Modeling, simulation, and optimization of supercritical and subcritical fluid extraction processes / / Zainuddin Abdul Manan, Gholamreza Zahedi, Ana Najwa Mustapa

• Autore: Manan Zainuddin Abdul
• Pubblicazione: Hoboken, New Jersey : , : Wiley : , : American Institute of Chemical Engineers, , [2022]; ©2022
• Descrizione fisica: 1 online resource (291 pages)
• Disciplina: 660.284248
• Soggetto topico: Supercritical fluid extraction - Simulation methods
• Persona (resp. second.): ZahediGholamreza; MustapaAna Najwa
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Nomenclature -- Chapter 1 Fundamentals of Supercritical and Subcritical Fluid Extraction -- 1.1 Introduction -- 1.2 Supercritical Fluid Properties -- 1.3 Subcritical Condition -- 1.4 Physical Properties of Subcritical Fluid -- 1.5 Principles of Sub- and Supercritical Extraction Process -- 1.5.1 Solid Sample Extraction -- 1.5.2 Liquid Sample Extraction -- 1.6 Applications of SCF Extraction -- 1.6.1 Decaffeination of Coffee and Tea -- 1.6.2 Removal of FFA in Fats and Oils -- 1.6.3 Enrichment of Tocopherols -- 1.6.4 Carotenes from Crude Palm Oil and from Palm Fatty Acid Esters -- 1.7 Solubility of Solutes in SCFs -- 1.8 Solute-Solvent Compatibility -- 1.9 Solubility and Selectivity of Low-Volatility Organic Compounds in SCFs -- 1.10 Method of Solubility Measurement -- 1.10.1 Static Method -- 1.10.2 Dynamic Method -- 1.11 Determination of Solvent -- 1.11.1 Carbon Dioxide (CO2) -- 1.11.2 1,1,1,2-Tetrafluoroethane (R134a) as a Solvent -- 1.12 Important Parameter Affecting Supercritical Extraction Process -- 1.12.1 Pressure and Temperature -- 1.12.2 Solvent Flowrate -- 1.12.3 Cosolvent -- 1.12.4 Moisture Content -- 1.12.5 Raw Material -- 1.13 Profile of Extraction Curves -- 1.14 Design and Scale Up -- Chapter 2 Modeling and Optimization Concept -- 2.1 SFE Modeling -- 2.1.1 Importance of Knowing the Solid Matrix and Selecting a Suitable Model -- 2.1.2 Different Modeling Approaches in SFE -- 2.1.2.1 Experimental Models -- 2.1.2.2 Models Which Are Based on Similarity between Heat and Mass Transfer -- 2.1.2.3 Models Based on Conservation Balance Equations -- 2.2 First Principle Modeling -- 2.2.1 The Equation of Continuitya -- 2.2.2 The Equation of Motion in Terms of τ -- 2.2.3 The Equation of Energy in Terms of q -- 2.3 Hybrid Modeling or Gray Box -- 2.4 ANN. ; 2.4.1 Simple Neural Network Structure -- 2.4.1.1 Transfer Function -- 2.4.1.2 Activation Functions -- 2.4.1.3 Learning Rules -- 2.4.2 Network Architecture -- 2.5 Fuzzy Logic -- 2.5.1 Boolean Logic and Fuzzy Logic -- 2.5.2 Fuzzy Sets -- 2.5.3 Membership Function -- 2.5.3.1 Membership Function Types -- 2.5.4 Fuzzy Rules -- 2.5.4.1 Classical Rules and Fuzzy Rules -- 2.5.5 Fuzzy Expert System and Fuzzy Inference -- 2.5.5.1 Mamdani FIS -- 2.5.5.1.1 Fuzzification -- 2.5.5.1.2 Fuzzy Logical Operation and Rule Evaluation -- 2.5.5.1.3 Implication Method -- 2.5.5.1.4 Aggregation of the Rule Outputs -- 2.5.5.1.5 Defuzzification -- 2.5.5.2 Sugeno Fuzzy Inference -- 2.6 Neuro Fuzzy -- 2.6.1 Structure of a Neuro Fuzzy System -- 2.6.2 Adaptive Neuro Fuzzy Inference System (ANFIS) -- 2.6.2.1 Learning in the ANFIS Model -- 2.7 Optimization -- 2.7.1 Traditional Optimization Methods -- 2.7.2 Evolutionary Algorithm -- 2.7.3 Simulated Annealing Algorithm -- 2.7.4 Genetic Algorithm -- 2.7.4.1 Genetic Algorithm Definitions -- 2.7.4.2 Genetic Algorithms Overview -- 2.7.4.3 Preliminary Considerations -- 2.7.4.4 Overview of Genetic Programming -- 2.7.4.5 Implementation Details -- 2.7.4.5.1 Selection