Microwave-assisted extraction of cellulose and aromatic compounds from rose petals based on deep eutectic solvent.

High-value utilization of agricultural wastes such as rose petals promotes the development of the dual carbon economy. In this study, rose petals were pretreated by microwave-assisted deep eutectic solvent (DES). Choline chloride-ethylene glycol (ChCl-EG) was used as the basis for the addition of P-toluenesulfonic acid (TsOH) or Ferric chloride (FeCl3). Forming ternary DESs, as well as designing quaternary DESs with a synergistic effect. The effects of different types of multicomponent DES on treating anthocyanins, cellulose, and lignin in rose flowers were explored. The results showed that the highest anthocyanin extraction of 173.71 mg/g and the highest lignin removal of 40.80 % could be achieved after tetrad DES pretreatment when the molar ratio was ChCl:EG:TsOH:FeCl3 = 1:2:0.3:0.3. The interaction energy between anthocyanins and DES was calculated using density functional theory (DFT), and the maximum was -543.14 kcal/mol. This study demonstrated that DES pretreatment can provide novel insights for the utilization of roses in high-value.

Exploration of the interaction mechanism of lignocellulosic hybrid systems based on deep eutectic solvents.

The interactions of three deep eutectic solvents (DES) choline chloride-glycerol (ChCl-GLY), ChCl-lactic acid (ChCl-LA) and ChCl-urea (ChCl-U) with cellulose-hemicellulose and cellulose-lignin hybrid systems were investigated using the simulated computational approach. Aiming to simulate DES pretreatment of real lignocellulosic biomass in nature. DES pretreatment could disrupt the original hydrogen bonding network structure among the lignocellulosic components and reconstruct the new DES-lignocellulosic hydrogen bonding network structure. ChCl-U had the highest intensity of action on the hybrid systems, removing 78.3% of the hydrogen bonds between cellulose-4-O-methyl Gluconic acid xylan (cellulose-Gxyl) and 68.4% of the hydrogen bonds between cellulose-Veratrylglycerol-b-guaiacyl ether (cellulose-VG), respectively. The increase of urea content facilitated the interaction between DES and lignocellulosic blend system. Finally, the addition of appropriate water (DES:H2O = 1:5) and DES formed the new DES-water hydrogen bonding network structure more favorable for the interaction of DES with lignocellulose.

Theoretical study of lactic acid-based deep eutectic solvents dissociation of hemicellulose with different hydrogen bonding acceptors.

This paper explored the mechanism of dissociation of hemicellulose using lactic acid (LA)-based deep eutectic solvents (DESs) synthesized with different hydrogen bond acceptors (HBAs) via simulations. Density functional theory (DFT) calculations and molecular dynamics (MD) simulations revealed that DESs synthesized with guanidine hydrochloride (GuHCl) as hydrogen bond acceptor (HBA) demonstrated better hemicellulose solubilization compared to the conventional DESs synthesized using choline chloride (ChCl) as HBA. The best interaction with hemicellulose was achieved at GuHCl:LA = 1:1. The results showed that CL- played a dominant role in the dissolution of hemicellulose by DESs. Unlike ChCl, the guanidine group in GuHCl had the delocalized π bond, which made CL- have stronger coordination ability and promoted dissolution of hemicellulose by DESs. Moreover, multivariable analysis was employed to establish the correlation between the effects of different DESs on hemicellulose and the molecular simulation results. Additionally, the influence of different HBAs functional groups and carbon chain length on the solubilization of hemicellulose by DESs were analyzed.

Advances in machine learning for high value-added applications of lignocellulosic biomass.

Lignocellulose can be converted into biofuel or functional materials to achieve high value-added utilization. Biomass utilization process is complex and multi-dimensional. This paper focuses on the biomass conversion reaction conditions, the preparation of biomass-based functional materials, the combination of biomass conversion and traditional wet chemistry, molecular simulation and process simulation. This paper analyzes the mechanism, advantages and disadvantages of important machine learning (ML) methods. The application examples of ML in different aspects of high value utilization of lignocellulose are summarized in detail. The challenges and future prospects of ML in this field are analyzed.

Mechanism study of ternary deep eutectic solvents with protonic acid for lignin fractionation.

This paper investigated the fractionation of lignin by ternary DES of different polyols using simulation calculation. ChCl-EG-PTSA showed the highest degradability of lignin with the absolute value of total interaction energy of -8023.80 kJ/mol, and the total number of hydrogen bonds was 91.4. The highest degradability was observed for ChCl:EG: PTSA = 2:4:1. The results show that CL- plays a dominant role in lignin fractionation and readily forms hydrogen bonds with γ-OH. The difference is that the polyol preferred to form hydrogen bonds with α-OH in lignin. The addition of PTSA provided protons to the original system. It formed a new π-π stacking interaction with the lignin benzene ring, which destroyed the π-π stacking interaction between the original lignin. And increased the interaction of DES on lignin from -39.73 kcal/mol to -58.15 kcal/mol based on DFT.

Comprehensive analysis of important parameters of choline chloride-based deep eutectic solvent pretreatment of lignocellulosic biomass.

