Selective lignin depolymerization (SLD) has emerged as a value-added method of pretreatment for lignocellulosic biorefining, in which lignin is depolymerized into valuable phenolic monomers prior to utilization of the hemicellulose and cellulose. Herein, we report a biomimetic Fenton catalyzed SLD process, converting sweet sorghum bagasse into an organic oil that is rich in phenolic monomers and a solid carbohydrate that is favorable for enzymatic hydrolysis into sugars. Initially, the feedstock's molecular structure was modified through iron chelation and free radical oxidation via Fenton's reagent (Fe 3+ , H 2 O 2 ). The lignin component of the modified feedstock was then selectively depolymerized in supercritical ethanol (250 °C, 6.5 MPa) under nitrogen to produce a phenolic oil, with a maximum yield of 75.8 wt %. Six valuable phenolic monomers were detected in this oil, with a maximum cumulative yield of 19.1 wt %. The solid carbohydrate obtained after the SLD process was enzymatically hydrolyzed to liberate 62.7 and 79.9 wt % of the initial 5-and 6-carbon polysaccharides within 24 h, respectively, indicating the majority of the hemicellulose and cellulose were preserved during the SLD process. Fenton modification not only increased the yields of phenolic monomers, particularly ethyl-p-coumarate and ethyl-ferulate, but also enhanced enzymatic hydrolysis.

Large amounts of food are wasted during the food supply chain. This loss is in part due to consumer confusion over dates on food packages that can indicate a variety of quality indicators in the product (e.g., expiration date, “best by” date, “sell by” dates, etc.). To reduce this food loss, much research has been focused on the films that offer simple and easily manipulated indication systems to detect food spoilage. However, these materials are usually hydrophilic biopolymers that can detect the food spoilage in a wide pH range but do not provide highly sensitive real-time measurements. In this work, a glycerol-based nanocomposite core–shell latex film was synthesized to create a responsive packaging material that can provide real-time pH detection of food with high sensitivity. First, the pH-responsive dendrimer comonomer was synthesized from glycerol and diamine. Then, the nanoencapsulation polymerization process via miniemulsion was conducted to form a core–shell structure with tunable nanoshell thickness for a sensible pH-responsive release (<0.5 pH change). Next, the flexible film encapsulated a color-indicative dye that provided highly sensitive and visible color changes as both the pH dropped and the time elapsed in the food. This film also provided a barrier to water and heat and resisted deformation. Ultimately, this nanocomposite flexible film pending a pH sensor has the potential as an intelligent food packaging material for a universal, accurate, easy-to-use, and real-time food spoilage monitoring system to reduce food waste.

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This study aimed to use a persulfate together with transition metal ions as the reagent to effectively depolymerize lignin into monophenolic compounds under mild conditions (ambient pressure, temperature <100 °C). The Box‐Behnken experimental design in combination with the response surface methodology was applied to obtain optimized reaction conditions. The results showed that this reagent could depolymerize up to 99 % of lignin dimers to mainly veratraldehyde. This reaction also successfully depolymerized industrial lignins with a high yield of phenolic oils and monophenolic compounds. Quantum chemistry calculations using the density functional theory level indicated that the persulfate free radical attacks Cβ to break the β‐O‐4 bond of lignin through a five‐membered ring mechanism. This mechanism using persulfate free radicals has a lower activation barrier than that using hydroxyl radicals. Gel permeation chromatography and 2D‐NMR spectroscopy demonstrated the effective cleavage of the β‐O‐4 bonds of lignin after depolymerization.

Phosphorus (P) is an essential nutrient for crops, but its excess in discharge water harms both surface water and groundwater quality. A cost-effective and eco-friendly adsorbent is desirable to meet circular economy criteria by effectively removing P from water and being safely recycled for agricultural use. Thus, this study aims to synthesize an amine-functionalized magnetic lignin nanocomposite biosorbent by first grafting poly­(ethyleneimine) on epoxidized lignin followed by coprecipitation with iron. This biosorbent shows an adsorption performance of 43 mg g–1, which is 20 times greater than the unmodified lignin reported in a previous research study and six times more than the magnetic iron metal. A series of characterization methods confirm the chemical features and the formation of a nanostructure. The pH, coexisting anions, and salt concentrations affect the P removal efficiency. The mechanism studies show that the electrostatic interaction between NH3 + functional groups and P, surface precipitation, and ligand exchange all count for P removal, which indicates the heterogeneous adsorption of P onto the sorbent surface by both chemisorption and physisorption. The seedling study confirms that the nanocomposite after P adsorption has better root development and biomass accumulation as a recycled fertilizer.

Detecting and reporting the quality of packaged food to the consumer in real-time can reduce the consumption of poor-quality food products. Current food quality detection and reporting technologies of perishable foods are usually expensive, complicated, and take a significantly long time to convey results. Herein, a real-time, simple, and user-friendly food freshness detection prototype was developed by combining a glycerol-based sensory film with unique visual color analysis and the k-nearest neighbors algorithm (KNN). We established the quantitative relationship between the pH, organic acid level, digital color variance, and food storage time. By measuring the color variations of sensor films as a function of food storage time, we demonstrate a technology to record the quantitative “RGB” values of sensory films to represent real-time and precise pH changes of the food sample and trace the real-time food spoilage degree (e.g., pork loin spoilage). Next, a quick-response (QR) reader with a center sensor film was designed to eliminate the environmental effects on the color variation in real time Furthermore, the KNN was implemented to classify food quality by training data from different sources. This study provides a technology well suited for large-scale food storage applications by combining a smart sensor film with a QR code design followed by image analysis and KNN. This real-time and rapid food quality monitoring technology will ultimately lead to a reduction in food waste and loss (FLW).

Herein we address the feedstock uncertainty for a robust lignin valorization process through a dynamic stochastic programming approach.