Selective Removal of Hemicellulose by Diluted Sulfuric Acid Assisted by Aluminum Sulfate.

Hemicellulose can be selectively removed by acid pretreatment. In this study, selective removal of hemicellulose was achieved using dilute sulfuric acid assisted by aluminum sulfate pretreatment. The optimal pretreatment conditions were 160 °C, 1.5 wt% aluminum sulfate, 0.7 wt% dilute sulfuric acid, and 40 min. A component analysis showed that the removal rate of hemicellulose and lignin reached 98.05% and 9.01%, respectively, which indicated that hemicellulose was removed with high selectivity by dilute sulfuric acid assisted by aluminum sulfate pretreatment. Structural characterizations (SEM, FTIR, BET, TGA, and XRD) showed that pretreatment changed the roughness, crystallinity, pore size, and functional groups of corn straw, which was beneficial to improve the efficiency of enzymatic hydrolysis. This study provides a new approach for the high-selectivity separation of hemicellulose, thereby offering novel insights for its subsequent high-value utilization.

Corn-derived Expansin synergistically promotes enzymatic hydrolysis of corn cob.

The enzymatic hydrolysis of lignocellulose is hindered by challenges such as high enzyme usage and associated costs. It is essential to explore effective approaches to improve the efficiency of enzymatic hydrolysis while reducing costs. Expansins are non-enzymatic proteins that can interact with lignocellulose and facilitate the loosening of plant cell walls. Given their natural affinity to plant cell walls, we hypothesized that a corn Expansin could enhance the enzymatic hydrolysis of corn lignocellulose. In this study, we expressed a corn (Zea mays) Expansin, EXPA17, in yeast cells and explored the synergistic effect between EXPA17 and commercial cellulase, and found that EXPA17 exhibited a pronounced synergistic effect on the enzymatic hydrolysis of corn cobs. The addition of 0.015 mg/mL EXPA17 resulted in a 14.00 % increase in glucose yield. Fourier-transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) analysis revealed that EXPA17 proteins disrupted hydrogen bonds in the amorphous regions of corn cobs, leading to a more porous and looser structure, thereby enhancing cellulose accessibility. Our work leveraged the synergistic effect between Expansin and lignocellulose from the same source of corn, providing a novel strategy to improve the efficiency of enzymatic hydrolysis of corn lignocellulose while potentially reducing the associated costs.

Adsorption of Pb2+, Cu2+ and Cd2+ by sulfhydryl modified chitosan beads.

A chitosan-based bead was synthesized by crosslinking as well as sulfhydryl modification reaction and its removal ability of Pb2+, Cu2+ and Cd2+ was investigated. The test results showed that the crystal structure of chitosan was destroyed completely and the specific surface area was greatly increased after modification. The adsorption of Pb2+, Cu2+ and Cd2+ by the beads was carried out at different pH, ionic strength, contact time and initial concentration and the maximum adsorption capacities were 273.7 mg/g, 163.3 mg/g and 183.1 mg/g, respectively. Furthermore, due to the large ion radius of Pb2+, its adsorption was seriously disturbed by other ions in the competitive adsorption process. Finally, the adsorption processes of Pb2+, Cu2+ and Cd2+ were well fitted by the Langmuir isotherm model and the pseudo second-order kinetics model, respectively. Combined with the results of X-ray photoelectron spectroscopy, chemical coordination is the main adsorption mechanism.

Preparation of a novel bio-adsorbent of sodium alginate grafted polyacrylamide/graphene oxide hydrogel for the adsorption of heavy metal ion.

A novel bio-adsorbent named SA-PAM/GO hydrogel composites was synthesized through free radical polymerization. The structure and performance were characterized and analyzed by BET, SEM-EDS, FTIR and TGA. After modification, the BET surface area increased more than tripled, which was consistent with SEM results. Under optimal conditions, the maximum adsorption capacity of Cu2+ and Pb2+ were 68.76 mg/g and 240.69 mg/g, respectively. In addition, the research of kinetics and isotherms displayed that the pseudo-second-order kinetic model and the Langmuir isotherm model fitted the data well. After further research, the different adsorption mechanism including physical adsorption, chemical adsorption and electrostatic interactions were discussed. The chemical adsorption accompanying the ion exchange process was confirmed as the staple adsorption mechanism. Furthermore, the adsorbent still maintained good adsorption capacity after 5 cycles of adsorption-regeneration. Therefore, the SA-PAM/GO hydrogel composites have potential to remove the heavy metal ions from water body effectively.

Preparation of acrylamide/acrylic acid cellulose hydrogels for the adsorption of heavy metal ions.

Modified cellulose hydrogels were prepared by blending and cross-linking with acrylamide and acrylic acid. The structure of hydrogels was characterized and analyzed with fourier transform infrared spectroscopy (FTIR), X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). Under the optimized conditions, the maximum absorption capacity in modified cellulose hydrogels of Cu (II), Pb (II) and Cd (II) ions were 157.51, 393.28 and 289.97 mg/g, respectively. In addition, the metal ion adsorption process accorded with pseudo-second-order rate equation and Langmuir adsorption isotherm. Based on the microstructure analysis and adsorption kinetics, the adsorption mechanisms such as physical, chemical, and electrostatic interactions are discussed. The adsorption process was controlled by the ion-exchange mechanism.

Research and improvement of ECG compression algorithm based on EZW.

Embedded zerotree wavelet (EZW) is an efficient compression method that has advantages in coding, but its multilayer structure information coding reduces signal compression ratio. This paper studies the optimization of the EZW compression algorithm and aims to improve it. First, we used lifting wavelet transformation to process electrocardiograph (ECG) signals, focusing on the lifting algorithm. Second, we utilized the EZW compression coding algorithm, through the ECG information decomposition to determine the feature detection value. Then, according to the feature information, we weighted the wavelet coefficients of ECG (through the coefficient as a measure of weight) to achieve the goal of improved compression benefit.