| Autore |
Salama Sayed
|
| Edizione | [1st ed.] |
| Pubbl/distr/stampa |
Chantilly : , : Elsevier Science & Technology, , 2025
|
| Descrizione fisica |
1 online resource (553 pages)
|
| Disciplina |
662.88028563
|
| Altri autori (Persone) |
SalamaSayed
|
| Collana |
Woodhead Series in Bioenergy Series
|
| Soggetto topico |
Renewable energy sources
Biodiesel fuels
|
| ISBN |
0-443-26719-7
0-443-26718-9
9780443267192
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Front Cover -- Artificial Intelligence in Biofuels Production -- Copyright Page -- Contents -- List of contributors -- About the editor -- Foreword -- Preface -- 1 An overview of biofuels with artificial intelligence -- 1.1 Introduction -- 1.1.1 Conventional fuel production rate and current energy crisis -- 1.1.1.1 Fuel properties and environmental issues -- 1.1.2 Overview of biofuel -- 1.2 Various generations of biofuels and types -- 1.3 Types of biofuels -- 1.3.1 Bioethanol production -- 1.3.1.1 Fermentation technologies -- 1.3.1.2 Fermentation process -- 1.3.1.3 Higher alcohol -- 1.3.2 Biodiesel generation -- 1.3.2.1 Transesterification of oil/lipid -- 1.3.2.2 Alkaline catalytic transesterification -- 1.3.2.3 Acid-catalyzed transesterification -- 1.3.2.4 Enzymatic transesterification -- 1.3.2.5 Advantages and disadvantages of biodiesel -- 1.3.2.6 Advantages of lipases and disadvantages of lipases -- 1.3.3 Anaerobic digestion -- 1.3.3.1 Factors affecting biogas production -- Feedstocks -- Temperature -- Nutrients -- pH and buffering capacity -- Volatile fatty acids -- Organic loading rate -- 1.3.3.2 Gas phase analysis -- 1.3.3.3 Liquid phase -- 1.3.3.4 Microbial community composition -- 1.3.4 Biohydrogen production -- 1.3.5 Fischer-Tropsch process for liquid hydrocarbons -- 1.4 Current applications of biofuels -- 1.5 Challenges in biofuel -- 1.6 Introduction to artificial intelligence and machine learning -- 1.6.1 Tyes of artificial intelligence and machine learning -- 1.7 Application of artificial intelligence in different biofuels -- 1.7.1 Machine learning application in biodiesel -- 1.7.2 Bioethanol process optimization and production -- 1.7.3 Anaerobic digestion process optimization -- 1.8 Relative importance of variables on predictability -- 1.9 Conclusion -- References -- 2 Waste materials as raw material for biofuel production.
2.1 Introduction -- 2.2 Waste materials -- 2.3 Health issues caused by wastewater -- 2.4 Types of wastewater -- 2.4.1 Agricultural wastewater -- 2.4.2 Industrial wastewater -- 2.5 Types of pollutants in wastewater -- 2.5.1 Micropollutants and heavy metals -- 2.6 Types of adsorbents used for wastewater -- 2.7 Types of conversion technology for producing biofuel -- 2.8 Current and future challenges -- 2.9 Conclusion -- References -- 3 Advancement in biodiesel production and economic feasibility -- 3.1 Introduction -- 3.2 Advancements in biodiesel production systems -- 3.2.1 Critical parameters -- 3.2.1.1 Compositional variables -- Feedstock effects -- Catalyst effects -- 3.2.1.2 Operational variables -- Calcination and reaction temperature effects -- Alcohol-to-oil ratio and mechanical stirring -- 3.2.2 Critical technologies -- 3.2.2.1 Advanced reactors -- Ultrasonic radiation reactor -- Benefits and constraints -- Plasma reactor -- Noncatalytic plasma reactors -- Catalytic plasma reactors -- Hybrid plasma reactors -- Benefits and constraints -- Microwave reactors -- Benefits and constraints -- 3.2.2.2 Other transesterification reactors -- 3.3 Economic feasibility -- 3.3.1 Operating cost -- 3.3.2 Benefits and constraints -- 3.4 Conclusion and future outlook -- References -- 4 Exploring the frontier of bioethanol production: real-time modeling -- 4.1 Bioethanol -- 4.2 Feedstocks for bioethanol production -- 4.2.1 Lignocellulosic source for bioethanol production -- 4.3 Pretreatment of lignocellulosic biomass -- 4.3.1 Physical pretreatment -- 4.3.2 Chemical pretreatment -- 4.3.3 Physicochemical treatment -- 4.3.4 Biological pretreatment -- 4.4 Hydrolysis of lignocellulosic biomass -- 4.5 Cell immobilization -- 4.5.1 Optimization of immobilized enzyme systems -- 4.5.2 Immobilization of yeast cells -- 4.5.3 Types of immobilization.
