Influence of external nitrogen-containing donors on polymerization behavior of neodymium-based cis-1,4-polybutadiene rubber

Neodymium(Nd)-based catalyst in butadiene(Bd)polymerization has drawn interests due to its availability in affording higher cis-1,4-unit selectivity than transition metal(Ti,Co,Ni,etc.)-based catalysts[1-2].Such outstanding high cis-1,4-unit selecti-vity is hypothetically originated from the presence of 4 f orbitals,that can participate in monomer coordination and thereby govern subsequent enchainment manners.This unique characteristic also renders the active species highly susceptible to Lewis bases,and may impact the overall selectivity as well as polyme-rization behavior after coordination.Nevertheless,it is still a virgin area in such a field,and the influence of Lewis bases on Nd-based diene polymerizations is still a black box.Based on this consideration,how nitrogen-containing donors(D)impacts the overall behaviors of Nd-mediated Bd polymerizations is disclosed.

Source localization based on field signatures:Laboratory ultrasonic validation

Location awareness in wireless networks is essential for emergency services,navigation,gaming,and many other applications.This article presents a method for source localization based on measuring the amplitude-phase distribution of the field at the base station.The existing scatterers in the target area create unique scattered field interference at each source location.The unique field interference at each source location results in a unique field signature at the base station which is used for source localization.In the proposed method,the target area is divided into a grid with a step of less than half the wavelength.Each grid node is characterized by its field signature at the base station.Field signatures corresponding to all nodes are normalized and stored in the base station as fingerprints for source localization.The normalization of the field signatures avoids the need for time synchronization between the base station and the source.When a source transmits signals,the generated field signature at the base station is normalized and then correlated with the stored fingerprints.The maximum correlation value is given by the node to which the source is the closest.Numerical simulations and results of experiments on ultrasonic waves in the air show that the ultrasonic source is correctly localized using broadband field signatures with one base station and without time synchronization.The proposed method is potentially applicable for indoor localization and navigation of mobile robots.

Flexible,thermal processable,self-healing,and fully bio-based starch plastics by constructing dynamic imine network

The serious environmental threat caused by petroleum-based plastics has spurred more researches in developing substitutes from renewable sources.Starch is desirable for fabricating bioplastic due to its abundance and renewable nature.However,limitations such as brittleness,hydrophilicity,and thermal properties restrict its widespread application.To overcome these issues,covalent adaptable network was constructed to fabricate a fully bio-based starch plastic with multiple advantages via Schiff base reactions.This strategy endowed starch plastic with excellent thermal processability,as evidenced by a low glass transition temperature(T_(g)=20.15℃).Through introducing Priamine with long carbon chains,the starch plastic demonstrated superior flexibility(elongation at break=45.2%)and waterproof capability(water contact angle=109.2°).Besides,it possessed a good thermal stability and self-adaptability,as well as solvent resistance and chemical degradability.This work provides a promising method to fabricate fully bio-based plastics as alternative to petroleum-based plastics.

Role of micro-Ca/In alloying in tailoring the microstructural characteristics and discharge performance of dilute Mg-Bi-Sn-based alloys as anodes for Mg-air batteries

The influence of micro-Ca/In alloying on the microstructural charac teristics,electrochemical behaviors and discharge properties of extruded dilute Mg-0.5Bi-0.5Sn-based(wt.%)alloys as anodes for Mg-air batteries are evaluated.The grain size and texture intensity of the Mg-Bi-Sn-based alloys are significantly decreased after the Ca/In alloying,particularly for the In-containing alloy.Note that,in addition to nanoscale Mg_(3)Bi_(2)phase,a new microscale Mg_(2)Bi_(2)Ca phase forms in the Ca-containing alloy.The electrochemical test results demonstrate that Ca/In micro-alloying can enhance the electrochemical activity.Using In to alloy the Mg-Bi-Sn-based alloy is effective in restricting the cathodic hydrogen evolution(CHE)kinetics,leading to a low self-corrosion rate,while severe CHE occurred after Ca alloying.The micro-alloying of Ca/In to Mg-Bi-Sn-based alloy strongly deteriorates the compactness of discharge products film and mitigates the"chunk effect"(CE),hence the cell voltage,anodic efficiency as well as discharge capacity are greatly improved.The In-containing alloy exhibits outstanding discharge performance under the combined effect of the modified microstructure and discharge products,thus making it a potential anode material for primary Mg-air battery.

