Preparation and applications of calcium ferrite as a functional material:A review

Calcium ferrite(CF)is recognized as a potential green and efficient functional material because of its advantages of magnetism,electrochemistry,catalysis,and biocompatibility in the fields of materials chemistry,environmental engineering,and biomedicine.There-fore,the obtained research results need to be systematically summarized,and new perspectives on CF and its composite materials need to be analyzed.Based on the presented studies of CF and its composite materials,the types and structures of the crystal are summarized.In addition,the current application technologies and theoretical mechanisms with various properties in different fields are elucidated.Moreover,the various preparation methods of CF and its composite materials are elaborated in detail.Most importantly,the advantages and disadvantages of the synthesis methods of CF and its composite materials are discussed,and the existing problems and emerging challenges in practical production are identified.Furthermore,the key future research directions of CF and its composite materials have been prospected from the potential application technologies to provide references for its synthesis and efficient utilization.

Effects of friction stir processing and nano-hydroxyapatite on the microstructure,hardness,degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications

Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural bones.However,the rapid degradation of magnesium alloys in biological media hinders successful implantation.Refinement of microstructure,as well as reinforcement particles can significantly improve the degradation rate.In this work,multi-pass friction stir processing(FSP)was proposed to synthesize WE43/nano-hydroxyapatite(n HA)surface composite,the microstructure,reinforced particle distribution,micro-hardness,corrosion behavior and in-vitro bioactivity were studied.The subsequent FSP passes of WE43 alloy and WE43/n HA composite refined the grain size which was reduced by 94.29%and 95.92%(2.63 and 1.88μm,respectively)compared to base metal after three passes.This resulted in increasing the microhardness by 120%(90.86 HV0.1)and 135%(105.59 HV0.1)for the WE43 and WE43-n HA,respectively.It is found that increasing FSP passes improved the uniform distribution of n HA particles within the composite matrix which led to improved corrosion resistance and less degradation rate.The corrosion rate of the FSPed WE43/n HA composite after three passes was reduced by 38.2%(4.13 mm/year)and the degradation rate was reduced by 69.7%(2.87 mm/y).This is attributed to secondary phase(Mg24Y5and Mg41Nd5)particle fragmentation and redistribution,as well as a homogeneous distribution of n HA.Additionally,the growing Ca-P and Mg(OH)2layer formed on the surface represented a protective layer that reduced the degradation rate.The wettability test revealed a relatively hydrophilic surface with water contact angle of 49.1±2.2°compared to 71.2±2.1°for base metal.Also,biomineralization test showed that apatite layer grew after immersion 7d in simulated body fluid with atomic ratio of Ca/P 1.60 approaching the stoichiometric ratio(1.67)indicating superior bioactivity of FSPed WE43/n HA composite after three passes.These results raise that the grain refinement by FSP and introduction of n HA particles significantly improved the degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications.

Recent progress on stability and applications of flexible perovskite photodetectors

Flexible photodetectors have garnered significant attention by virtue of their potential applications in environmental monitoring,wearable healthcare,imaging sensing,and portable optical communications.Perovskites stand out as particularly promising materials for photodetectors,offering exceptional optoelectronic properties,tunable band gaps,low-temperature solution processing,and notable mechanical flexibility.In this review,we explore the latest progress in flexible perovskite photodetectors,emphasizing the strategies developed for photoactive materials and device structures to enhance optoelectronic performance and stability.Additionally,we discuss typical applications of these devices and offer insights into future directions and potential applications.

Advancements in implantable temperature sensors:Materials,mechanisms,and biological applications

Implantable temperature sensors are revolutionizing physiological monitoring and playing a crucial role in diagnostics,therapeutics,and life sciences research.This review classifies the materials used in these sensors into three categories:metal-based,inorganic semiconductor,and organic semiconductor materials.Metal-based materials are widely used in medical and industrial applications due to their linearity,stability,and reliability.Inorganic semiconductors provide rapid response times and high miniaturization potential,making them promising for biomedical and environmental monitoring.Organic semiconductors offer high sensitivity and ease of processing,enabling the development of flexible and stretchable sensors.This review analyzes recent studies for each material type,covering design principles,performance characteristics,and applications,highlighting key advantages and challenges regarding miniaturization,sensitivity,response time,and biocompatibility.Furthermore,critical performance parameters of implantable temperature sensors based on different material types are summarized,providing valuable references for future sensor design and optimization.The future development of implantable temperature sensors is discussed,focusing on improving biocompatibility,long-term stability,and multifunctional integration.These advancements are expected to expand the application potential of implantable sensors in telemedicine and dynamic physiological monitoring.

