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RESEARCH PAPER · Engineering · 2021

Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats

Maarten R. Dobbelaere, Pieter P. Plehiers, Ruben Van de Vijver, Christian Victor Stevens, Kevin M. Van Geem

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Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and ThreatsOriginalApplication of computational approach in plastic pyrolysis kinetic modelling: a review41Analytics Driving Kinetics: Advanced Mass Spectrometric Characterization of Petroleum Products32Big data analytics opportunities for applications in process engineering18Prediction of Glucose Concentration Hydrolysed from Oil Palm Trunks Using a PLSR-Based Model6A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing78Machine learning for design principles for single atom catalysts towards electrochemical reactions116Process Digital Twin and Its Application in Petrochemical Industry21การประยกตใชโครงขายประสาทเทยมเพอทำนายคาความเขมขนของหอกลนแยกเอทานอลและนำโดยมจำนวนขอมลจำกด0Machine Learning-Based Dynamic Modeling for Process Engineering Applications: A Guideline for Simulation and Prediction from Perceptron to Deep Learning23Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses – A comprehensive study of artificial neural network applications83Hybrid modelling of water resource recovery facilities: status and opportunities70Precise prediction of performance and emission of a waste derived Biogas–Biodiesel powered Dual–Fuel engine using modern ensemble Boosted regression Tree: A critique to Artificial neural network78Utilization of Improved Machine Learning Method Based on Artificial Hummingbird Algorithm to Predict the Tribological Behavior of Cu-Al2O3 Nanocomposites Synthesized by In Situ Method69Comparative evaluation of AI ‐based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe 3 O 4 ‐coated MWCNT hybrid nanofluids for potential application in energy systems57Machine Learning for Physicochemical Property Prediction of Complex Hydrocarbon Mixtures49Predicting Density and Viscosity for Liquid Metals and Alloys Using Machine Learning15Quo vadis multiscale modeling in reaction engineering? – A perspective63Multi-output machine learning models for kinetic data evaluation : A Fischer–Tropsch synthesis case study50Online estimation using dynamic flux balance model and multiparametric programming1Performance analysis of a micro-scale integrated hydrogen production system by analytical approach, machine learning, and response surface methodology22Using scientific machine learning to develop universal differential equation for multicomponent adsorption separation systems19Machine Learning and Data Science in Chemical Engineering30UzADL: Anomaly detection and localization using graph Laplacian matrix-based unsupervised learning method34Machine learning to predict biochar and bio-oil yields from co-pyrolysis of biomass and plastics159Active learning-based exploration of the catalytic pyrolysis of plastic waste34Non‐physical Species in Chemical Kinetic Models: A Case Study of Diazenyl Hydroxy and Diazenyl Peroxide**8Incorporating Machine Learning in Computer-Aided Molecular Design for Fragrance Molecules20Direct prediction of steam cracking products from naphtha bulk properties: Application of the two sub-networks ANN2Intensification of catalytic reactors: A synergic effort of Multiscale Modeling, Machine Learning and Additive Manufacturing40Chemical structure and thermodynamic properties based models for estimating nitrous oxide solubility in ionic Liquids: Equations of state and Machine learning approaches12Neural network-based adaptive control and energy management system of a direct methanol fuel cell in a hybrid renewable power system16Perspectives on Adsorption. What else? A personal view3Theoretical investigations on the liquid-phase molecular separation in isolation and purification of pharmaceutical molecules from aqueous solutions via polymeric membranes10An enhanced Dendritic Neural Algorithm to predict the wear behavior of alumina coated silver reinforced copper nanocomposites71Modeling solubility of oxygen in ionic liquids: Chemical structure-based Machine Learning Systems Compared to Equations of State9Predicting volatile fatty acid synthesis from palm oil mill effluent on an industrial scale10Editorial: Machine learning for chemical processes0Prediction of Tribological Properties of Alumina-Coated, Silver-Reinforced Copper Nanocomposites Using Long Short-Term Model Combined with Golden Jackal Optimization77Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO2 Capture Technologies13Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor18Machine learning coupled with group contribution for predicting the density of deep eutectic solvents33Bayesian tuned kinetic Monte Carlo modeling of polystyrene pyrolysis: Unraveling the pathways to its monomer, dimers, and trimers formation44Review of interpretable machine learning for process industries107Machine learning for surrogate process models of bioproduction pathways36Growth Indexes and Yield Prediction of Summer Maize in China Based on Supervised Machine Learning Method5Extensive Knowledge Distillation Model: An End-to-End Effective Anomaly Detection Model for Real-Time Industrial Applications22Machine Learning Application Guidelines in Flow Assurance1Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a review146Multiscale theoretical tools for in silico macromolecular chemistry and engineering6The Application of