A Novel Sensing Imaging Equipment Under Extremely Dim Light for Blast Furnace Burden Surface:Starlight High-Temperature Industrial Endoscope

Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control,optimize gas flow distribution and improve ironmaking efficiency.It has been challengeable to obtain high-quality optical burden surface images under high-temperature,high-dust,and extremelydim(less than 0.001 Lux)environment.Based on a novel endoscopic sensing detection idea,a reverse telephoto structure starlight imaging system with large field of view and large aperture is designed.Combined with a water-air dual cooling intelligent self-maintenance protection device and the imaging system,a starlight high-temperature industrial endoscope is developed to obtain clear optical burden surface images stably under the harsh environment.Based on an endoscope imaging area model,a material flow trajectory model and a gas-dust coupling distribution model,an optimal installation position and posture configuration method for the endoscope is proposed,which maximizes the effective imaging area and ensures large-area,safe and stable imaging of the device in a confined space.Industrial experiments and applications indicate that the proposed method obtains clear and reliable large-area optical burden surface images and reveals new BF conditions,providing key data support for green iron smelting.

Hybrid 2D/3D Graphitic Carbon Nitride-Based High-Temperature Position-Sensitive Detector

Ultraviolet position-sensitive detectors(PSDs)are expected to undergo harsh environments,such as high temperatures,for a wide variety of applications in military,civilian,and aerospace.However,no report on relevant PSDs operating at high temperatures can be found up to now.Herein,we design a new 2D/3D graphitic carbon nitride(g-C_(3)N_(4))/gallium nitride(GaN)hybrid heterojunction to construct the ultraviolet high-temperature-resistant PSD.The g-C_(3)N_(4)/GaN PSD exhibits a high position sensitivity of 355 mV mm^(-1),a rise/fall response time of 1.7/2.3 ms,and a nonlinearity of 0.5%at room temperature.The ultralow formation energy of-0.917 eV atom^(-1)has been obtained via the thermodynamic phase stability calculations,which endows g-C_(3)N_(4)with robust stability against heat.By merits of the strong built-in electric field of the 2D/3D hybrid heterojunction and robust thermo-stability of g-C_(3)N_(4),the g-C_(3)N_(4)/GaN PSD delivers an excellent position sensitivity and angle detection nonlinearity of 315 mV mm^(-1)and 1.4%,respectively,with high repeatability at a high temperature up to 700 K,outperforming most of the other counterparts and even commercial silicon-based devices.This work unveils the high-temperature PSD,and pioneers a new path to constructing g-C_(3)N_(4)-based harsh-environment-tolerant optoelectronic devices.

Harness High-Temperature Thermal Energy via Elastic Thermoelectric Aerogels

Despite notable progress in thermoelectric(TE)materials and devices,developing TE aerogels with high-temperature resistance,superior TE performance and excellent elasticity to enable self-powered high-temperature monitoring/warning in industrial and wearable applications remains a great challenge.Herein,a highly elastic,flame-retardant and high-temperature-resistant TE aerogel,made of poly(3,4-ethylene dioxythiophene):poly(styrenesulfonate)/single-walled carbon nanotube(PEDOT:PSS/SWCNT)composites,has been fabricated,displaying attractive compression-induced power factor enhancement.The as-fabricated sensors with the aerogel can achieve accurately pressure stimuli detection and wide temperature range monitoring.Subsequently,a flexible TE generator is assembled,consisting of 25 aerogels connected in series,capable of delivering a maximum output power of 400μW when subjected to a temperature difference of 300 K.This demonstrates its outstanding high-temperature heat harvesting capability and promising application prospects for real-time temperature monitoring on industrial high-temperature pipelines.Moreover,the designed self-powered wearable sensing glove can realize precise wide-range temperature detection,high-temperature warning and accurate recognition of human hand gestures.The aerogel-based intelligent wearable sensing system developed for firefighters demonstrates the desired self-powered and highly sensitive high-temperature fire warning capability.Benefitting from these desirable properties,the elastic and high-temperature-resistant aerogels present various promising applications including self-powered high-temperature monitoring,industrial overheat warning,waste heat energy recycling and even wearable healthcare.