4.5.3.1 Entrapment method -- 4.6 Bioethanol fermentation -- 4.6.1 Current fermentation strategies for bioethanol production -- 4.6.2 Hexose and pentose utilization in different microorganisms -- 4.6.3 Anaerobic xylose metabolism and eukaryotic glycolytic pathways -- 4.6.4 Alternative carbohydrate catabolic pathways in prokaryotes -- 4.7 Machine learning models for bioethanol -- 4.7.1 Ethanol yield prediction using machine learning models -- 4.7.2 Optimization of ethanol production using hybrid machine learning approaches -- 4.8 Conclusion -- References -- 5 Bio-oil and aviation production: applications and upgradation -- 5.1 Introduction to bio-oil -- 5.2 Recent technologies used in bio-oil production -- 5.2.1 Catalytic pyrolysis -- 5.2.2 Fast pyrolysis -- 5.2.3 Thermal pyrolysis -- 5.2.4 Bifunctional catalysts -- 5.2.5 Novel catalytic processes -- 5.2.6 Coprocessing techniques -- 5.2.7 Slow pyrolysis -- 5.2.8 Hydrothermal liquefaction -- 5.3 Compositional analysis of bio-oil through different approaches -- 5.3.1 Chemical composition of bio-oil -- 5.3.2 Approaches for composition analysis -- 5.3.2.1 Nuclear magnetic resonance spectroscopy -- 5.3.2.2 Gas chromatography-mass spectrometry -- 5.3.2.3 Ultrahigh-resolution mass spectrometry -- 5.3.2.4 Gel permeation chromatography -- 5.3.2.5 Centrifugal partition chromatography -- 5.3.2.6 High performance liquid chromatography -- 5.3.2.7 Hydroxyl group profiling -- 5.3.2.8 Other techniques -- 5.4 Bio-oil properties -- 5.4.1 Stability and content of bio-oil -- 5.4.2 Heating value -- 5.4.3 Viscosity and density -- 5.4.4 Acidity -- 5.4.5 Stability -- 5.4.6 Corrosiveness -- 5.5 Upgrading bio-oil is essential for enhancing its fuel properties -- 5.5.1 Hydrotreating -- 5.5.2 Supercritical fluid upgrading -- 5.5.3 Hydrocracking -- 5.5.4 Esterification -- 5.5.5 Catalytic cracking -- 5.5.6 Emulsification.