Construction of coal pitch-based HA-K grafted poly condensates and their excellent anti-temperature and viscosity-reducing properties

Humic acids(HAs)are widely used as filtrate and viscosity reducers in drilling fluids.However,their practical utility is limited due to poor stability in salt resistance and high-temperature resistance.Hightemperature coal pitch(CP)is a by-product from coal pyrolysis above 650℃.The substance's molecular structure is characterized by a dense arrangement of aromatic hydrocarbon and alkyl substituents.This unique structure gives it unique chemical properties and excellent drilling performance,surpassing traditional humic acids in drilling operations.Potassium humate is prepared from CP(CP-HA-K)by thermal catalysis.A new type of high-quality humic acid temperature-resistant viscosity-reducer(Graft CP-HA-K polymer)is synthesized with CP-HA-K,hydrolyzed polyacrylonitrile sodium salt(Na-HPAN),urea,formaldehyde,phenol and acrylamide(AAM)as raw materials.The experimental results demonstrate that the most favorable conditions for the catalytic preparation of CP-HA-K are 1 wt%catalyst dosage,30 wt%KOH dosage,a reaction temperature of 250℃,and a reaction time of 2 h,resulting in a maximum yield of CP-HA-K of 39.58%.The temperature resistance of the Graft CP-HA-K polymer is measured to be 177.39℃,which is 55.39℃ higher than that of commercial HA-K.This is due to the abundant presence of amide,hydroxyl,and amine functional groups in the Graft CP-HA-K polymer,which increase the length of the carbon chains,enhance the electrostatic repulsion on the surface of solid particles.After being aged to 120℃ for a specified duration,the Graft CP-HA-K polymer demonstrates significantly higher viscosity reduction(42.12%)compared to commercial HA-K(C-HA-K).Furthermore,the Graft CP-HA-K polymer can tolerate a high salt concentration of 8000 mg.L-1,measured after the addition of optimum amount of 3 wt%Graft CP-HA-K polymer.The action mechanism of Graft CP-HA-K polymer on high-temperature drilling fluid is that the Graft CP-HA-K polymer can increase the repulsive force between solid particles and disrupt bentonite's reticulation structure.Overall,this research provides novelty insights into the synthesis of artificial humic acid materials and the development of temperature-resistant viscosity reducers,offering a new avenue for the utilization of CP resources.

Prediction of Lubricant Physicochemical Properties Based on Gaussian Copula Data Expansion

The composition of base oils affects the performance of lubricants made from them.This paper proposes a hybrid model based on gradient-boosted decision tree(GBDT)to analyze the effect of different ratios of KN4010,PAO40,and PriEco3000 component in a composite base oil system on the performance of lubricants.The study was conducted under small laboratory sample conditions,and a data expansion method using the Gaussian Copula function was proposed to improve the prediction ability of the hybrid model.The study also compared four optimization algorithms,sticky mushroom algorithm(SMA),genetic algorithm(GA),whale optimization algorithm(WOA),and seagull optimization algorithm(SOA),to predict the kinematic viscosity at 40℃,kinematic viscosity at 100℃,viscosity index,and oxidation induction time performance of the lubricant.The results showed that the Gaussian Copula function data expansion method improved the prediction ability of the hybrid model in the case of small samples.The SOA-GBDT hybrid model had the fastest convergence speed for the samples and the best prediction effect,with determination coefficients(R^(2))for the four indicators of lubricants reaching 0.98,0.99,0.96 and 0.96,respectively.Thus,this model can significantly reduce the model’s prediction error and has good prediction ability.

Improving Satellite-Retrieved Cloud Base Height with Ground-Based Cloud Radar Measurements

Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.

Elastic wave insulation and propagation control based on the programmable curved-beam periodic structure

Curved-beams can be used to design modular multistable metamaterials(MMMs)with reprogrammable material properties,i.e.,programmable curved-beam periodic structure(PCBPS),which is promising for controlling the elastic wave propagation.The PCBPS is theoretically equivalent to a spring-oscillator system to investigate the mechanism of bandgap,analyze the wave propagation mechanisms,and further form its geometrical and physical criteria for tuning the elastic wave propagation.With the equivalent model,we calculate the analytical solutions of the dispersion relations to demonstrate its adjustability,and investigate the wave propagation characteristics through the PCBPS.To validate the equivalent system,the finite element method(FEM)is employed.It is revealed that the bandgaps of the PCBPS can be turned on-and-off and shifted by varying its physical and geometrical characteristics.The findings are highly promising for advancing the practical application of periodic structures in wave insulation and propagation control.