Enhanced High-Temperature Energy Storage Performance of All-Organic Composite Dielectric via Constructing Fiber-Re in forced Structure

Optimizing the high-temperature energy storage characteristics of energy storage dielectrics is of great significance for the development of pulsed power devices and power control systems.Selecting a polymer with a higher glass transition temperature(T_(g))as the matrix is one of the effective ways to increase the upper limit of the polymer operating temperature.However,current high-T_(g)polymers have limitations,and it is difficult to meet the demand for high-temperature energy storage dielectrics with only one polymer.For example,polyetherimide has high-energy storage efficiency,but low breakdown strength at high temperatures.Polyimide has high corona resistance,but low high-temperature energy storage efficiency.In this work,combining the advantages of two polymer,a novel high-T_(g)polymer fiber-reinforced microstructure is designed.Polyimide is designed as extremely fine fibers distributed in the composite dielectric,which will facilitate the reduction of high-temperature conductivity loss for polyimide.At the same time,due to the high-temperature resistance and corona resistance of polyimide,the high-temperature breakdown strength of the composite dielectric is enhanced.After the polyimide content with the best high-temperature energy storage characteristics is determined,molecular semiconductors(ITIC)are blended into the polyimide fibers to further improve the high-temperature efficiency.Ultimately,excellent high-temperature energy storage properties are obtained.The 0.25 vol%ITIC-polyimide/polyetherimide composite exhibits high-energy density and high discharge efficiency at 150℃(2.9 J cm^(-3),90%)and 180℃(2.16 J cm^(-3),90%).This work provides a scalable design idea for high-performance all-organic high-temperature energy storage dielectrics.

Building Feedback-Regulation System Through Atomic Design for Highly Active SO_(2)Sensing

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction.Herein,we present an ingen-ious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO_(2)sensing.We found that the single Pt sites on the MoS_(2)surface can induce easier volatiliza-tion of adjacent S species to activate the whole inert S plane.Reversely,the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms,thus creating a combined system involving S vacancy-assisted single Pt sites(Pt-Vs)to synergistically improve the adsorption ability of SO_(2)gas molecules.Further-more,in situ Raman,ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS_(2)supports in SO_(2)gas atmosphere.Equipped with wireless-sensing modules,the final Pt1-MoS_(2)-def sensors array can further realize real-time monitoring of SO_(2)levels and cloud-data storage for plant growth.Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

Tailoring MXene Thickness and Functionalization for Enhanced Room‑Temperature Trace NO_(2) Sensing

In this study,precise control over the thickness and termination of Ti3C2TX MXene flakes is achieved to enhance their electrical properties,environmental stability,and gas-sensing performance.Utilizing a hybrid method involving high-pressure processing,stirring,and immiscible solutions,sub-100 nm MXene flake thickness is achieved within the MXene film on the Si-wafer.Functionalization control is achieved by defunctionalizing MXene at 650℃ under vacuum and H2 gas in a CVD furnace,followed by refunctionalization with iodine and bromine vaporization from a bubbler attached to the CVD.Notably,the introduction of iodine,which has a larger atomic size,lower electronegativity,reduce shielding effect,and lower hydrophilicity(contact angle:99°),profoundly affecting MXene.It improves the surface area(36.2 cm^(2) g^(-1)),oxidation stability in aqueous/ambient environments(21 days/80 days),and film conductivity(749 S m^(-1)).Additionally,it significantly enhances the gas-sensing performance,including the sensitivity(0.1119Ωppm^(-1)),response(0.2% and 23%to 50 ppb and 200 ppm NO_(2)),and response/recovery times(90/100 s).The reduced shielding effect of the–I-terminals and the metallic characteristics of MXene enhance the selectivity of I-MXene toward NO2.This approach paves the way for the development of stable and high-performance gas-sensing two-dimensional materials with promising prospects for future studies.

