Superwetting Ag/α-Fe_(2)O_(3) anchored mesh with enhanced photocatalytic and antibacterial activities for efficient water purification

Superwetting materials have drawn unprecedented attention in the treatment of oily wastewater due to their preferable anti-fouling property and selective oil/water separation.However,it is still a challenge to fabricate multifunctional and environmentally friendly materials,which can be stably applied to purify the actual complicated wastewater.Here,a Ag/Ag/α-Fe_(2)O_(3) heterostructure anchored copper mesh was intentionally synthesized using a facile two-step hydrothermal method.The resultant mesh with superhydrophilicity and underwater superoleophobicity was capable of separating various oil/water mixtures with superior separation efficiency and high permeationflux driven by gravity.Benefiting from the joint effects of the smaller band gap of Ag/α-Fe_(2)O_(3) heterojunction,inherent antibacterial capacity of Ag/α-Fe_(2)O_(3) and Ag nanoparticles,favorable conductive substrate,as well as the hierarchical structure with superwettability,such mesh presented remarkably enhanced degradation capability toward organic dyes under visible light irradiation and antibacterial activity against both Escherichia coli(E.coli)and Staphylococcus aureus(S.aureus)compared with the pure Ag/α-Fe_(2)O_(3) coated mesh.Impressively,the mesh exhibited bifunctional water purification performance,in which organic dyes were eliminated simultaneously from water during oil/water separation in onefiltration process.More importantly,this mesh behaved exceptional chemical resistance,mechanical stability and long-term reusability.Therefore,this material with multifunctional integration may hold promising potential for steady water purification in practice.

Enhancing Relational Triple Extraction in Specific Domains:Semantic Enhancement and Synergy of Large Language Models and Small Pre-Trained Language Models

In the process of constructing domain-specific knowledge graphs,the task of relational triple extraction plays a critical role in transforming unstructured text into structured information.Existing relational triple extraction models facemultiple challenges when processing domain-specific data,including insufficient utilization of semantic interaction information between entities and relations,difficulties in handling challenging samples,and the scarcity of domain-specific datasets.To address these issues,our study introduces three innovative components:Relation semantic enhancement,data augmentation,and a voting strategy,all designed to significantly improve the model’s performance in tackling domain-specific relational triple extraction tasks.We first propose an innovative attention interaction module.This method significantly enhances the semantic interaction capabilities between entities and relations by integrating semantic information fromrelation labels.Second,we propose a voting strategy that effectively combines the strengths of large languagemodels(LLMs)and fine-tuned small pre-trained language models(SLMs)to reevaluate challenging samples,thereby improving the model’s adaptability in specific domains.Additionally,we explore the use of LLMs for data augmentation,aiming to generate domain-specific datasets to alleviate the scarcity of domain data.Experiments conducted on three domain-specific datasets demonstrate that our model outperforms existing comparative models in several aspects,with F1 scores exceeding the State of the Art models by 2%,1.6%,and 0.6%,respectively,validating the effectiveness and generalizability of our approach.

Combining ability for main quality traits in peanut(Arachis hypogaea L.)

High-oleic peanuts has been recognized by processing sectors,seed sellers and consumers for their longer shelf life,longer seed life and mutiple healthe benefits.High oleate is becoming a requisite for varietal releases in many peanut breeding programs at present.To select desirable parents for high-oleic peanut breeding,the study was conducted to evaluate the combining ability of 5 high-oleic donors from our research team,based on quality of individual single seeds.General combining ability was significant for oleic,linoleic,stearic and palmitic acid,oil and protein,while specific combining ability was significant for the traits except oil.Among them,oil content was found to be conditioned solely by additive gene actions,and for other quality traits,additive gene effects were more important than non-additive gene effects.High-oleic CTW and normal-oleic Xiaojingsheng were selected as the best general combiners for peanut oleic acid improvement.Narrow-sense heritability was high for quality traits other than protein,suggesting that there was high potential for genetic improvement in these traits.

Highly Durable Ag-CuO Heterostructure-Decorated Mesh for Efficient Oil/Water Separation and In Situ Photocatalytic Dye Degradation

It is of great necessity yet still a challenge to develop superwetting functional interfacial materials for simultaneously separating insoluble oil and degrading soluble dye pollutants in practical wastewater.In this work,a Ag-CuO heterostructure-decorated mesh was fabricated via facile alkali etchingcalcination and photoreduction approaches.The as-synthesized mesh with superhydrophilicity and underwater superoleophobicity displayed high separation efficiency(>99.998%)for diverse oil/water mixtures.Besides,it demonstrated more superior photocatalytic performance in dye degradation than those of bare CuO nanostructure-coated materials,which is primarily attributed to the intensive visible light harvesting and efficient electron-holes separation occurred on noble metal-semiconductor heterostructures.Furthermore,on account of the tenacity of Cu substrate as well as enhanced structural stability,this binary composite-decorated mesh exhibited highly reliable durability and robustness after 10 cycles of photocatalytic degradation tests,and even being ultrasonic worn for 30 min.More importantly,our developed mesh was capable of in situ catalytic degrading water-soluble organic dyes during oil/water separation under visible light irradiation.Therefore,such a dexterous and feasible strategy may afford a new route to construct bifunctional and predurable materials for actual sewage purification.

Modified Coffin-Manson equation to predict the fatigue life of structural materials subjected to mechanical-thermal coupling non-coaxial loading

With regard to the structures subjected to severe mechanical-thermal coupling fatigue conditions,the consistency between service conditions and loading conditions was the prerequisite for the fatigue prop-erties test and fatigue life prediction.A miniature piezoelectric-driven instrument integrating with a tripodal piezoelectric actuator and envelope-type heating function was developed to investigate the mechanical-thermal coupling fatigue properties and obtain the fatigue life of materials under approximate service conditions.A physical model was described to quantitatively calculate the alternating deformation under the mechanical-thermal coupling tensile-bending combined condition.Accordingly,a fatigue life prediction method based on the Coffin-Manson equation under tensile-bending combined loading was proposed to estimate the mechanical-thermal coupling fatigue life in terms of the total coupling defor-mation and plastic strain amplitude.The feasibility of the proposed instrument was verified through the analysis of displacement responses of high entropy alloy specimens under the thermal-mechanical cou-pling tensile-bending combined condition at temperatures ranging from RT to 600°C.The comparison between fatigue lives directly measured through thermal-mechanical coupling experiments and theoreti-cally predicted fatigue lives indicated the availability of the modified Coffin-Manson equation.

Band-structure-engineered high-gain LWIR photodetector based on a type-Ⅱ superlattice

The LWIR and longer wavelength regions are of particular interest for new developments and new approaches to realizing long-wavelength infrared(LWIR)photodetectors with high detectivity and high responsivity.These photodetectors are highly desirable for applications such as infrared earth science and astronomy,remote sensing,optical communication,and thermal and medical imaging.Here,we report the design,growth,and characterization of a high-gain band-structure-engineered LWIR heterojunction phototransistor based on type-Ⅱ superlattices.The 1/e cut-off wavelength of the device is 8.0 pm.At 77 K,unity optical gain occurs at a 90 mV applied bias with a dark current density of 3.2×10^(-7)A/cm^(2).The optical gain of the device at 77 K saturates at a value of 276 at an applied bias of 220 mV.This saturation corresponds to a responsivity of 1284 A/W and a specific detectivity of 2.34×10^(13)cm Hz^(1/2)/W at a peak detection wavelength of~6.8 pm.The type-Ⅱ superlattice-based high-gain LWIR device shows the possibility of designing the high-performance gain-based LWIR photodetectors by implementing the band structure engineering approach.