Recent Advances in Artificial Intelligence and Machine Learning for Thermochemical and Biochemical Bioprocess
- 1st Edition - November 15, 2026
- Latest edition
- Editors: Mukesh Kumar Awasthi, Mohammad J. Taherzadeh, Karthik Rajendran
- Language: English
Recent Advances in Artificial Intelligence and Machine Learning for Thermochemical and Biochemical Bioprocess delves into the transformative role of AI and ML in enhancing the ef… Read more
Description
Description
Recent Advances in Artificial Intelligence and Machine Learning for Thermochemical and Biochemical Bioprocess delves into the transformative role of AI and ML in enhancing the efficiency and effectiveness of bioprocess operations. The book covers everything from predictive modeling and bioreactor design to the integration of IoT in Bioprocess 4.0 while also synthesizing the latest scientific advancements and practical applications in the field of thermochemical and biochemical bioprocesses. It explores a wide array of topics, including deep learning applications in gasification, the role of artificial neural networks in process control, and the use of genetic algorithms in thermochemical processing.
Each chapter offers invaluable insights into current methodologies and future perspectives, providing a solid foundation for applying AI and ML techniques to tackle pressing challenges in clean fuel production, waste management, and climate change mitigation.
Each chapter offers invaluable insights into current methodologies and future perspectives, providing a solid foundation for applying AI and ML techniques to tackle pressing challenges in clean fuel production, waste management, and climate change mitigation.
Key features
Key features
- Explores cutting-edge applications of AI and ML tools in enhancing clean fuel technologies and energy security, providing readers with innovative strategies to tackle global energy challenges
- Analyzes the integration of AI and ML in waste management and valorization processes, highlighting methods to reduce greenhouse gas emissions and promote a circular economy for sustainable development
- Evaluates the role of AI and ML in advancing thermochemical biomass conversion technologies, equipping researchers with insights into chemical kinetics, process intensification, and economic viability for biofuel production
- Discusses the implications of AI and ML on regulatory frameworks and policies, offering a comprehensive guide for academics, industry leaders, and policymakers
- Presents case studies and real-world applications, illustrating the transformative potential of AI and ML in addressing climate change mitigation and fostering a sustainable future
Readership
Readership
Professionals, researchers, and graduate students in biochemical and environmental engineering
Table of contents
Table of contents
1. Introduction and historical perspectives to AI and ML in bioprocess and thermochemical process engineering
2. Pretreatment and characterization using machine learning approaches
3. Applications of deep learning in gasification and pyrolysis
4. Predictive modelling of biochemical reactions for biofuels, bioproducts and biomaterials.
5. Bioreactor design and operation using AI
6. Role of artificial neural networks in process control and monitoring in bioprocessing
7. Natural language processing for bioprocess data analysis and visualization
8. Usage of genetic algorithms towards thermochemical reactions and processing
9. Support of AI towards experimental design for bio- and thermos-chemical process development
10. Machine learning approaches for predictive maintenance in bioprocessing equipment
11. Fusing AI and mechanistic modeling for better bioprocessing
12. Use of AI for a better decision making of bioprocessing and thermochemical processing
13. Machine learning in fermentative biohydrogen production
14. ML approaches towards the reduction of technology development in bio- and thermos-chemical processes
15. Integrating AI, ML, and IoT in Bioprocess 4.0
16. Future perspectives, challenges and restrictions related to the current application of AI and ML in the process industry
2. Pretreatment and characterization using machine learning approaches
3. Applications of deep learning in gasification and pyrolysis
4. Predictive modelling of biochemical reactions for biofuels, bioproducts and biomaterials.
5. Bioreactor design and operation using AI
6. Role of artificial neural networks in process control and monitoring in bioprocessing
7. Natural language processing for bioprocess data analysis and visualization
8. Usage of genetic algorithms towards thermochemical reactions and processing
9. Support of AI towards experimental design for bio- and thermos-chemical process development
10. Machine learning approaches for predictive maintenance in bioprocessing equipment
11. Fusing AI and mechanistic modeling for better bioprocessing
12. Use of AI for a better decision making of bioprocessing and thermochemical processing
13. Machine learning in fermentative biohydrogen production
14. ML approaches towards the reduction of technology development in bio- and thermos-chemical processes
15. Integrating AI, ML, and IoT in Bioprocess 4.0
16. Future perspectives, challenges and restrictions related to the current application of AI and ML in the process industry
Product details
Product details
- Edition: 1
- Latest edition
- Published: November 15, 2026
- Language: English
About the editors
About the editors
Mukesh Kumar Awasthi
Editor
Mukesh Kumar Awasthi is Assistant Professor in the Department of Mathematics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. His research focuses on the mathematical modelling of fluid flow problems, with particular interests in viscous potential flow, electrohydrodynamics, magnetohydrodynamics, heat and mass transfer, and fluid instability phenomena. He teaches postgraduate courses in fluid mechanics, discrete mathematics, partial differential equations, abstract algebra, mathematical methods, and measure theory. His work encompasses both analytical and numerical approaches to modelling complex flow systems. He has received research funding for projects in nonlinear fluid dynamics and has been recognized with research awards for his contributions to the field. He is the author and editor of numerous scholarly publications, including books, book chapters, journal articles, and conference papers. His research contributes to the advancement of mathematical methods and modelling techniques in fluid mechanics and related disciplines.
Affiliations and expertise
Assistant Professor, Department of Mathematics, Babasaheb Bhimrao Ambedkar University, Lucknow, IndiaMohammad J. Taherzadeh
Editor
Mohammad J. Taherzadeh is professor in Biotechnology since 2004 at University of Borås in Sweden. He is also director of Resource Recovery, a research profile with about 50 researchers to convert wastes to energy and value-added products. Prof. Taherzadeh has PhD in Bioscience and MSc and Bsc in Chemical Engineering. He is working on converting wastes and residuals to ethanol, biogas, fish feed and superabsorbents, in which fermentation development using bacteria, yeast and filamentous fungi has a heavy weight. Prof. Taherzadeh has more than 120 publications in scientific peer-reviewed journals, 10 book chapters and two patents about filamentous fungi. Mohammad is the panel chairman of “biotechnology, chemical technology and environmental technology” of Swedish Research Council, and also in the editorial board of Bioresource Technology and BioResources.
Affiliations and expertise
Professor, Swedish Centre for Resource Recovery, University of Boras, Boras, SwedenKarthik Rajendran
Editor
Dr. Karthik Rajendran is a distinguished academic and researcher, currently serving as the Associate Dean at SRM University-AP, where he oversees the Office of the Dean Quality Assurance and Rankings. His work primarily focuses on the development of advanced biofuels, the integration of Energy and AI, and conducting thorough techno-economic analyses and lifecycle assessments.
Affiliations and expertise
Assistant Professor, Department of Environmental Science, SRM University, Andhra Pradesh, India