Literature classification and its applications in condensed matter physics and materials science by natural language processing

The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.

MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

Potential industrial applications of photo/electrocatalysis: Recent progress and future challenges

Nowadays,the rapid development of the social economy inevitably leads to global energy and environmental crisis.For this reason,more and more scholars focus on the development of photocatalysis and/or electrocatalysis technology for the advantage in the sustainable production of high-value-added products,and the high efficiency in pollutants remediation.Although there is plenty of outstanding research has been put forward continuously,most of them focuses on catalysis performance and reaction mechanisms in laboratory conditions.Realizing industrial application of photo/electrocatalytic processes is still a challenge that needs to be overcome by social demand.In this regard,this review comprehensively summarized several explorations in thefield of photo/electrocatalytic reduction towards potential industrial applications in recent years.Special attention is paid to the successful attempts and the current status of photo/electrocatalytic water splitting,carbon dioxide conversion,resource utilization from waste,etc.,by using advanced reactors.The key problems and challenges of photo/electrocatalysis in future industrial practice are also discussed,and the possible development directions are also pointed out from the industry view.

A Review of Contact Electrification at Diversified Interfaces and Related Applications on Triboelectric Nanogenerator

The triboelectric nanogenerator(TENG)can effectively collect energy based on contact electrification(CE)at diverse interfaces,including solid–solid,liquid–solid,liquid–liquid,gas–solid,and gas–liquid.This enables energy harvesting from sources such as water,wind,and sound.In this review,we provide an overview of the coexistence of electron and ion transfer in the CE process.We elucidate the diverse dominant mechanisms observed at different interfaces and emphasize the interconnectedness and complementary nature of interface studies.The review also offers a comprehensive summary of the factors influencing charge transfer and the advancements in interfacial modification techniques.Additionally,we highlight the wide range of applications stemming from the distinctive characteristics of charge transfer at various interfaces.Finally,this review elucidates the future opportunities and challenges that interface CE may encounter.We anticipate that this review can offer valuable insights for future research on interface CE and facilitate the continued development and industrialization of TENG.

Hydrodynamic and morphological processes in Yangtze Estuary:State-of-the-art research and its applications by Hohai University

This paper presents a review of the state-of-the-art research and its applications developed at Hohai University relating to the hydrodynamic and morphological processes in the Yangtze Estuary. Longitudinal, lateral, and horizontal flow circulations have been revealed based on the measurements with acoustic Doppler current profilers （ADCP）. The hydrodynamic mechanism at diversion points as well as the changing patterns of flow and sediment flux in the Yangtze Estuary has been investigated through long-term data analysis. A field survey has been carried out to detect the saltwater intrusion from the North Branch to South Branch. Different numerical models of flow motion, sediment transport, and saltwater intrusion have been developed to simulate the complicated processes and to evaluate the effects of engineering projects. The morphological processes of wetlands over a time scale of decades have been analyzed with an established database. Ideas for further research on the bio-geomorphological model system and long-term evolution mechanisms are put forward.

Big Data Application Simulation Platform Design for Onboard Distributed Processing of LEO Mega-Constellation Networks

Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.

Research and development of gas induced semi-solid process for industrial applications

Several rheocasting processes are developed or applied worldwide in the metal forming industry.One of the new rheocasting processes is the gas induced semi-solid(GISS) process.The GISS process utilizes the principle of rapid heat extraction and vigorous local extraction using the injection of fine gas bubbles through a graphite diffuser.Several forming processes such as die casting,squeeze casting,gravity casting,and rheo-extrusion of the semi-solid slurries prepared by the GISS process have also been conducted.The GISS process is capable of processing various alloys including cast aluminum alloys,die casting aluminum alloys,wrought aluminum alloys,and zinc alloys.The GISS process is currently developed to be used commercially in the industry with the focus on forming semi-solid slurries containing low fractions solid(< 0.25) into parts.The research and development activities of the GISS process were discussed and the status of the industrial developments of this process was reported.