The effect of salt anion in ether‐based electrolyte for electrochemical performance of sodium‐ion batteries:A case study of hard carbon

Compared with the extensively used ester‐based electrolyte,the hard carbon(HC)electrode is more compatible with the ether‐based counterpart in sodium‐ion batteries,which can lead to improved cycling stability and robust rate capability.However,the impact of salt anion on the electrochemical performance of HC electrodes has yet to be fully understood.In this study,the anionic chemistry in regulating the stability of electrolytes and the performance of sodium‐ion batteries have been systematically investigated.This work shows discrepancies in the reductive stability of the anionic group,redox kinetics,and component/structure of solid electrolyte interface(SEI)with different salts(NaBF_(4),NaPF_(6),and NaSO_(3)CF_(3))in the typical ether solvent(diglyme).Particularly,the density functional theory calculation manifests the preferred decomposition of PF_(6)−due to the reduced reductive stability of anions in the solvation structure,thus leading to the formation of NaF‐rich SEI.Further investigation on redox kinetics reveals that the NaPF_(6)/diglyme can induce the fast ionic diffusion dynamic and low charge transfer barrier for HC electrode,thus resulting in superior sodium storage performance in terms of rate capability and cycling life,which outperforms those of NaBF_(4)/diglyme and NaSO_(3)CF_(3)/diglyme.Importantly,this work offers valuable insights for optimizing the electrochemical behaviors of electrode materials by regulating the anionic group in the electrolyte.

RoBGP:A Chinese Nested Biomedical Named Entity Recognition Model Based on RoBERTa and Global Pointer

Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and categorize them into predefined entity types.This process can provide basic support for the automatic construction of knowledge bases.In contrast to general texts,biomedical texts frequently contain numerous nested entities and local dependencies among these entities,presenting significant challenges to prevailing NER models.To address these issues,we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer(RoBGP).Our model initially utilizes the RoBERTa-wwm-ext-large pretrained language model to dynamically generate word-level initial vectors.It then incorporates a Bidirectional Long Short-Term Memory network for capturing bidirectional semantic information,effectively addressing the issue of long-distance dependencies.Furthermore,the Global Pointer model is employed to comprehensively recognize all nested entities in the text.We conduct extensive experiments on the Chinese medical dataset CMeEE and the results demonstrate the superior performance of RoBGP over several baseline models.This research confirms the effectiveness of RoBGP in Chinese biomedical NER,providing reliable technical support for biomedical information extraction and knowledge base construction.

Buckling Optimization of Curved Grid Stiffeners through the Level Set Based Density Method

Stiffened structures have great potential for improvingmechanical performance,and the study of their stability is of great interest.In this paper,the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method,where the shape and cross section(including thickness and width)of the stiffeners can be optimized simultaneously.The grid stiffeners are a combination ofmany single stiffenerswhich are projected by the corresponding level set functions.The thickness and width of each stiffener are designed to be independent variables in the projection applied to each level set function.Besides,the path of each single stiffener is described by the zero iso-contour of the level set function.All the single stiffeners are combined together by using the p-norm method to obtain the stiffener grid.The proposed method is validated by several numerical examples to optimize the critical buckling load factor.

Infuences of Different Admixtures on the Drying Shrinkage Characteristics of Metakaolin-based Geopolymer Mortar

To investigate the influences of different admixtures on the drying shrinkage of polymer mortar in a metakaolin base,the experiments of VAE(vinyl acetate ethylene copolymer),APAM(anionic polyacrylamide)and CPAM(cationic polyacrylamide)on the drying shrinkage properties of geopolymer mortar were designed under normal temperature curing conditions.An SP-175 mortar shrinkage dilatometer was introduced to measure the dry shrinkage of geopolymer mortar.Meanwhile,the drying shrinkage properties of geopolymer mortar are exhibited by the parameters of water loss rate,drying shrinkage rate,drying shrinkage strain and drying shrinkage coefficient.The experimental data are further fitted to obtain the prediction model of dry shrinkage of geopolymer mortar,which can better reflect the relationship between dry shrinkage rate and time.Finally,the experimental results demonstrate that the dry shrinkage of geopolymer mortar can be significantly increased by adding 4%VAE admixture,meanwhile under the condition that the polymer film formed by VAE reaction can strengthen and toughen the mortar.2.5%APAM admixture and 1.5%CPAM admixture can enhance the dry shrinkage performance of geopolymer mortar in a certain range.