Preparation of single atom catalysts for high sensitive gas sensing

Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the semiconductor-based electrical gas sensor,the core is the catalysis process of target gas molecules on the sensitive materials.In this context,the SACs offer great potential for highly sensitive and selective gas sensing,however,only some of the bubbles come to the surface.To facilitate practical applications,we present a comprehensive review of the preparation strategies for SACs,with a focus on overcoming the challenges of aggregation and low loading.Extensive research efforts have been devoted to investigating the gas sensing mechanism,exploring sensitive materials,optimizing device structures,and refining signal post-processing techniques.Finally,the challenges and future perspectives on the SACs based gas sensing are presented.

TiN/Fe_(2)N/C composite with stable and broadband high-temperature microwave absorption

Facing the complex variable high-temperature environment,electromagnetic wave(EMW)absorbing materials maintaining high stability and satisfying absorbing properties is essential.This study focused on the synthesis and EMW absorbing performance evaluation of TiN/Fe_(2)N/C composite materials,which were prepared using electrostatic spinning followed by a high-temperature nitridation process.The TiN/Fe_(2)N/C fibers constructed a well-developed conductive network that generates considerable conduction loss.The heterogeneous interfaces between different components generated a significant level of interfacial polarization.Thanks to the synergistic effect of stable dielectric loss and optimized impedance matching,the TiN/Fe_(2)N/C composite materials demonstrated excellent and stable absorption performance across a wide temperature range(293-453 K).Moreover,TiN/Fe_(2)N/C-15 achieved a minimum reflection loss(RL)of−48.01 dB and an effective absorption bandwidth(EAB)of 3.64 GHz at 2.1 mm and 373 K.This work provides new insights into the development of high-efficiency and stabile EMW absorbing materials under complex variable high-temperature conditions.

Synergistic effect of Zr and Mo on precipitation and high-temperature properties of Al-Si-Cu-Mg alloys

This study focuses on finding a solution to the sharp decline in mechanical properties of Al-Si-Cu-Mg alloys due to rapid coarsening of traditional intermediate phases at high temperature.A new type of modified al oy,to be used in automobile engines at high temperatures,was prepared by adding Zr and Mo into Al-Si-Cu-Mg alloy.The synergistic effects of Zr and Mo on the microstructure evolution and high-temperature mechanical properties were studied.Results show that the addition of Zr and Mo generates a series of intermetallic phases dispersed in the alloy.They can improve the strength of the alloy by hindering dislocation movement and crack propagation.In addition,some nano-strengthened phases show coherent interfaces with the matrix and improve grain refinement.The addition of Mo greatly improves the heat resistance of the alloy.The extremely low diffusivity of Mo enables it to improve the thermal stability of the intermetallic phases,inhibit precipitation during aging,reduce the size of the precipitates,and improve the heat resistance of the alloy.

HZSM-5 zeolites undergoing the high-temperature process for boosting the bimolecular reaction in n-heptane catalytic cracking

High-temperature treatment is key to the preparation of zeolite catalysts.Herein,the effects of hightemperature treatment on the property and performance of HZSM-5 zeolites were studied in this work.X-Ray diffraction,N2physisorption,27Al magic angle spinning nuclear magnetic resonance(MAS NMR),and temperature-programmed desorption of ammonia results indicated that the hightemperature treatment at 650℃ hardly affected the inherent crystal and texture of HZSM-5zeolites but facilitated the conversion of framework Al to extra-framework Al,reducing the acid site and enhancing the acid strength.Moreover,the high-temperature treatment improved the performance of HZSM-5 zeolites in n-heptane catalytic cracking,promoting the conversion and light olefins yield while inhibiting coke formation.Based on the kinetic and mechanism analysis,the improvement of HZSM-5 performance caused by high-temperature treatment has been attributed to the formation of extra-framework Al,which enhanced the acid strength,facilitated the bimolecular reaction,and promoted the entropy change to overcome a higher energy barrier in n-heptane catalytic cracking.