Machine Learning in Chemical Engineering: A Literature Review1Towards Machine Learning Applications for Computational Fluid Dynamics Modeling in Chemical Engineering2SPT-NRTL: A physics-guided machine learning model to predict thermodynamically consistent activity coefficients73On the prediction of the mechanical properties of ultrafine grain Al-TiO2 nanocomposites using a modified long-short term memory model with beluga whale optimizer73Iron limitation effect on H2/CO2 biomethanation: Experimental and model analysis15Deep Learning Methods for Small Molecule Drug Discovery: A Survey29Prediction of wear rates of Al-TiO2 nanocomposites using artificial neural network modified with particle swarm optimization algorithm55Achieving Optimal Paper Properties: A Layered Multiscale kMC and LSTM-ANN-Based Control Approach for Kraft Pulping42Predicting overall mass transfer coefficients of CO2 capture into monoethanolamine in spray columns with hybrid machine learning23Swiss CAT+, a Data-driven Infrastructure for Accelerated Catalysts Discovery and Optimization29Machine learning: An effective technical method for future use in assessing the effectiveness of phosphorus-dissolving microbial agroremediation18Machine learning-aided characterization of microbubbles for venturi bubble generator20Machine Learning for Fuel Property Predictions: A Multi-Task and Transfer Learning Approach9A Light Attention-Mixed-Base Deep Learning Architecture toward Process Multivariable Modeling and Knowledge Discovery12Fifth Paradigm in Science: A Case Study of an Intelligence-Driven Material Design16On the understanding and prediction of tribological properties of Al-TiO 2 nanocomposites using artificial neural network33Review of analytical and numerical modeling for pressure retarded osmosis membrane systems39Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review233Machine learning implemented exploration of the adsorption mechanism of carbon dioxide onto porous carbons64Smart laboratory: Building a smart laboratory environment by using AI0Prediction of heavy metals adsorption by hydrochars and identification of critical factors using machine learning algorithms65Transdisciplinary competency-based development in the process engineering subjects: A case study in Brazil12Retention time prediction for chromatographic enantioseparation by quantile geometry-enhanced graph neural network78Computational applications using data driven modeling in process Systems: A review72Machine learning methods for endocrine disrupting potential identification based on single-cell data10Interpretation of Drop Size Predictions from a Random Forest Model Using Local Interpretable Model-Agnostic Explanations (LIME) in a Rotating Disc Contactor10Aprendizado de máquina aplicado à modelagem da permeação de gases em membranas visando a purificação de metano0Machine Learning for Chemistry: Basics and Applications102Active Machine Learning for Chemical Engineers: A Bright Future Lies Ahead!37State of the Art and Outlook of Data Science and Machine Learning in Organic Chemistry1Applications of Machine Learning to Optimizing Polyolefin Manufacturing0Machine learning-based predictive control using on-line model linearization: Application to an experimental electrochemical reactor25The rise of the machines: A state-of-the-art technical review on process modelling and machine learning within hydrogen production with carbon capture36Machine learning in chemical engineering: Hands-on activities30A new semi-empirical correlation for estimating settling dynamics of suspensions in viscoelastic shear-thinning fluids2Optimal hybrid artificial intelligence models for predicting the adsorptive removal of dyes and phenols from aqueous solutions using an amine-functionalized graphene oxide/layered triple hydroxide nanocomposite44Design of a control system for rotating equipment0Modeling and simulation of the enzymatic kinetics for the production of Galactooligosaccharides (GOS) using an Artificial Neural Network hybrid model7Otimização em trocadores de calor usando inteligência artificial: uma abordagem híbrida de redes neurais para a previsão do acúmulo de depósitos e a eficiência do equipamento1Underestimation of alkaline dosage and precipitate amount during water treatment: Role of inorganic carbon and use of PHREEQ-N-AMDTreat4Recent advances in the applications of machine learning methods for heat exchanger modeling—a review52Improved deep bidirectional recurrent neural network for learning the cross-sensitivity rules of gas sensor array32A perspective on data-driven screening and discovery of polymer membranes for gas separation, from the molecular structure to the industrial performance11Abordagens de aprendizado de máquina para prever o equilíbrio de adsorção de gases leves em zeólitas, carvões ativados e redes metalorgânicas0Multi Objective Optimization using Non-Dominated Sort Genetic Algorithm with Artificial Neural Network for Reactive Dividing Wall Column0Ensemble meta machine learning for predicting the adsorption of anionic and cationic dyes from aqueous solutions using Polymer/graphene/clay/MgFeAl-LTH nanocomposite60Estimation of the Surface Free Energy Components for Solid Surfaces: A Machine Learning Approach4Imperative of Integrating Process Safety Education in Chemical Engineering Curricula8Industrial-scale anaerobic Co-digestion (ACoD) of palm oil mill effluent (POME) and decanter cake (DC) for maximizing methane yield: An integrated machine learning and simulation-based economic analysis