Removal behavior and mechanism of silver from low concentration wastewater using cellulose aerogel modified by thiosemicarbazide

Due to the low concentration of silver in water, most of the cellulose adsorbents exhibited low removal efficiency, which greatly limited their practical applications. Herein, a cellulose aerogel modified by thiosemicarbamide (CAT) was fabricated for reducing and adsorbing silver ions from low concentration wastewater. The characterization results concluded that CAT owned a three-dimensional spongy structure with many circular microspheres and a better specific surface area (19.37 m² g⁻¹), as well as the functional groups of ─C═N⁺─H and ─(C═S)─N. The static batch adsorption experiments demonstrated that CAT could reached the maximum removal percentage of 94.94% and adsorption capacity of 42.12 mg g⁻¹ under the initial concentration of Ag(I) was 15 mg L⁻¹ and the pH value was 7. Meanwhile, the adsorption of Ag(I) on CAT was second-order reaction, and the Langmuir model could better fit the adsorption process. In addition, CAT exhibited wide pH values (1–9) adaptability and excellent adsorption performance for silver through electrostatic interaction, chelation, and reduction. This study probably provides a new method as well as important experimental data and theoretical reference for the removal of silver ions and other metals.     

Viscoelastic properties and flow instabilities of aqueous suspensions of cellulosic fibers: Effects of a gelation agent on dispersion,rheology, and flow stability

Processing of concentrated lignocellulosic biomass suspensions typically involves the conversion of the cellulose into sugars and sugars into ethanol. Biomass is usually pretreated via methods like comminution or steam explosion to form fine cellulosic fibers to be dispersed into an aqueous phase for further treatment. The resulting cellulose suspensions need to be pressurized and pumped into and out of various processing vessels without allowing the development of flow instabilities that are typically associated with “demixing”, that is, the segregation of the cellulosic biomass from the aqueous phase via the formation of mats of cellulosic fibers and the filtration of the aqueous phase. Such demixing can prevent continuous processing at high rates. Here, the development of flow instabilities via the demixing effect for cellulose suspensions is demonstrated using capillary and compressive squeeze flows. It is shown that the use of a gelation agent, hydroxypropyl guar gum, at the critical concentration of 0.5 wt% or higher significantly affects the viscoelastic material functions of cellulosic suspensions, improves the dispersive mixing of the fibers within the aqueous phase, and results in the elimination of the flow instabilities and associated demixing effects that are ubiquitously observed during the pressurization and processing of cellulosic suspensions.     

Effect of processing techniques and residual solvent on the thermal/mechanical properties of epoxy-cellulose nanocrystal nanocomposites

Epoxy nanocomposites reinforced with 0–5 wt% cellulose nanocrystal (CNC) were fabricated by solution casting method. The CNCs were first dispersed in the hardener together with a co-solvent and subsequently mixed with epoxy monomer using two different protocols: bulk mixing and dropwise mixing. The dropwise mixing resulted in more homogeneously-dispersed CNCs and provided better mechanical properties, particularly higher tensile strength, tensile modulus, and work of fracture with increasing CNC content. Investigation of various CNC/hardener mixtures with different solvent content showed that the residual solvent in the composite mixture had an impact on the curing behavior of the nanocomposite epoxy and may have lowered its crosslinking density, leading to T_g depression. However, the presence of the solvent was shown to be essential for the preparation of a well-dispersed CNC phase in the hardener solution, and to form homogenous composite mixtures. Our results show that the reinforcement effect due to higher CNC concentration is more significant than the solvent effect in the hardener system and shows greater improvement in mechanical properties. The CNC component reversed the solvent plasticizing effect through its superior mechanical reinforcing effects, and the dropwise mixing process led to better dispersion compared with the bulk mixing process.     

The challenge of predicting spinnability: Investigating benefits of adding lignin to cellulose solutions in air-gap spinning

In this study, the underlying mechanism for improved spinnability when mixing lignin and cellulose in solution was investigated. Co-processing of lignin and cellulose has previously been identified as a potential route for production of inexpensive and bio-based carbon fibers. The molecular order of cellulose contributes to the strength of the fibers and the high carbon content of lignin improves the yield during conversion to carbon fibers. The current work presents an additional benefit of combining lignin and cellulose; solutions that contain both lignin and cellulose could be air-gap spun at substantially higher draw ratios than pure cellulose solutions, that is, lignin improved the spinnability. Fibers were spun from solutions containing different ratios of lignin, from 0 to 70 wt%, and the critical draw ratio was determined at various temperatures of solution. The observations were followed by characterization of the solutions with shear and elongational viscosity and surface tension, but none of these methods could explain the beneficial effect of lignin on the spinnability. However, by measuring the take-up force it was found that lignin seems to stabilize against diameter fluctuations during spinning, and plausible explanations are discussed.     

下向焊仰位操作技能

分析了下向焊接工艺(特别是纤维素打底)焊接时产生焊缝背面内凹、打底焊道烧穿、焊缝夹渣、未熔合、咬边、焊缝成形不良等缺陷的原因.针对这些缺陷提出了根焊、填充焊、盖面焊的操作技能,获得了下向焊仰位焊的合格焊缝.     