A review of in-situ high-temperature characterizations for understanding the processes in metallurgical engineering

For the rational manipulation of the production quality of high-temperature metallurgical engineering,there are many challenges in understanding the processes involved because of the black box chemical/electrochemical reactors.To overcome this issue,various in-situ characterization methods have been recently developed to analyze the interactions between the composition,microstructure,and solid-liquid interface of high-temperature electrochemical electrodes and molten salts.In this review,recent progress of in-situ hightemperature characterization techniques is discussed to summarize the advances in understanding the processes in metallurgical engineering.In-situ high-temperature technologies and analytical methods mainly include synchrotron X-ray diffraction(s-XRD),laser scanning confocal microscopy,and X-ray computed microtomography(X-rayμ-CT),which are important platforms for analyzing the structure and morphology of the electrodes to reveal the complexity and variability of their interfaces.In addition,laser-induced breakdown spectroscopy,high-temperature Raman spectroscopy,and ultraviolet-visible absorption spectroscopy provide microscale characterizations of the composition and structure of molten salts.More importantly,the combination of X-rayμ-CT and s-XRD techniques enables the investigation of the chemical reaction mechanisms at the two-phase interface.Therefore,these in-situ methods are essential for analyzing the chemical/electrochemical kinetics of high-temperature reaction processes and establishing the theoretical principles for the efficient and stable operation of chemical/electrochemical metallurgical processes.

Natural Lignin:A Sustainable and Cost-Effective Electrode Material for High-Temperature Na-Ion Battery

Rechargeable sodium-ion batteries usually suffer from accelerated electrode destruction at high temperatures and high synthesis costs of electrode materials.Therefore,it is highly desirable to explore novel organic electrodes considering their cost-effectiveness and large adaptability to volume changes.Herein,natural biomass,pristine lignin,is employed as the sodium-ion battery anodes,and their sodium storage performance is investigated at room temperature and 60℃.The lignin anodes exhibit excellent high-temperature sodium-ion battery performance.This mainly results from the generation of abundant reactive sites(C=O)due to the high temperature-induced homogeneous cleavage of the C_(β)-O bond in the lignin macromolecule.This work can inspire researchers to explore other natural organic materials for large-scale applications and high-value utilization in advanced energy storage devices.

Temperature and Salinity Dual-parameter Sensing Based on Forward Brillouin Scattering in 1060-XP SMF

A novel temperature and salinity discriminative sensing method based on forward Brillouin scattering(FBS)in 1060-XP single-mode fiber(SMF)is proposed.The measured frequency shifts corresponding to different radial acoustic modes in 1060-XP SMF show different sensitivities to temperature and salinity.Based on the new phenomenon that different radial acoustic modes have different frequency shift-temperature and frequency shift-salinity coefficients,we propose a novel method for simultaneously measuring temperature and salinity by measuring the frequency shift changes of two FBS scattering peaks.In a proof-of-concept experiment,the temperature and salinity measurement errors are 0.12℃and 0.29%,respectively.The proposed method for simultaneously measuring temperature and salinity has the potential applications such as ocean surveying,food manufacturing and pharmaceutical engineering.

CrossFormer Embedding DeepLabv3+ for Remote Sensing Images Semantic Segmentation

High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presenceof occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the difficultyof segmentation. In this paper, an improved network with a cross-region self-attention mechanism for multi-scalefeatures based onDeepLabv3+is designed to address the difficulties of small object segmentation and blurred targetedge segmentation. First,we use CrossFormer as the backbone feature extraction network to achieve the interactionbetween large- and small-scale features, and establish self-attention associations between features at both large andsmall scales to capture global contextual feature information. Next, an improved atrous spatial pyramid poolingmodule is introduced to establish multi-scale feature maps with large- and small-scale feature associations, andattention vectors are added in the channel direction to enable adaptive adjustment of multi-scale channel features.The proposed networkmodel is validated using the PotsdamandVaihingen datasets. The experimental results showthat, compared with existing techniques, the network model designed in this paper can extract and fuse multiscaleinformation, more clearly extract edge information and small-scale information, and segment boundariesmore smoothly. Experimental results on public datasets demonstrate the superiority of ourmethod compared withseveral state-of-the-art networks.

On-chip quantum NOON state sensing for temperature and humidity

A maximal photon number entangled state,namely NOON state,can be adopted for sensing with a quantum enhancedprecision.In this work,we designed silicon quantum photonic chips containing two types of Mach-Zehnder interferometerswherein the two-photon NOON state,sensing element for temperature or humidity,is generated.Compared with classicallight or single photon case,two-photon NOON state sensing shows a solid enhancement in the sensing resolution andprecision.As the first demonstration of on-chip quantum photonic sensing,it reveals the advantages of photonic chips forhigh integration density,small-size,stability for multiple-parameter sensing serviceability.A higher sensing precision isexpected to beat the standard quantum limit with a higher photon number NOON state.