Operator -- 2.7.4.5.2 Crossover Operator -- 2.7.4.5.3 Mutation Operator -- 2.7.4.6 Effects of Genetic Operators -- 2.7.4.7 The Algorithms -- Chapter 3 Physical Properties of Palm Oil as Solute -- 3.1 Introduction -- 3.2 Palm Oil Fruit -- 3.3 Palm Oil Physical and Chemical Properties -- 3.3.1 Palm Oil Triglycerides -- 3.3.2 Minor Components in Palm Oil -- 3.4 Vegetable Oil Refining -- 3.5 Conventional Palm Oil Refining Process -- 3.5.1 Chemical Refining -- 3.5.2 Physical Refining -- 3.5.3 Effect of Palm Oil Refining -- 3.6 Conclusions -- Chapter 4 First Principle Supercritical and Subcritical Fluid Extraction Modeling: Part I: Modeling Methodology -- 4.1 Introduction. ; 4.2 Phase Equilibrium Modeling -- 4.3 The Redlich-Kwong-Aspen Equation of State -- 4.3.1 Calculations of Pure Component Parameters for the RKA-EOS -- 4.3.2 Binary Mixture Calculations -- 4.4 Palm Oil System Characterization -- 4.4.1 Palm Oil Triglycerides -- 4.4.2 Free Fatty Acids -- 4.4.3 Palm Oil Minor Components -- 4.5 Development of Aspen Plus® Physical Property Database for Palm Oil Components -- 4.5.1 Vapor Pressure Estimation -- 4.5.2 Estimation of Pure Component Critical Properties -- 4.5.2.1 Critical Properties Estimation Using Normal Boiling Point -- 4.5.2.2 Critical Properties Estimation Using One Vapor Pressure Point -- 4.6 Binary Interaction Parameters Calculations -- 4.7 Supercritical Fluid Extraction Process Development -- 4.7.1 Hydrodynamics of Countercurrent SFE Process -- 4.7.2 Solubility of Palm Oil in Supercritical CO2 -- 4.7.3 Process Modeling and Simulation -- 4.7.3.1 Simple Countercurrent Extraction -- 4.7.3.2 Countercurrent Extraction with External Reflux -- 4.7.4 Process Analysis and Optimization -- Part II: Results and Discussion -- 4.8 Palm Oil Component Physical Properties -- 4.8.1 Vapor Pressure of Palm Oil Components -- 4.8.2 Pure Component Critical Properties -- 4.9 Regression of Interaction Parameters for the Palm Oil Components-Supercritical CO2 Binary System -- 4.9.1 Binary System: Triglyceride - Supercritical CO2 -- 4.9.2 Binary System: Oleic Acid - Supercritical CO2 -- 4.9.3 Binary System: α-Tocopherol - Supercritical CO2 -- 4.9.4 Binary System: β-Carotene - Supercritical CO2 -- 4.9.5 Temperature-Dependent Interaction Parameters -- 4.10 Phase Equilibrium Calculation for the Palm Oil -Supercritical CO2 System -- 4.11 Ternary System: CO2 - Triglycerides - Free Fatty Acids -- 4.12 Distribution Coefficients of Palm Oil Components -- 4.13 Separation Factor Between Palm Oil Components. ; 4.13.1 Separation Factor Between Fatty Acids and Triglycerides -- 4.13.2 Separation Factor Between Fatty Acids and α-Tocopherols -- 4.14 Base Case Process Simulation -- 4.14.1 Palm Oil Deacidification Process -- 4.14.1.1 Solubility of Palm Oil in Supercritical CO2 -- 4.14.1.2 Palm Oil Deacidification Process: Comparison to Pilot Plant Results -- 4.15 Conclusion -- Chapter 5 Application of Other Supercritical and Subcritical Modeling Techniques -- 5.1 Mass Transfer, Correlation, ANN, and Neuro Fuzzy Modeling of Sub- and Supercritical Fluid Extraction Processes -- 5.2 Mass Transfer Model -- 5.3 ANN Modeling -- 5.4 Neuro Fuzzy Modeling -- 5.5 ANFIS and Gray-box Modeling of Anise Seeds -- 5.6 White Box SFE Modeling of Anise -- 5.6.1 Gray Box Parameters -- 5.6.2 ANFIS -- 5.6.2.1 Preprocessing -- 5.6.3 Gray Box -- 5.7 Results and Discussion -- 5.7.1 ANFIS -- 5.7.2 Gray Box Modeling Results -- 5.7.2.1 Black Box -- 5.7.3 Comparison of ANFIS and Gray Box Models with ANN and White Box Models -- 5.8 Introduction - Statistical versus ANN Modeling -- 5.9 Supercritical Carbon Dioxide Extraction of Q. infectoria Oil -- 5.9.1 Materials and Methods -- 5.9.2 Experimental Design -- 5.9.3 Artificial Neural Network Modeling -- 5.10 Subcritical Ethanol Extraction of Java Tea Oil -- 5.10.1 Artificial Neural Network Modeling -- 5.11 SFE of Oil from Passion Fruit Seed -- 5.11.1 Experimental Procedures -- 5.11.2 RSM Statistical Modeling -- 5.11.3 ANN Modeling of Passion Fruit Seed Oil Extraction with Supercritical Carbon Dioxide -- Chapter 6 Experimental Design Concept and Notes on Sample Preparation and SFE Experiments -- 6.1 Introduction -- 6.2 Experimental Design -- 6.3 Statistical Optimization -- 6.4 Optimization of Palm Oil Subcritical R134a Extraction -- 6.4.1 Effect of Temperature and Pressure -- 6.4.2 Model Fitting -- 6.4.3 Process Optimization. ; 6.5 Comparison of Subcritical R134a and Supercritical CO2 Extraction of Palm Oil -- 6.5.1 Extraction Performance -- 6.5.2 Economic Factor -- 6.6 Sample Pretreatment -- 6.6.1 Moisture Content Reduction -- 6.6.2 Sample Size Reduction -- 6.7 New Trends in Pretreatment -- 6.8 Optimal Pretreatment -- Chapter 7 Supercritical and Subcritical Optimization: Part I: First Principle Optimization -- 7.1 Introduction -- 7.2 Evaluation of Separation Performance -- 7.2.1 Effects of Temperature and Pressure -- 7.2.2 Effect of the Number of Stages -- 7.2.3 Effect of Solvent-to-Feed Ratio -- 7.2.4 Effect of Reflux Ratio -- 7.3 Parameter Optimization of Palm Oil Deacidification Process -- 7.3.1 Simple Countercurrent Extraction (Without Reflux) -- 7.3.2 Countercurrent Extraction with Reflux -- 7.4 Proposed Flowsheet for Palm Oil Refining Process -- 7.5 Conclusions -- Part II: ANN, GA Statistical Optimization -- 7.6 Introduction -- 7.7 Traditional Optimization -- 7.8 Nimbin Extraction Process Optimization -- 7.9 Genetic Algorithm for Mass Transfer Correlation Development -- 7.10 Optimizing Chamomile Extraction -- 7.11 Statistical and ANN Optimization -- 7.12 Conclusion -- Appendix A Calculation of the Composition for Palm Oil TG (Lim et al. 2003) -- Appendix B Calculation of Distribution Coefficient and Separation Factor (Lim et al. 2003) -- Appendix C Calculation of Palm Oil Solubility in Supercritical CO2 (Lim et al. 2003) -- References -- Index -- EULA.
• Sommario/riassunto: "Supercritical fluid extraction (SFE) technology has become an increasingly popular method for extraction and purification of food ingredients including vegetable oils over the last 20 years due to its unique advantages over conventional processing methods. These include low-temperature operation, inert solvent, selective separation, and the extraction of high-value products or new products with improved functional or nutritional characteristics. SFE is also an environmentally benign technology since the process typically generates little or no waste. SFE technology is used to process hundreds of millions of pounds of coffee, tea, and hops annually, and is increasingly becoming of common use in the pharmaceutical industry for purification and nano-particle formation. Supercritical fluid processing is also gaining popularity in botanicals, vitamins and supplements industries that require products of highest purity and quality"--
• Titolo autorizzato: Modeling, simulation, and optimization of supercritical and subcritical fluid extraction processes
• ISBN: 1-119-30320-6; 1-119-30319-2; 1-119-30321-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910830062303321
• Lo trovi qui: Univ. Federico II