5.5.7 Solvent addition -- 5.5.8 Integrated systems -- 5.6 Factors influence the bio-oil -- 5.6.1 Bio-oil pyrolysis product yield -- 5.6.2 Substrate composition's effect on pyrolysis -- 5.6.3 Factor effecting pyrolysis rate -- 5.7 Artificial intelligence in bio-oil -- 5.7.1 Artificial intelligence-aided bio-oil optimization -- 5.7.2 Model training and validation -- 5.7.3 Application of artificial intelligence in bio-oil production -- 5.7.4 Process optimization -- 5.7.5 Challenges for artificial intelligence -- 5.7.6 Future direction for artificial intelligence -- 5.8 Economic feasibility production of bio-oil -- 5.8.1 Feedstock -- 5.8.2 Industrial scalable technologies -- 5.8.3 Operational parameters -- 5.8.4 Techno-economic analysis -- 5.9 Challenges and future directions -- 5.10 Conclusion -- References -- 6 Biohythane as sustainable biofuel -- 6.1 Introduction -- 6.2 Importance of biohythane in renewable energy -- 6.3 Composition of biohythane -- 6.3.1 Hydrogen and methane as key components -- 6.3.2 Proportions of hydrogen to methane in biohythane -- 6.4 The biochemical pathways of biohythane production -- 6.4.1 Fermentation and anaerobic digestion -- 6.4.2 Microbial communities involved in biohythane production -- 6.4.3 Overview of anaerobic digestion process -- 6.5 Hydrolysis -- 6.5.1 Acidogenesis -- 6.5.2 Acetogenesis -- 6.5.3 Methanogenesis -- 6.6 Hydrogen production in biohythane -- 6.6.1 Dark fermentation -- 6.6.2 Microbes responsible for hydrogen production -- 6.7 Methane production in biohythane -- 6.7.1 Methanogenesis pathway -- 6.7.2 Role of archaea in methane production -- 6.8 Conventional biohythane production and its limitations -- 6.9 Biohythane production in bioelectrochemical system -- 6.10 Factors affecting biohythane production -- 6.10.1 Feedstock types and their influence -- 6.10.2 Temperature and pH levels.
6.10.3 Retention time in digesters -- 6.11 Biohythane as a dual-energy resource -- 6.11.1 Combined benefits of hydrogen and methane -- 6.11.2 Comparison with other renewable energy sources -- 6.12 Environmental impact of biohythane -- 6.12.1 Reduced greenhouse gas emissions -- 6.12.2 Waste management and resource recovery -- 6.13 Applications of biohythane -- 6.13.1 Power generation -- 6.13.2 Transportation fuel -- 6.13.3 Industrial use -- 6.14 Challenges in biohythane production -- 6.14.1 Technical barriers -- 6.14.1.1 Feedstock variability and pretreatment requirements -- 6.14.1.2 Microbial community management -- 6.14.1.3 Integration of production processes -- 6.14.2 Economic considerations -- 6.14.2.1 Production costs -- 6.14.2.2 Market competition -- 6.14.2.3 Investment in research and development -- 6.15 Future prospects for biohythane -- 6.15.1 Technological advancements -- 6.15.2 Policy and regulatory support -- 6.16 Biohythane and the circular economy -- 6.16.1 Waste-to-energy concept -- 6.16.2 Sustainability and renewable energy -- 6.17 Scaling up biohythane production -- 6.17.1 From laboratory to industrial scale -- 6.17.2 Infrastructure requirements -- 6.18 Conclusion -- References -- 7 Biofuels for aviation -- 7.1 Introduction -- 7.1.1 Definition of aviation biofuels and their role in sustainable aviation -- 7.1.2 Importance of transitioning from fossil-based jet fuels to biofuels -- 7.1.3 Current challenges with traditional aviation fuels (e.g., carbon emissions, price volatility, and supply chain risks) -- 7.1.4 Types of biofuels for aviation -- 7.1.5 First-generation biofuels -- 7.1.5.1 Features and manufacturing -- 7.1.5.2 Advantages and disadvantages -- 7.1.5.3 Production methods -- 7.1.6 Second-generation biofuels -- 7.1.6.1 Features and manufacturing -- 7.1.6.2 Advantages and disadvantages.
7.1.6.3 Third-generation and advanced biofuels.
|
| Record Nr. | UNINA-9911119064503321 |
Info
Advanced technologies in biodiesel : new advances in designed and optimized catalysts / / Aminul Islam [and three others]
