The structure–activity relationships of Rh/CeO_(2)-ZrO_(2) catalysts based on Rh metal size effect in the three-way catalytic reactions

With the continuous tightening of automotive emission regulations and the increasing promotion of energy-efficient hybrid vehicles,new challenges have arisen for the low-temperature performance of three-way catalysts(TWCs).To guide the design of next-generation TWCs,it is essential to further develop our understanding of the relationships between microstructure and catalytic performance.Here,Rh/CeO_(2)–ZrO_(2) catalysts were synthesized with different Rh metal dispersion by using a combination of the wet impregnation method and reduction treatment.These catalysts included Rh single-atom catalysts,cluster catalysts,and nanoparticle catalysts.The results showed that the Rh nanoparticle catalyst,with an average size of 1.9 nm,exhibited superior three-way catalytic performance compared to the other catalysts.Based on the catalytic activity in a series of simple reaction atmospheres such as CO+O_(2),NO+CO,and hydrocarbons(HCs)+O_(2) and operando infrared spectroscopy,we found that metallic Rh sites on Rh nanoparticles are the key factor responsible for the low-temperature catalytic performance.

Inhibition mechanisms of ammonia and sulfate in high-solids anaerobic digesters for food waste treatment: Microbial community and element distributions responses

The horizontal flow anaerobic digester indicated that high ammonia (2923 mg/L) and SO42-(3653 mg/L)would influence the performance of methane production with food waste as substrates.Therefore,bottle anaerobic digestion reactors were carried out to investigate the effect of ammonia/sulfate concentrations on the methane production.Experimental results manifested that the anaerobic digesters with an ammonia concentration of 3500 mg/L or sulfate of 1600 mg/L showed the best performance of methane production,with an average methane yield of 0.32 and 0.33 L (g VS)^(-1)d^(-1),respectively.Specifically,a higher ammonia (6500 mg/L) or sulfate (1600-3500 mg/L) level hindered the bioconversion of C from liquid to gas phase (2.68%or 1.73%CH_(4)-Gas,respectively),while insignificantly for the hydrolyzation of C and N from solid to liquid phase.Similar to sulfate,high ammonia nitrogen seriously inhibited the methanation process,leading to a significant carbon accumulation in the anaerobic reactor,especially for propionic acid.The predominant archaea Methanosarcina at genus level indicated that aceticlastic methanogenesis was the major methanogenic pathway.Meanwhile,high ammonia level suppressed the activity of Methanosarcina,while modest sulfate improved H_(2)-consuming methanogens activity.A large fraction of unclassified bacteria within the Firmicutes (43.78%-63.17%) and Bacteroidetes (24.20%-33.30%) phylum played an important role in substrates hydrolysis.

Extracellular polymeric substances-antibiotics interaction in activated sludge:A review

Antibiotics,the most frequently prescribed drugs,have been widely applied to prevent or cure human and veterinary diseases and have undoubtedly led to massive releases into sewer networks and wastewater treatment systems,a hotspot where the occurrence and transformation of antibiotic resistance take place.Extracellular polymeric substances(EPS),biopolymers secreted via microbial activity,play an important role in cell adhesion,nutrient retention,and toxicity resistance.However,the potential roles of sludge EPS related to the resistance and removal of antibiotics are still unclear.This work summarizes the composition and physicochemical characteristics of state-of-the-art microbial EPS,highlights the critical role of EPS in antibiotics removal,evaluates their defense performances under different antibiotics exposures,and analyzes the typical factors that could affect the sorption and biotransformation behavior of antibiotics.Next,interactions between microbial EPS and antibiotic resistance genes are analyzed.Future perspectives,especially the engineering application of microbial EPS for antibiotics toxicity detection and defense,are also emphatically stressed.

一种可促进重组蛋白表达量和稳定性的多功能纯化标签的开发与利用

自组装双亲短肽(Self-assembling amphipathic peptides,SAPs)是一类亲疏水氨基酸按一定规律分布、具有自聚合效应的短肽,融合在酶蛋白N端时,具有促进表达和稳定化的功能。根据前期研究结论,设计一条全新的基于SAPs (S1vw,HNANARARHNANARARHNANARARHNARARAR)的可促进融合蛋白表达和稳定性,并可用于镍柱亲和层析的多功能短肽标签,在大肠杆菌表达系统中,将S1vw以PT-linker(PTPPTTPTPPTTPTP)融合在碱性果胶酶(Alkaline polygalacturonate lyase,PGL)、脂肪氧合酶(Lipoxygenase,LOX)及绿色荧光蛋白(Green fluorescent protein,GFP)的N末端时,与对应的野生型相比,PGL及LOX的粗酶活分别提高了3.1倍和1.89倍,GFP的荧光强度提高了16.22倍。S1vw的3种融合酶均可用镍柱进行亲和纯化,并具有较高的回收率。PGL及LOX在对应的热处理条件下,与野生型相比,半衰期分别提高了2.16倍和3.2倍。将GFP-S1vw在枯草芽孢杆菌及毕赤酵母表达系统中表达,发现在枯草芽孢杆菌中融合蛋白表达量提高明显,但在毕赤酵母中表达量几乎没有改变。说明在原核表达体系中,S1vw可作为一种新型的促表达、稳定化及可纯化的多功能标签。

A uncertainty visual analytics approach for bus travel time

Bus travel time is uncertain due to the dynamic change in the environment.Passenger analyzing bus travel time uncertainty has significant implications for understanding bus running errors and reducing travel risks.To quantify the uncertainty of the bus travel time prediction model,a visual analysis method about the bus travel time uncertainty is proposed in this paper,which can intuitively obtain uncertain information of bus travel time through visual graphs.Firstly,a Bayesian encoder–decoder deep neural network(BEDDNN)model is proposed to predict the bus travel time.The BEDDNN model outputs results with distributional properties to calculate the prediction model uncertainty degree and provide the estimation of the bus travel time uncertainty.Second,an interactive uncertainty visualization system is developed to analyze the time uncertainty associated with bus stations and lines.The prediction model and the visualization model are organically combined to better demonstrate the prediction results and uncertainties.Finally,the model evaluation results based on actual bus data illustrate the effectiveness of the model.The results of the case study and user evaluation show that the visualization system in this paper has a positive impact on the effectiveness of conveying uncertain information and on user perception and decision making.