-based approach to group contribution methods: A study on cannabinoids and terpenes2Deep-learning-based acceleration of critical point calculations3Leveraging High-throughput Molecular Simulations and Machine Learning for Formulation Design1Machine Learning Assisted Discovery of Efficient MOFs for One-Step C2H4 Purification from Ternary C2H2/C2H4/C2H6 Mixtures3Data-driven approach augmented by attention mechanism in critical and boiling thermophysical properties prediction of fluorine/chlorine-based refrigerants14Process Systems Engineering Tools for Optimization of Trained Machine Learning Models: Comparative and Perspective18NNEoS : Neural network-based thermodynamically consistent equation of state for fast and accurate flash calculations9A Method for Efficiently Predicting the Radial Distribution Function and Osmotic Coefficients of Aqueous Electrolyte Solutions8Molecular dynamics simulations on salt deposition and nucleation in supercritical water7Development and construction of a cost-effective non-contact instrument for measuring the dielectric constant of liquids0Impact of inhibition mechanisms, automation, and computational models on the discovery of organic corrosion inhibitors64Machine Learning for Fluid Thermodynamics: State of the Art and Open Challenges5Understanding the language of molecules: predicting pure component parameters for the PC-SAFT equation of state from SMILES23Assessing suitability of glycerol-derived green solvent for the separation of n-hexane + ethanol azeotropic mixture, accompanied by VLE studies using machine learning10Explicit-model exploring framework integrating thermodynamic principles and interpretable machine learning in predicting gaseous speed of sound7Gaseous PVTx Properties of the CO2–N2O Binary Mixture: Experiment and Simulation1Leveraging high-throughput molecular simulations and machine learning for the design of chemical mixtures18Thermophysical property prediction of supercritical multiple mixtures fluid by molecular dynamics simulation3Study on the Effect of the Electron Density-Characterized Groups on the Nitrogen Transformation during Coal Pyrolysis0Machine learning models for volumetric swelling in uranium nitride3Sol-gel auto-combustion synthesized ZnMn2O4 for efficient photocatalytic Congo red degradation: structural, kinetics, computational, and ecotoxicity analyses14Machine learning model of plant fiber/PLA composite: Prediction and analysis of mechanical strength18Photocatalytic degradation of an organic pollutant using ZnMn2O4/TiO2 heterojunction under solar light11Integrated design of solvent–antisolvent mixtures and crystallization processes powered by machine learning6Tradition of Data-Intensive Use: The Example of Domain Thermophysics. Methods and Algorithms0Development of Surrogate Models for Thermophysical Properties of Petroleum-Based Rocket Kerosene Using BP-ANN Algorithm2Development of a generalizable and interpretable machine learning model for predicting hydrogen production from supercritical water gasification using generative adversarial network data augmentation9Toward a Generalizable Prediction Model of Molten Salt Mixture Density with Chemistry‐Informed Transfer Learning2Thermal conductivity prediction of BN composites based on Enhanced Co-ANN combined with physical attention mechanisms3A physically interpretable machine-learning method in efficiently and explicitly exploring predictive thermodynamic models for mixture working fluids5Research on the prediction model of effective thermal conductivity of marine natural gas hydrate reservoirs based on machine learning0Thermodynamics-Grounded AI-Collaboration Trend in Systematically Exploring Models and Interpretably Predicting Thermophysical Properties for Working Fluids0WITHDRAWN: Kolmogorov-Arnold Networks for Predicting Dense Gas Thermodynamics0Advancing Biodiesel Quality Assessment Using Machine Learning Algorithms: A Mini-Review on Oxidative Stability Prediction and Models Benchmarking1Emerging Advanced Electronic Packaging Materials for Thermal Management in Power Electronics34Thermal conductivity gradation design in alumina-polymer thermal interface materials based on DF-PINN and Bayesian optimisation0Thermodynamic Study of Propyl Propanoate and 1-Alkanols (C 6 –C 10 ): Application of Machine Learning for Prediction of Density of Mixtures2Transient temperature, pressure, and flow characteristics of high-pressure hydrogen-containing mixtures during discharge from an orifice0Prediction of vapor–liquid equilibrium and azeotropic behavior of binary refrigerant blends by machine learning with COSMO-RS-based descriptors1Harnessing Kolmogorov-Arnold networks for refrigerant property prediction: Critical and boiling point analysis0Machine Learning-Based Prediction of Phase Equilibria and Interfacial Properties of Multicomponent CO2 Mixtures with Impurities: Application to CO2 Transportation0HiPrFlame-An ab initio based real-fluid modeling approach for high-pressure combustion-II. Generalization to large saturated alkanes via universal atomic force fields and ML-based property predictions without hard-sphere approximation0Fluid phase behavior under shale nanoconfinement effect: Advances and challenges from molecular simulation0

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  1. Molecular dynamics simulation and theoretical study on heat capacities of supercritical H2O/CO2 mixtures

    Journal of Molecular Liquids · 2019-11-25

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  2. Thermodynamic models for H2O–CO2–H2 mixtures in near-critical and supercritical regions of water

    International Journal of Hydrogen Energy · 2020-01-09

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  3. Molecular dynamics simulation study used in systems with supercritical water