approach14Optimization in heat exchangers using artificial intelligence: A hybrid neural network approach for predicting deposit accumulation and equipment efficiency0Automatic mechanism generation for the combustion of advanced biofuels: A case study for diethyl ether9Bayesian LSTM framework for the surrogate modeling of process engineering systems16Optimizing coagulant dosage using deep learning models with large-scale data32Responsive CO 2 capture: predictive multi-objective optimisation for managing intermittent flue gas and renewable energy supply7Application of machine learning in chemical engineering: outlook and perspectives31Machine Learning Models for Efficient Adsorption of Congo Red Dye on High-Performance Polyethyleneimine Macroporous Sponge11A Review of Machine Learning for Additive Manufacturing0Accelerated design of nickel-cobalt based catalysts for CO 2 hydrogenation with human-in-the-loop active machine learning17Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis45Machine learning for control of (bio)chemical manufacturing systems7Machine learning in reaction engineering0Modeling the Vapor-Liquid Equilibrium of CO2-H2O-[CNC1Im][NTf2] Blends Using Machine Learning Techniques to Determine Feasible Solvent Conditions for CO2 Absorption in a Gas-Sweetening Unit0Surrogate-based optimisation of process systems to recover resources from wastewater19The forefront of chemical engineering research43Modeling the Viscosity of ChCl-Based Deep Eutectic Solvents and Their Mixtures with Water28Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities101Hybrid data-driven and physics-based modeling for viscosity prediction of ionic liquids18Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey101Machine Learning-Assisted Optimization of Microbubble-Enhanced Cold Plasma Activation for Water Treatment30Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview14Goal‐Oriented Two‐Layered Kernel Models as Automated Surrogates for Surface Kinetics in Reactor Simulations10Quantitative analysis of pyrolysis characteristics and chemical components of tobacco materials based on machine learning6Harnessing artificial intelligence for data-driven energy predictive analytics: A systematic survey towards enhancing sustainability33Development of an electrophotochemical flow microreactor for efficient electrophotocatalytic C-H hydroxylation of benzene to phenol10Accelerated modelling of moisture diffusion controlled drying using coupled physics informed neural network16Machine learning applications in catalytic hydrogenation of carbon dioxide to methanol: A comprehensive review58An embedded deep learning model discrepancy for computational combustion simulations1Machine learning and human learning: a socio-cultural and -material perspective on their relationship and the implications for researching working and learning11Physics‐informed learning of chemical reactor systems using decoupling–coupling training framework16Low-cycle fatigue design for reinforced high-strength concrete under high compressive stress6Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices12Rheological‐based digital approach for gel curve analysis of alcohol ethoxylates1Engineers as Agents of Technological Change: Ethical Challenges of Technology Adoption0Generalizability of empirical correlations for predicting higher heating values of biomass14Machine Learning-Based Regression Model for Detection of Petroleum Engineering Problems1Comparative study of the effectiveness of time series and arima modeling x RNA approach in a Multi Layer Perceptron (MLP) model in predicting fouled in petroleum pre-processing heat exchangers0Application and Prospect of Machine Learning in the Field of Materials and Chemical Engineering1Exploring machine learning applications in chemical production through valorization of biomass, plastics, and petroleum resources: A comprehensive review22Prediction of storm surge in the Pearl River Estuary based on data-driven model17An Improved Machine Learning Model for Pure Component Property Estimation11Artificial intelligence-based surrogate modeling for computational cost-effective optimization of hydrogen liquefaction process14Best Student Classification using Ensemble Random Forest Method2Unlocking Potential in the Chemical Industry Sector: An Innovative SWOT Analysis Study5Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing10Machine Learning Methods to Improve Crystallization through the Prediction of Solute–Solvent Interactions5A comprehensive review towards resilient rainfall forecasting models using artificial intelligence techniques25A unified framework of response surface methodology and coalescing of Firefly with random forest algorithm for enhancing nano-phytoremediation efficiency of chromium via in vitro regenerated aquatic macrophyte coontail (Ceratophyllum demersum L.)9Experimental study of biological wastewater recovery using microbial fuel cell and application of reliability and machine learning to predict the system behavior15Machine learning for open-pit mining: a systematic review24Balancing data-driven insights and human judgment in supply chain management: The role of business intelligence, big data analytics, and artificial intelligence23Prediction of Human Liver Microsome Clearance with Chirality-Focused Graph Neural Networks6

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  50. The Application of Machine Learning in Chemical Engineering: A Literature Review

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