Accelerating manufacturing for biomass conversion <i>via</i> integrated process and bench digitalization: a perspective

Batchu, Sai Praneet; Blazquez, Borja Hernandez; Malhotra, Abhinav; Fang, Hui; Ierapetritou, Marianthi G.; Vlachos, Dionisios G.

doi:10.1039/d1re00560j

Cited by 16 publications

(9 citation statements)

References 153 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Discovering new patterns in supply chain data has the potential to revolutionize any business. However, only a few previous studies [75][76][77] have focused on using these techniques applied to the biomass supply chain, and these were mostly focused on sustainability or a single element of the larger supply chain (e.g., biomass conversion technology). The "Mathematics" and "Computer Science" subject areas evaluated in this study (Figure 2) represent a relatively small number of the papers in this study, but thanks to an explosion of research and tools in AI and ML techniques in computing [78], this area is currently receiving keen attention from researchers in the biomass-to-bioenergy field.…”

Section: Discussion: Constraints Gaps and Future Researchmentioning

confidence: 99%

A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization

et al. 2023

View full text Add to dashboard Cite

Based on current trends and policies aimed at decarbonizing energy systems, the conversion of biomass to bioenergy has the potential to grow rapidly, but such growth depends on the development of efficient, sustainable, and competitive biomass supply chains. As a result, the biomass supply chain has stimulated the interest of a diverse group of researchers across academia, government, and industry, and there is a need to synthesize and categorize the rapidly expanding literature in this field. We conducted a literature review using advanced bibliometric analysis and visualization of 1711 peer-reviewed articles published from January 1992 to August 2022 with the aim of promoting impactful research in both growing and neglected areas of investigation. The results show that there are potential research gaps and opportunities in six critical areas: globalization of supply chain research; incorporation of uncertainty, stochasticity, and risk into supply chain models; investigation of multi-feedstock supply systems; strengthening supply chain resilience; application of inventory control methods; and broader use of machine learning and artificial intelligence in this field. By providing a holistic examination of how biomass-to-bioenergy supply chain research has grown and evolved over this period, our results and subsequent framework and recommendations can aid researchers in developing future studies and can guide stakeholder strategies to identify, diagnose, and address modern challenges that face the bioenergy industry.

show abstract

Section: Discussion: Constraints Gaps and Future Researchmentioning

confidence: 99%

A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization

et al. 2023

View full text Add to dashboard Cite

show abstract

“…In particular, the integrated biorefinery design involves emerging technologies in its superstructure with uncertainties from various sources. The design of profitable, environmentally friendly, and flexible biorefineries is also of practical importance for the implementation of viable technologies toward circular economy . Consequently, a biorefinery case study is selected in section to demonstrate the effectiveness of the proposed method in handling supply, demand, conversion, and price uncertainties.…”

Section: Problem Formulationmentioning

confidence: 99%

Multifeedstock and Multiproduct Process Design Using Neural Network Surrogate Flexibility Constraints

Luo

Ierapetritou

2023

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

Biorefineries are designed to utilize a combination of various technologies to transform biomass derived raw materials into different valueadded products. This strategy has been highlighted in the literature for reducing waste, increasing profitability, and improving the process resilience to uncertain biomass feedstocks. In this work, a two-stage stochastic programming (TSSP) model is developed to maximize profit and minimize emissions under different sources of uncertainties. Data-driven surrogate models are built for biorefinery's flexibility index (FI) to quantify and improve its operational flexibility. The neural network with rectified linear unit (ReLU) activation function is established as the appropriate surrogate model because it closely approximates the flexibility index while retaining the mixed-integer linear characteristics of the overall design formulation. Moreover, the stochastic programming demonstrates the magnitude of environmental impact uncertainty quantitatively in each scenario using empirical price/demand/supply uncertainty information, which cannot be addressed by the traditional Pedigree-based life cycle assessment (LCA) uncertainty analysis.

show abstract

“…They are unmatched compared to conducting a single or a couple of measurements per day in batch systems. 113 In this section, the catalytic conversion of monosaccharides to furanic derivatives using homogeneous and heterogeneous monophasic and biphasic reactors is reviewed. Productivity is a crucial advantage of continuous flow reactors and is used as a comparison metric.…”

Section: Lignocellulosic Biomass Conversion In Microflowmentioning

confidence: 99%

Microflow chemistry and its electrification for sustainable chemical manufacturing

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective

Abstract: We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass...

Cited by 16 publications

References 153 publications

A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization

A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization

Multifeedstock and Multiproduct Process Design Using Neural Network Surrogate Flexibility Constraints

Microflow chemistry and its electrification for sustainable chemical manufacturing

Contact Info

Product

Resources

About