Analysis of application range of simplified models for field to thermo-field to thermionic emission processes from the cathode

Electron emission plays a dominant role in plasma-cathode interactions and is a key factor in many plasma phenomena and industrial applications.It is necessary to illustrate the various electron emission mechanisms and the corresponding applicable description models to evaluate their impacts on discharge properties.In this study,detailed expressions of the simplified formulas valid for field emission to thermo-field emission to thermionic emission typically used in the numerical simulation are proposed,and the corresponding application ranges are determined in the framework of the Murphy-Good theory,which is commonly regarded as the general model and to be accurate in the full range of conditions of the validity of the theory.Dimensionless parameterization was used to evaluate the emission current density of the Murphy-Good formula,and a deviation factor was defined to obtain the application ranges for different work functions(2.5‒5 eV),cathode temperatures(300‒6000 K),and emitted electric fields(10^(5) to 10^(10) V·m^(-1)).The deviation factor was shown to be a nonmonotonic function of the three parameters.A comparative study of particle number densities in atmospheric gas discharge with a tungsten cathode was performed based on the one-dimensional implicit particle-in-cell(PIC)with the Monte Carlo collision(MCC)method according to the aforementioned application ranges.It was found that small differences in emission current density can lead to variations in the distributions of particle number density due to changes in the collisional environment.This study provides a theoretical basis for selecting emission models for subsequent numerical simulations.

Review on Sol-Gel Derived Coatings: Process, Techniques and Optical Applications

Sol-gel process is one of the simplest techniques to manufacture thin films. The quality of the prepared films depends on the parameters of the sol-gel process and the used technique for deposition. A great variety of the sol-gel derived films have been prepared for different applications. We present a review on the sol-gel derived coatings. The description of the process is introduced in details. Different sol-gel deposition techniques are mentioned. The optical applications of the sol-gel derived coatings are reviewed.

Synthesis and modification strategies of g-C_(3)N_(4) nanosheets for photocatalytic applications

Graphitic carbon nitride nanosheets(CNNs)become the most promising member in the carbon nitride family benefitted from their two-dimensional structural features.Recently,great endeavors have been made in the synthesis and modification of CNNs to improve their photocatalytic properties,and many exciting progresses have been gained.In order to elucidate the fundamentals of CNNs based catalysts and provide the insights into rational design of photocatalysis system,we describe recent progress made in CNNs preparation strategies and their applications in this review.Firstly,the physicochemical properties of CNNs are briefly introduced.Secondly,the synthesis approaches of CNNs are reviewed,including top-down stripping strategies(thermal,gas,liquid,and composite stripping)and bottom-up precursor molecules design strategies(solvothermal,template,and supramolecular self-assembly method).Subsequently,the modification strategies based on CNNs in recent years are discussed,including crystal structure design,doping,surface functionalization,constructing 2D heterojunction,and anchoring single-atom.Then the multifunctional applications of g-C_(3)N_(4) nanosheet based materials in photocatalysis including H_(2) evolution,O_(2) evolution,overall water splitting,H_(2)O_(2) production,CO_(2) reduction,N_(2) fixation,pollutant removal,organic synthesis,and sensing are highlighted.Finally,the opportunities and challenges for the development of high-performance CNNs photocatalytic systems are also prospected.

Tailoring metallic surface properties induced by laser surface processing for industrial applications

As a simple, reproducible, and pollution-free technique with the potential of integration and automation, laser processing has attracted increasing attention. Laser processing, which includes laser polishing, laser cleaning,and fabrication of laser-induced micro-/nano-structures, has been demonstrated to yield smooth, clean, functional surfaces and effective joining. Laser polishing is an advanced, highly efficient, and ecofriendly polishing technology. This study demonstrated the laser polishing of a selective laser-melted Inconel 718(IN718) superalloy and a titanium alloy sample. The surface roughnesses Raand Rzof the IN718 superalloy were respectively reduced from 8 and 33 μm to 0.2 and 0.8 μm, and the Raof the titanium alloy was reduced from 9.8 μm to 0.2 μm.Moreover, the wear resistance and corrosion resistance of the IN718 were apparently improved. As another surface-related processing method, laser cleaning was used to clean terminal blocks. Almost all the contaminants were removed, as verified by the absence of their chemical compositions and the decreased surface roughness. In addition, a superhydrophobic surface with a contact angle of over 160° and sliding angle of b8° on stainless steel was obtained by laser texturing treatment. These results demonstrate the high potential of laser processing in the scientific, technological, and industrial fields.

