Bioenergy is widely considered a sustainable alternative to fossil fuels. However, large‐scale applications of biomass‐based energy products are limited due to challenges related to feedstock variability, conversion economics, and supply chain reliability. Artificial intelligence (AI), an emerging concept, has been applied to bioenergy systems in recent decades to address those challenges. This paper reviewed 164 articles published between 2005 and 2019 that applied different AI techniques to bioenergy systems. This review focuses on identifying the unique capabilities of various AI techniques in addressing bioenergy‐related research challenges and improving the performance of bioenergy systems. Specifically, we characterized AI studies by their input variables, output variables, AI techniques, dataset size, and performance. We examined AI applications throughout the life cycle of bioenergy systems. We identified four areas in which AI has been mostly applied, including (1) the prediction of biomass properties, (2) the prediction of process performance of biomass conversion, including different conversion pathways and technologies, (3) the prediction of biofuel properties and the performance of bioenergy end‐use systems, and (4) supply chain modeling and optimization. Based on the review, AI is particularly useful in generating data that are hard to be measured directly, improving traditional models of biomass conversion and biofuel end‐uses, and overcoming the challenges of traditional computing techniques for bioenergy supply chain design and optimization. For future research, efforts are needed to develop standardized and practical procedures for selecting AI techniques and determining training data samples, to enhance data collection, documentation, and sharing across bioenergy‐related areas, and to explore the potential of AI in supporting the sustainable development of bioenergy systems from holistic perspectives.
The earth abundant and environmentally friendly element iron (Fe) forms various functional materials of metallic iron, iron oxides, iron carbides, natural iron ore, and iron-based metallic-organic frameworks. The Fe-based materials have been intensively studied as oxygen carriers, catalysts, adsorbents, and additives in bioenergy production. This review was to provide a fundamental understanding of the syntheses and characteristics of various Fe-based materials for further enhancing their functionalities and facilitating their applications in various bioenergy conversion processes. The syntheses, characteristics, and applications of various iron-based materials for bioenergy conversion published in peer-reviewed articles were first reviewed. The challenges and perspectives of the wide applications of those functional materials in bioenergy conversion were then discussed. The functionalities, stability, and reactivity of Fe-based materials depend on their structures and redox phases. Furthermore, the phase and composition of iron compounds change in a process. More research is needed to analyze the complex phase and composition changes during their applications, and study the type of iron precursors, synthesizing conditions, and the use of promoters and supports to improve their performance in bioenergy conversion. More studies are also needed to develop multifunctional Fe-based materials to be used for multi-duties in a biorefinery and develop green processes to biologically, economically, and sustainably produce those functional materials at a large scale.
more » « less- Award ID(s):
- 1736173
- PAR ID:
- 10477459
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Biomass Conversion and Biorefinery
- ISSN:
- 2190-6815
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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