Choline chloride based deep eutectic solvents have showed great potential in lignocellulosic biomass pretreatment. In this study, for DES pretreatment with different hydrogen bond donners of different raw materials under different reaction conditions, multivariate analysis methods including principal component analysis and partial least squares analysis were used for reveal the pretreatment mechanism by evaluating the inner relationships among 42 key process factors. Furthermore, based on molecular simulation, the detailed relationships between key variables were further analyzed. Meanwhile, four-dimensional color graphs were used to intuitively reveal the synergistic influence of multivariate conditions variables on pretreatment effect to obtain better economic benefits and energy consumption indicators for DES pretreatment. The results showed that HBD hydrophilic ability, HBD polarity, HBD acidity, HBD ability to form hydrogen bonds, molar ratio of HBD to choline chloride and pretreatment severity had great influence on the Choline chloride based deep eutectic solvents pretreatment effect.

Key process parameters for deep eutectic solvents pretreatment of lignocellulosic biomass materials: A review.

Deep eutectic solvent (DES) has been considered as a novel green solvent for lignocellulosic biomass pretreatment. The efficiency of DES pretreatment is affected by the synergy of various process parameters. The study of effect of DES physicochemical properties and pretreatment reaction conditions on the mechanism of lignocellulose biomass fractionation was of great significance for the development of biomass conversion. Form the view of process control, this review summarized recent advances in DES pretreatment, analyzed the challenges, and prospected the future development of this research field.

Effect of crystallinity on pretreatment and enzymatic hydrolysis of lignocellulosic biomass based on multivariate analysis.

In this work, multivariate data analysis was employed to correlate variables of pretreatment process of lignocellulosic biomass. Principal component analysis and partial least square methods were performed to get the inner-relationship and data interpretation between the crystallinity and other parameters of mechanical refining-assisted sodium hydroxide pretreatment followed by enzymatic saccharification of corn stover. The PCA and PLS models showed that Sodium hydroxide dosage, mechanical refining treatment, lignin removal rate and crystallinity had close inner-related relationship with the efficiency of pretreatment and enzymolysis. Alkaline reaction and mechanical refining treatment had strong influence on the crystallinity. Multivariate data analysis revealed that pretreated corn stover samples with lower crystallinity were more easily hydrolyzed by enzyme and could get more final reducing sugar. This work could offer a new methodology to get further understanding of effect of crystallinity on the crop residue lignocellulosic biomass conversion process.

Boosting ORR Catalytic Activity by Integrating Pyridine-N Dopants, a High Degree of Graphitization, and Hierarchical Pores into a MOF-Derived N-Doped Carbon in a Tandem Synthesis.

N-doped carbon materials represent promising metal-free electrocatalysts for the oxygen reduction reaction (ORR), the cathode reaction in fuel cells, metal-air batteries, and so on. A challenge for optimizing the ORR catalytic activities of these electrocatalysts is to tune their local structures and chemical compositions in a rational and controlled way that can achieve the synergistic function of each factor. Herein, we report a tandem synthetic strategy that integrates multiple contributing factors into an N-doped carbon. With an N-containing MOF (ZIF-8) as the precursor, carbonization at higher temperatures leads to a higher degree of graphitization. Subsequent NH3 etching of this highly graphitic carbon enabled the introduction of a higher content of pyridine-N sites and higher porosity. By optimizing these three factors, the resultant carbon materials displayed ORR activity that was far superior to that of carbon derived from a one-step pyrolysis. The onset potential of 0.955 V versus a reversible hydrogen electrode (RHE) and the half-wave potential of 0.835 V versus RHE are among the top ranks of metal-free ORR catalysts and are comparable to commercial Pt/C (20 wt %) catalysts. Kinetic studies revealed lower H2 O2 yields, higher electron-transfer numbers, and lower Tafel slopes for these carbon materials compared with that derived from a one-step carbonization. These findings verify the effectiveness of this tandem synthetic strategy to enhance the ORR activity of N-doped carbon materials.

CRGO/alginate microbeads: an enzyme immobilization system and its potential application for a continuous enzymatic reaction.

In this work, novel hybrid microbeads composed of chemically reduced graphene oxide (CRGO) and alginate were fabricated, which could encapsulate enzymes by a simple non-covalent adsorption-entrapment method. Compared with alginate gel beads, the intervention of CRGO in the alginate gel enhanced its mechanical strength, effectively prevented the leakage of enzyme, and greatly enhanced the stability and environmental tolerance. Compared with free enzymes or those on a single carrier, the enzyme encapsulated in these hybrid microbeads can retain its optimum activity within a broad range (temperature 45-60 °C, pH 4-6). Additionally, the microbeads can be easily recycled by simple filtration and filled into a column to achieve a continuous fixed-bed enzyme catalytic reaction.

Quantitative characterization of the impact of pulp refining on enzymatic saccharification of the alkaline pretreated corn stover.

In this work, corn stover was refined by a pulp refining instrument (PFI refiner) after NaOH pretreatment under varied conditions. The quantitative characterization of the influence of PFI refining on enzymatic hydrolysis was studied, and it was proved that the enhancement of enzymatic saccharification by PFI refining of the pretreated corn stover was largely due to the significant increment of porosity of substrates and the reduction of cellulose crystallinity. Furthermore, a linear relationship between beating degree and final total sugar yields was found, and a simple way to predict the final total sugar yields by easily testing the beating degree of PFI refined corn stover was established. Therefore, this paper provided the possibility and feasibility for easily monitoring the fermentable sugar production by the simple test of beating degree, and this will be of significant importance for the monitoring and controlling of industrial production in the future.