Simulation of Haloxylon Ammodendron Stand Basic Diameter Structure Based on Fuzzy Distribution Function

Based on the investigation data of 12 Haloxylon ammodendron plots in the south edge of Gurbantunggut Desert, Fuzzy distribution was introduced into the study of Haloxylon ammodendron base diameter structure fitting according to the consistency between the characteristics of Fuzzy distribution function and the distribution series of cumulative percentage of stand base diameter, and the fitting precision and effect of Fuzzy distribution function were discussed. The root mean square error RMSE and determination coefficient R2 values showed that Fuzzy-Γ1, Fuzzy-Γ2, Fuzzy-Γ3, Fuzzy-Γ4 had good fitting performance, among which Fuzzy-Γ1 had relatively high fitting precision, and its parameters were closely related to stand age and density, Fuzzy-Γ2 distribution function was the second, and Fuzzy-Γ4 distribution function had the worst fitting effect. By introducing a parameter c from the similarity of four distribution function formulas, a generalized Fuzzy distribution function Fuzzy-Γ5 is obtained. This function shows the highest fitting accuracy. Most of the values of parameter c are near 1 or 2, which shows that the diameter distribution is mainly approximate to Fuzzy-Γ1 and Fuzzy-Γ2.

Physics-Based Active Learning for Design Space Exploration and Surrogate Construction for Multiparametric Optimization

The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practices.Active learning(AL)approaches are useful in such a context since they maximize the performance of the trained model while minimizing the number of training samples.Such smart sampling methodologies iteratively sample the points that should be labeled and added to the training set based on their informativeness and pertinence.To judge the relevance of a data instance,query rules are defined.In this paper,we propose an AL methodology based on a physics-based query rule.Given some industrial objectives from the physical process where the AI model is implied in,the physics-based AL approach iteratively converges to the data instances fulfilling those objectives while sampling training points.Therefore,the trained surrogate model is accurate where the potentially interesting data instances from the industrial point of view are,while coarse everywhere else where the data instances are of no interest in the industrial context studied.

Preparation of palladium-based catalyst by plasma-assisted atomic layer deposition and its applications in CO_(2) hydrogenation reduction

Supported Pd catalyst is an important noble metal material in recent years due to its high catalytic performance in CO_(2)hydrogenation.A fluidized-bed plasma assisted atomic layer deposition(FP-ALD) process is reported to fabricate Pd nanoparticle catalyst over γ-Al_(2)O_(3)or Fe_(2)O_(3)/γ-Al_(2)O_(3)support,using palladium hexafluoroacetylacetonate as the Pd precursor and H_(2)plasma as counter-reactant.Scanning transmission electron microscopy exhibits that highdensity Pd nanoparticles are uniformly dispersed over Fe_(2)O_(3)/γ-Al_(2)O_(3)support with an average diameter of 4.4 nm.The deposited Pd-Fe_(2)O_(3)/γ-Al_(2)O_(3)shows excellent catalytic performance for CO_(2)hydrogenation in a dielectric barrier discharge reactor.Under a typical condition of H_(2)to CO_(2)ratio of 4 in the feed gas,the discharge power of 19.6 W,and gas hourly space velocity of10000 h^(-1),the conversion of CO_(2)is as high as 16.3% with CH_(3)OH and CH4selectivities of 26.5%and 3.9%,respectively.

Accountable capability improvement based on interpretable capability evaluation using belief rule base

A new approach is proposed in this study for accountable capability improvement based on interpretable capability evaluation using the belief rule base(BRB).Firstly,a capability evaluation model is constructed and optimized.Then,the key sub-capabilities are identified by quantitatively calculating the contributions made by each sub-capability to the overall capability.Finally,the overall capability is improved by optimizing the identified key sub-capabilities.The theoretical contributions of the proposed approach are as follows.(i)An interpretable capability evaluation model is constructed by employing BRB which can provide complete access to decision-makers.(ii)Key sub-capabilities are identified according to the quantitative contribution analysis results.(iii)Accountable capability improvement is carried out by only optimizing the identified key sub-capabilities.Case study results show that“Surveillance”,“Positioning”,and“Identification”are identified as key sub-capabilities with a summed contribution of 75.55%in an analytical and deducible fashion based on the interpretable capability evaluation model.As a result,the overall capability is improved by optimizing only the identified key sub-capabilities.The overall capability can be greatly improved from 59.20%to 81.80%with a minimum cost of 397.Furthermore,this paper also investigates how optimizing the BRB with more collected data would affect the evaluation results:only optimizing“Surveillance”and“Positioning”can also improve the overall capability to 81.34%with a cost of 370,which thus validates the efficiency of the proposed approach.