土壤中SRB及Cl-对1Cr18Ni9Ti不锈钢腐蚀的相互影响

利用交流阻抗测试技术、扫描电镜及表面能谱、失重法、微生物分析等方法 ,研究了在不同Cl-含量的土壤中 ,硫酸盐还原菌对 1Cr18Ni9Ti不锈钢腐蚀的影响规律 .13 6d的试验结果表明 ,不同Cl-含量土壤中SRB菌量在2 3 0 0 0～ 3 5 0 0 0 (个 /克土 )之间 ,Cl-的加入并没有显著影响SRB的生长 ,随着Cl-的加入土壤中SRB的菌量有增大的趋势 ;随着土壤中Cl-含量的增大 ,不锈钢腐蚀电位负偏移 ,而且在接菌土壤中的腐蚀电位比在灭菌土壤中负移幅度更大 ;不锈钢在灭菌土壤中没有发生点蚀现象 ,而在接菌土壤中发生了严重的点蚀 ,最大点蚀深度随着土壤中Cl-含量的增加而增大 ,这说明在土壤中SRB及Cl-的共同作用下 ,增大了不锈钢的点蚀敏感性 .不锈钢在灭菌土壤中的阻抗图谱表现为一个半径很大的容抗弧 ,而在接菌土壤中的阻抗图表现为两个时间常数的双容抗弧     

基于Levy飞行的改进菌群觅食算法

针对经典菌群觅食算法因固定趋化步长导致的求解精度不高、收敛性能差等缺陷,提出一种基于Levy飞行的菌群觅食算法,其特点是利用基于Levy分布的趋化步长改善算法的求解精度与收敛性能,借助Levy飞行随机游走策略改善细菌迁徙位置.多个基准测试函数的实验结果表明,该算法在求解质量和收敛性能上均取得了较好的改进效果.     

Nanocellulose-Carboxymethylcellulose Electrolyte for Stable,High-Rate Zinc-Ion Batteries

Aqueous Zn ion batteries (ZIBs) are one of the most promising battery chemistries for grid-scale renewable energy storage. However, their application is limited by issues such as Zn dendrite formation and undesirable side reactions that can occur in the presence of excess free water molecules and ions. In this study, a nanocellulose-carboxymethylcellulose (CMC) hydrogel electrolyte is demonstrated that features stable cycling performance and high Zn²⁺ conductivity (26 mS cm⁻¹), which is attributed to the material's strong mechanical strength (≈70 MPa) and water-bonding ability. With this electrolyte, the Zn-metal anode shows exceptional cycling stability at an ultra-high rate, with the ability to sustain a current density as high as 80 mA cm⁻² for more than 3500 cycles and a cumulative capacity of 17.6 Ah cm⁻² (40 mA cm⁻²). Additionally, side reactions, such as hydrogen evolution and surface passivation, are substantially reduced due to the strong water-bonding capacity of the CMC. Full Zn||MnO₂ batteries fabricated with this electrolyte demonstrate excellent high-rate performance and long-term cycling stability (>500 cycles at 8C). These results suggest the cellulose-CMC electrolyte as a promising low-cost, easy-to-fabricate, and sustainable aqueous-based electrolyte for ZIBs with excellent electrochemical performance that can help pave the way toward grid-scale energy storage for renewable energy sources.     

Bacteria-Responsive Self-Assembly of Antimicrobial Peptide Nanonets for Trap-and-Kill of Antibiotic-Resistant Strains

Bacterial trapping using nanonets is a ubiquitous immune defense mechanism against infectious microbes. These nanonets can entrap microbial cells, effectively arresting their dissemination and rendering them more vulnerable to locally secreted microbicides. Inspired by this evolutionarily conserved anti-infective strategy, a series of 15 to 16 residue-long synthetic β-hairpin peptides is herein constructed with the ability to self-assemble into nanonets in response to the presence of bacteria, enabling spatiotemporal control over microbial killing. Using amyloid-specific K114 assay and confocal microscopy, the membrane components lipoteichoic acid and lipopolysaccharide are shown to play a major role in determining the amyloid-nucleating capacity as triggered by Gram-positive and Gram-negative bacteria respectively. These nanonets displayed both trapping and killing functionalities, hence offering a direct improvement from the trap-only biomimetics in literature. By substituting a single turn residue of the non-amyloidogenic BTT1 peptide, the nanonet-forming BTT1-3A analog is produced with comparable antimicrobial potency. With the same sequence manipulation approach, BTT2-4A analog modified from BTT2 peptide showed improved antimicrobial potency against colistin-resistant clinical isolates. The peptide nanonets also demonstrated robust stability against proteolytic degradation, and promising in vivo efficacy and biosafety profile. Overall, these bacteria-responsive peptide nanonets are promising clinical anti-infective alternatives for circumventing antibiotic resistance.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.