A Novel Fracturing Fluid with High-Temperature Resistance for Ultra-Deep Reservoirs

Ultra-deep reservoirs play an important role at present in fossil energy exploitation.Due to the related high temperature,high pressure,and high formation fracture pressure,however,methods for oil well stimulation do not produce satisfactory results when conventional fracturing fluids with a low pumping rate are used.In response to the above problem,a fracturing fluid with a density of 1.2~1.4 g/cm^(3)was developed by using Potassium formatted,hydroxypropyl guanidine gum and zirconium crosslinking agents.The fracturing fluid was tested and its ability to maintain a viscosity of 100 mPa.s over more than 60 min was verified under a shear rate of 1701/s and at a temperature of 175℃.This fluid has good sand-carrying performances,a low viscosity after breaking the rubber,and the residue content is less than 200 mg/L.Compared with ordinary reconstruction fluid,it can increase the density by 30%~40%and reduce the wellhead pressure of 8000 m level reconstruction wells.Moreover,the new fracturing fluid can significantly mitigate safety risks.

Remote sensing of quality traits in cereal and arable production systems:A review

Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multiplatform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.

Chaotic CS Encryption:An Efficient Image Encryption Algorithm Based on Chebyshev Chaotic System and Compressive Sensing

Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgorithm, called chaotic compressive sensing (CS) encryption (CCSE), which can not only improve the efficiencyof image transmission but also introduce the high security of the chaotic system. Specifically, the proposed CCSEcan fully leverage the advantages of the Chebyshev chaotic system and CS, enabling it to withstand various attacks,such as differential attacks, and exhibit robustness. First, we use a sparse trans-form to sparse the plaintext imageand then use theArnold transformto perturb the image pixels. After that,we elaborate aChebyshev Toeplitz chaoticsensing matrix for CCSE. By using this Toeplitz matrix, the perturbed image is compressed and sampled to reducethe transmission bandwidth and the amount of data. Finally, a bilateral diffusion operator and a chaotic encryptionoperator are used to perturb and expand the image pixels to change the pixel position and value of the compressedimage, and ultimately obtain an encrypted image. Experimental results show that our method can be resistant tovarious attacks, such as the statistical attack and noise attack, and can outperform its current competitors.

Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of pictures.This study presents a new approach to the encryption and compression of color images.It is predicated on 2D compressed sensing(CS)and the hyperchaotic system.First,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security.Then,the processed images are con-currently encrypted and compressed using 2D CS.Among them,chaotic sequences replace traditional random measurement matrices to increase the system’s security.Third,the processed images are re-encrypted using a combination of permutation and diffusion algorithms.In addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct images.Compared with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational complexity.Furthermore,it has better robustness.The experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.

Multidomain Correlation-Based Multidimensional CSI Tensor Generation for Device-FreeWi-Fi Sensing

Due to the fine-grained communication scenarios characterization and stability,Wi-Fi channel state information(CSI)has been increasingly applied to indoor sensing tasks recently.Although spatial variations are explicitlyreflected in CSI measurements,the representation differences caused by small contextual changes are easilysubmerged in the fluctuations of multipath effects,especially in device-free Wi-Fi sensing.Most existing datasolutions cannot fully exploit the temporal,spatial,and frequency information carried by CSI,which results ininsufficient sensing resolution for indoor scenario changes.As a result,the well-liked machine learning(ML)-based CSI sensing models still struggling with stable performance.This paper formulates a time-frequency matrixon the premise of demonstrating that the CSI has low-rank potential and then proposes a distributed factorizationalgorithm to effectively separate the stable structured information and context fluctuations in the CSI matrix.Finally,a multidimensional tensor is generated by combining the time-frequency gradients of CSI,which containsrich and fine-grained real-time contextual information.Extensive evaluations and case studies highlight thesuperiority of the proposal.