State-of-the-art and future directions of machine learning for biomass characterization and for sustainable biorefinery

Chemocatalytic production of sorbitol from cellulose via sustainable chemistry – a tutorial review

“…Through kinetic control and process integration, efforts are being made to reduce energy consumption. [24][25][26] Based on VOSviewer analysis of keywords (Fig. 2) in research papers related to the catalytic production of sorbitol, much attention is being paid to upstream and downstream bio-derived compounds and performance of the catalytic systems.…”

“…However, ML-assisted prediction is still in its infancy and lacks explanatory power, and it needs to be improved in the future. 26…”

“…Furthermore, machine learning can be used to predict reaction products, accelerate catalyst design and optimization, and to explore new catalysts and reaction systems. 26 In the past several years, studies have analyzed the adsorption energy and hydrogen activation capacity of catalysts by density-functional theory (DFT) calculations to gain insight into the mechanisms of cellulose hydrolysis and glucose hydrogenation. With the development of microscopic and macroscopic characterization techniques, calculation methods have become powerful enough to propose insights into reaction mechanisms.…”

New trends in microbial lipid-based biorefinery for fermentative bioenergy production from lignocellulosic biomass

“…Moreover, leveraging artificial intelligence will enhance the precision of large-scale LCB pretreatment. This improvement includes deploying both partially and fully automated sensors and robotic systems for sophisticated and critical pretreatment steps, ensuring efficiency in processes that are challenging for individual operations (Velidandi et al, 2023). The systematic integration of machine learning algorithms in maintaining an alert and optimized working environment, regulating parameters such as temperature, pH conditions, presence of unwanted compounds in the hydrolysate, and toxicity indexing of the reaction chamber represents a promising avenue for high-throughput LCB fractionation in biofuel industries (Phromphithak et al, 2021).…”

Materials Design for the Improvement of SiC Field Effect Gas Sensor performance in High Temperature Process Control applications

“…for the processing of different bio-derived raw materials into different products in one and the same facility, generally requires on-line monitoring and feedback of various process parameters to the control system [164], see also Figure 1.19. The role of sensors and systems for the collection and processing of data from a large number of nodes within these facilities are therefore often emphasized in studies addressing the design of future bio-based production infrastructure [165][166][167]. Besides commonly measured parameters like temperature, pressure, and flow, the need for real-time monitoring also of process gas/ liquid composition changes (i.e., variations in the concentration of individual substances) in the conversion of biomass into everything from fertilizers, biofuels, and basic chemicals to plastics and pharmaceuticals is thereby likely to increase in the near future.…”