    Reviews in Chemical Engineering · 2020-04-10

    Hui Jin, Weijing Ding, Bin Bai, Changqing Cao

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  4. Viscosity Measurements of the H2–CO2, H2–CO2–CH4, and H2–H2O Mixtures and the H2–CO2–CH4–CO–H2O System at 280–924 K and 0.7–33.1 MPa with a Capillary Apparatus

    Journal of Chemical & Engineering Data · 2020-07-06

    思远 程, Fei Shang, Weigang Ma, Hui Jin, Naoya Sakoda, Xing Zhang, Liejin Guo

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  5. Thermodynamic Calculations of the Critical Points of the H2–CO2–CH4–CO–H2O System

    International Journal of Thermophysics · 2020-08-05

    思远 程, Weigang Ma, Naoya Sakoda, Xing Zhang

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  6. Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid

    The Journal of Chemical Physics · 2020-09-08

    Galen T. Craven, Nicholas Lubbers, Kipton M. Barros, Sergei Tretiak

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  7. PVT Measurements of the H 2 –CO 2 –CH 4 –CO–H 2 O System at 740–939 K and 18.1–34.7 MPa with an Isochoric Apparatus and the Development of a Virial Equation of State

    Journal of Chemical & Engineering Data · 2020-09-30

    思远 程, Fei Shang, Weigang Ma, Hui Jin, Naoya Sakoda, Xing Zhang, Liejin Guo

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  8. Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O3

    The Journal of Chemical Physics · 2020-10-08

    Yuanbin Liu, Jia‐Yue Yang, Gongming Xin, Linhua Liu, Gábor Cśanyi, Bing Cao

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  9. A data-driven model for thermodynamic properties of a steam generator under cycling operation

    Energy · 2020-10-10

    Abhishek Navarkar, Veeraraghava Raju Hasti, Elihu Deneke, Jay P. Gore

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  10. A machine learning model for predicting the minimum miscibility pressure of CO2 and crude oil system based on a support vector machine algorithm approach

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    Hao Chen, Chao Zhang, Ninghong Jia, Ian Duncan, Shenglai Yang, Yongzhi Peter Yang

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  11. A co-training style semi-supervised artificial neural network modeling and its application in thermal conductivity prediction of polymeric composites filled with BN sheets

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  12. Predicting entropy and heat capacity of hydrocarbons using machine learning

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  13. Machine learning approach for the prediction and optimization of thermal transport properties

    Frontiers of Physics · 2021-02-11

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  14. Open Catalyst 2020 (OC20) Dataset and Community Challenges

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  15. A Review of Experimental Researches on the Thermophysical Properties of Hydrogen-Containing Mixtures at High Temperatures and High Pressures

    Journal of Chemical & Engineering Data · 2021-08-18

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  16. Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning

    arXiv (Cornell University) · 2021-10-18

    Rodolfo S. M. Freitas, Ágatha P. F. Lima, Cheng Chen, Fernando Alves Rochinha, Daniel Mira, Xi Jiang

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  17. Aviation Turbine Fuel Thermal Conductivity: A Predictive Approach Using Entropy Scaling-Guided Machine Learning with Experimental Validation

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  18. Multiscale Graph Attention Neural Networks for Mapping Materials and Molecules beyond Short-Range Interatomic Correlations

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  19. Modeling the Solubility of Sulfur in Sour Gas Mixtures Using Improved Support Vector Machine Methods

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  20. Multi support vector models to estimate solubility of Busulfan drug in supercritical carbon dioxide

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  21. Predicting Diffusion Coefficients of Binary and Ternary Supercritical Water Mixtures via Machine and Transfer Learning with Deep Neural Network

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  22. MolNet‐3D: Deep Learning of Molecular Representations and Properties from 3D Topography

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  23. Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review

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  24. The calibration for many-body dissipative particle dynamics by using back-propagation neural networks

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  25. Machine learning of consistent thermodynamic models using automatic differentiation

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  26. Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks

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  27. Enhancing thermal transport in multilayer structures: A molecular dynamics study on Lennard-Jones solids

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  28. Machine learning-based optimization of air-cooled heat sinks

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  29. Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization

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  30. Dielectric constant prediction of pure organic liquids and their mixtures with water based on interpretable machine learning

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  35. PREDICTING DRY GAS SEALS RELIABILITY WITH MACHINE LEARNING TECHNIQUES DEVELOPED FROM SCARCE DATA

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  36. Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods

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  38. Estimation of Breakdown Voltage of Epoxy/SiO2 Nanocomposites Insulators Using Machine Learning Algorithm

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  39. Neuro-fuzzy Approach based Prediction of Thermodynamic Properties of Steam

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  40. A Diversified End-to-End Machine Learning Approach for Thermo-Fluids’ Properties Prediction

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  41. Machine Learning Applications in Chemical Kinetics and Thermochemistry

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  42. SPT-NRTL: A physics-guided machine learning model to predict thermodynamically consistent activity coefficients

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  43. Self-heating optimization of integrated system of supercritical water gasification of biomass for power generation using artificial neural network combined with process simulation

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  45. Assessment of machine learning algorithms for predicting autoignition and ignition delay time in microscale supercritical water oxidation process

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  47. Applications of machine learning in supercritical fluids research

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  48. Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy

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  49. Data-driven methods for diffusivity prediction in nuclear fuels

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  50. A data-driven model to determine the infiltration characteristics of air curtains at building entrances

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