State of the art in applications of machine learning in steelmaking process modeling

With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data.The application of machine learning in the steelmaking process has become a research hotspot in recent years.This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other aspects.The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,respectively.Collected data in the steelmaking plants are frequently faulty.Thus,data processing,especially data cleaning,is crucially important to the performance of machine learning models.The detection of variable importance can be used to optimize the process parameters and guide production.Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction.The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking.Machine learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization processes.Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.

Progress of Solidification Researches and the Applications in Materials Processing

The research achievements of solidification theories and technologies in the last decades are reviewed with the stresses on some new development in the recent years. Some new interesting areas emerged in the last years are also pointed out.

Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process

State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modeled dynamics,parameter sensitivity,etc.This paper discusses the principles and characteristics of three different approaches,extended Kalman filters,strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance,an improved Kalman filter,unscented transformation based robust Kalman filter,is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.

Heating of nanoparticles and their environment by laser radiation and applications

This review considers the fundamental dynamic processes involved in the laser heating of metal nanoparticles and their subsequent cooling.Of particular interest are the absorption of laser energy by nanoparticles,the heating of a single nanoparticle or an ensemble thereof,and the dissipation of the energy of nanoparticles due to heat exchange with the environment.The goal is to consider the dependences and values of the temperatures of the nanoparticles and the environment,their time scales,and other parameters that describe these processes.Experimental results and analytical studies on the heating of single metal nanoparticles by laser pulses are discussed,including the laser thresholds for initiating subsequent photothermal processes,how temperature influences the optical properties,and the heating of gold nanoparticles by laser pulses.Experimental studies of the heating of an ensemble of nanoparticles and the results of an analytical study of the heating of an ensemble of nanoparticles and the environment by laser radiation are considered.Nanothermometry methods for nanoparticles under laser heating are considered,including changes in the refractive indices of metals and spectral thermometry of optical scattering of nanoparticles,Raman spectroscopy,the thermal distortion of the refractive index of an environment heated by a nanoparticle,and thermochemical phase transitions in lipid bilayers surrounding a heated nanoparticle.Understanding the sequence of events after radiation absorption and their time scales underlies many applications of nanoparticles.The applicationfields for the laser heating of nanoparticles are reviewed,including thermochemical reactions and selective nanophotothermolysis initiated in the environment by laser-heated nanoparticles,thermal radiation emission by nanoparticles and laser-induced incandescence,electron and ion emission of heated nanoparticles,and optothermal chemical catalysis.Applications of the laser heating of nanoparticles in laser nanomedicine are of particular interest.Significant emphasis is given to the proposed analytical approaches to modeling and calculating the heating processes under the action of a laser pulse on metal nanoparticles,taking into account the temperature dependences of the parameters.The proposed models can be used to estimate the parameters of lasers and nanoparticles in the various applicationfields for the laser heating of nanoparticles.

Research and Applications of Semi-solid Processing

It has been more than ten years since the semi-solid processing (SSP) technique was put into commercial applications in the world. A lot of work on semi-solid metals (SSM) including their preparation, reheating and semi-solid forming has been done in China. In order to produce the high quality die-casting, a novel innovation that modifies the present machines based on the SSP technique was proposed. Semi-solid die-casting on modified casting machines can manufacture parts with more excellent quality than those produced by squeeze casting. It was found that the defects such as 'elephant foot' and 'periphery liquid metal loss' during reheating could be avoided through controlling the non-dendritic structure of billets and optimizing the reheating process. The processing parameters and mold designs of semi-solid die-casting are fairly different from those of liquid die-casting.