Are case reports valuable?Exploring their role in evidence based medicine and patient care

Case reports,often overlooked in evidence-based medicine(EBM),play a pivotal role in healthcare research.They provide unique insights into rare conditions,novel treatments,and adverse effects,serving as valuable educational tools and generating new hypothesis.Despite their limitations in generalizability,case reports contribute significantly to evidence-based practice by offering detailed clinical information and fostering critical thinking among healthcare professionals.By acknowledging their limitations and adhering to reporting guidelines,case reports can contribute significantly to medical knowledge and patient care within the evolving landscape of EBM.This editorial explores the intrinsic value of case reports in EBM and patient care.

Research progress on electronic and active site engineering of cobalt‐based electrocatalysts for oxygen evolution reaction

Electrocatalytic water splitting has been identified as a potential candidate for producing clean hydrogen energy with zero carbon emission.However,the sluggish kinetics of oxygen evolution reaction on the anode side of the watersplitting device significantly hinders its practical applications.Generally,the efficiency of oxygen evolution processes depends greatly on the availability of cost‐effective catalysts with high activity and selectivity.In recent years,extensive theoretical and experimental studies have demonstrated that cobalt(Co)‐based nanomaterials,especially low‐dimensional Co‐based nanomaterials with a huge specific surface area and abundant unsaturated active sites,have emerged as versatile electrocatalysts for oxygen evolution reactions,and thus,great progress has been made in the rational design and synthesis of Co‐based nanomaterials for electrocatalytic oxygen evolution reactions.Considering the remarkable progress in this area,in this timely review,we highlight the most recent developments in Co‐based nanomaterials relating to their dimensional control,defect regulation(conductivity),electronic structure regulation,and so forth.Furthermore,a brief conclusion about recent progress achieved in oxygen evolution on Co‐based nanomaterials,as well as an outlook on future research challenges,is given.

Layer by Layer Self-assembly Fiber-based Flexible Electrochemical Transistor

Poly(3,4-ethylenedioxyethiophene)-polystyrene sulfonic acid(PEDOT:PSS)/polyallyl dimethyl ammonium chloride modified reduced graphene oxide(PDDA-rGO)was layer by layer self-assembled on the cotton fiber.The surface morphology and electric property was investigated.The results confirmed the dense membrane of PEDOT:PSS and the lamellar structure of PDDA-rGO on the fibers.It has excellent electrical conductivity and mechanical properties.The fiber based electrochemical transistor(FECTs)prepared by the composite conductive fiber has a maximum output current of 8.7 mA,a transconductance peak of 10 mS,an on time of 1.37 s,an off time of 1.6 s and excellent switching stability.Most importantly,the devices by layer by layer self-assembly technology opens a path for the true integration of organic electronics with traditional textile technologies and materials,laying the foundation for their later widespread application.

Advancements in biomass gasification research utilizing iron-based oxygen carriers in chemical looping:A review

Biomass,recognized as renewable green coal,is pivotal for energy conservation,emission reduction,and dualcarbon objectives.Chemical looping gasification,an innovative technology,aims to enhance biomass utilization efficiency.Using metal oxides as oxygen carriers regulates the oxygen-to-fuel ratio to optimize synthesis product yields.This review examines various oxygen carriers and their roles in chemical looping biomass gasification,including natural iron ore types,industrial by-products,cerium oxide-based carriers,and core-shell structures.The catalytic,kinetic,and phase transfer properties of iron-based oxygen carriers are analyzed,and their catalytic cracking capabilities are explored.Molecular interactions are elucidated and system performance is optimized by providing insights into chemical looping reaction mechanisms and strategies to improve carrier efficiency,along with discussing advanced techniques such as density functional theory(DFT)and reactive force field(ReaxFF)molecular dynamics(MD).This paper serves as a roadmap for advancing chemical looping gasification towards sustainable energy goals.