Applications of machine learning in thermochemical conversion of biomass-A review

Fuel, Год журнала: 2022, Номер 332, С. 126055 - 126055

Опубликована: Сен. 24, 2022

Язык: Английский

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Recent advancements and challenges in emerging applications of biochar-based catalysts

Biotechnology Advances, Год журнала: 2023, Номер 67, С. 108181 - 108181

Опубликована: Июнь 1, 2023

The sustainable utilization of biochar produced from biomass waste could substantially promote the development carbon neutrality and a circular economy. Due to their cost-effectiveness, multiple functionalities, tailorable porous structure, thermal stability, biochar-based catalysts play vital role in biorefineries environmental protection, contributing positive, planet-level impact. This review provides an overview emerging synthesis routes for multifunctional catalysts. It discusses recent advances biorefinery pollutant degradation air, soil, water, providing deeper more comprehensive information catalysts, such as physicochemical properties surface chemistry. catalytic performance deactivation mechanisms under different systems were critically reviewed, new insights into developing efficient practical large-scale use various applications. Machine learning (ML)-based predictions inverse design have addressed innovation with high-performance applications, ML efficiently predicts biochar, interprets underlying complicated relationships, guides synthesis. Finally, benefit economic feasibility assessments are proposed science-based guidelines industries policymakers. With concerted effort, upgrading protection reduce pollution, increase energy safety, achieve management, all which beneficial attaining several United Nations Sustainable Development Goals (UN SDGs) Environmental, Social Governance (ESG).

Язык: Английский

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Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives

Renewable and Sustainable Energy Reviews, Год журнала: 2023, Номер 182, С. 113405 - 113405

Опубликована: Май 25, 2023

Язык: Английский

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Thermochemical conversion of large-size woody biomass for carbon neutrality: Principles, applications, and issues

Bioresource Technology, Год журнала: 2022, Номер 370, С. 128562 - 128562

Опубликована: Дек. 29, 2022

Язык: Английский

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Artificial Intelligence in Biological Sciences

Life, Год журнала: 2022, Номер 12(9), С. 1430 - 1430

Опубликована: Сен. 14, 2022

Artificial intelligence (AI), currently a cutting-edge concept, has the potential to improve quality of life human beings. The fields AI and biological research are becoming more intertwined, methods for extracting applying information stored in live organisms constantly being refined. As field matures with trained algorithms, its application epidemiology, study host–pathogen interactions drug designing widens. is now applied several discovery, customized medicine, gene editing, radiography, image processing medication management. More precise diagnosis cost-effective treatment will be possible near future due AI-based technologies. In agriculture, farmers have reduced waste, increased output decreased amount time it takes bring their goods market advanced approaches. Moreover, use through machine learning (ML) deep-learning-based smart programs, one can modify metabolic pathways living systems obtain best outputs minimal inputs. Such efforts industrial strains microbial species maximize yield bio-based setup. This article summarizes potentials biology, such as industry.

Язык: Английский

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A comparative analysis of biomass torrefaction severity index prediction from machine learning

Applied Energy, Год журнала: 2022, Номер 324, С. 119689 - 119689

Опубликована: Июль 22, 2022

Язык: Английский

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Advances in machine learning technology for sustainable biofuel production systems in lignocellulosic biorefineries

The Science of The Total Environment, Год журнала: 2023, Номер 886, С. 163972 - 163972

Опубликована: Май 8, 2023

Язык: Английский

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Lignocellulosic biofuel properties and reactivity analyzed by thermogravimetric analysis (TGA) toward zero carbon scheme: A critical review

Energy Conversion and Management X, Год журнала: 2024, Номер 22, С. 100538 - 100538

Опубликована: Янв. 28, 2024

Biomass is an organic substance widely available in nature as a fresh or waste material considered renewable energy that aligns with the zero-carbon scheme to reduce dependency on fossil fuels. However, after conversion, biomass's physical chemical properties highly affect biofuel characteristics. A variety of instruments can be used figure out reactivity. Considering commonly adopted instruments, thermogravimetric analysis (TGA) simple, fast, and efficient way determine The TGA method has capability analyze (proximate analysis: moisture, volatile matter, fixed carbon, ash) combustion features biomass (such ignition, reactivity, etc). Most importantly, TG curvatures (TGA DTG) reveal behavior during thermodegradation process. As consequence, quality quantity analyses reactivity investigated comprehensively. Moreover, some integration artificial intelligence (AI) been studied better understand management technology for future development. outcome TGA-AI may obtain excellent result fit value R2>95 %. This study aims comprehensively review relevant research using lignocellulosic discussion this extended perspective, challenges, work.

Язык: Английский

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A review of noncatalytic and catalytic pyrolysis and co-pyrolysis products from lignocellulosic and algal biomass using Py-GC/MS

Journal of Industrial and Engineering Chemistry, Год журнала: 2024, Номер 134, С. 51 - 64

Опубликована: Янв. 9, 2024

Biomass pyrolysis has garnered significant attention as a sustainable energy production method utilizing various biomass feedstocks. Pyrolysate is any product generated from the process, including solid, liquid, and gas types. This review focuses on application of analytical pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) in context four modes: single feedstock pyrolysis, co-pyrolysis, catalytic co-pyrolysis to gain insights into characteristics pyrolysates. A comprehensive understanding each mode's unique products, benefits, limitations achieved by analyzing pyrolysates different feedstocks, lignocellulosic algal biomass. Moreover, this study discusses integration Py-GC/MS with techniques such density function theory (DFT), which estimating reactions' activation energies or kinetic studies concentrating reaction rate mechanism further insight mechanisms. Lastly, design experiment (DoE) are proposed for optimization obtain more assessment parameter's influence factors levels.

Язык: Английский

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Introduction of machine learning and artificial intelligence in biofuel technology

Current Opinion in Green and Sustainable Chemistry, Год журнала: 2024, Номер 47, С. 100928 - 100928

Опубликована: Апрель 26, 2024

Язык: Английский

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