Self-heating tendency evaluation of sulfide ores based on nonlinear multi-parameters fusion

In order to reveal the nonlinear dynamics characteristics of unsteady self-heating process of sulfide ores, nine different kinds of sulfide ore samples from a pyrite mine in China were taken as experimental materials and their self-heating characteristics were measured in laboratory. Furthermore, the measured temperature was studied by integrating wavelet transform, nonlinear characteristic parameters extraction and fuzzy comprehensive evaluation. The results indicate that only the ore samples 1, 2, 6 and 9 have obvious self-heating phenomenon, and their self-heating initiative temperatures are 220 ℃, 239 ℃, 220 ℃ and 220 ℃, respectively, which means that they are difficult to produce self-heating under normal mining conditions. The correlation dimension of self-heating process is fraction and the maximum Lyapunov exponent is positive, which means that it is feasible to study the self-heating process based on chaotic dynamics theory. The nonlinearities of self-heating process of these four samples （ore samples 1, 2, 6 and 9） are 0.8227, 0.7521, 0.9401 and 0.8827 respectively and the order of the samples according to these results is： sample 6, sample 9, sample 1, sample 2, which is consistent with the measured results of self-heating characteristics. Therefore, the nonlinearity method can be used to evaluate the self-heating tendency of sulfide ores, and it is an effective verification of the reliability of measured results.

Dendritic spine degeneration:a primary mechanism in the aging process

Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).

Analytical workload dependence of self-heating effect for SOI MOSFETs considering two-stage heating process

Dynamic self-heating effect(SHE)of silicon-on-insulator(SOI)MOSFET is comprehensively evaluated by ultrafast pulsed I-V measurement in this work.It is found for the first time that the SHE complete heating response and cooling response of SOI MOSFETs are conjugated,with two-stage curves shown.We establish the effective thermal transient response model with stage superposition corresponding to the heating process.The systematic study of SHE dependence on workload shows that frequency and duty cycle have more significant effect on SHE in first-stage heating process than in the second stage.In the first-stage heating process,the peak lattice temperature and current oscillation amplitude decrease by more than 25 K and 4%with frequency increasing to 10 MHz,and when duty cycle is reduced to 25%,the peak lattice temperature drops to 306 K and current oscillation amplitude decreases to 0.77%.Finally,the investigation of two-stage(heating and cooling)process provides a guideline for the unified optimization of dynamic SHE in terms of workload.As the operating frequency is raised to GHz,the peak temperature depends on duty cycle,and self-heating oscillation is completely suppressed.

Prediction and optimization of flue pressure in sintering process based on SHAP

Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.

An Unprecedented Efficiency with Approaching 21%Enabled by Additive‑Assisted Layer‑by‑Layer Processing in Organic Solar Cells

Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.

Processing,microstructure,and mechanical properties of wire arc additively-manufactured AZ91 magnesium alloy using cold arc process

Thin walls of an AZ91 magnesium alloy with fine equiaxed grains were fabricated via cold arc-based wire arc additive manufacturing(CA-WAAM),and the droplet transfer behaviours,microstructures,and mechanical properties were investigated.The results showed that the cold arc process reduced splashing at the moment of liquid bridge breakage and effectively shortened the droplet transfer period.The microstructures of the deposited samples exhibited layered characteristics with alternating distributions of coarse and fine grains.During layer-by-layer deposition,the β-phase precipitated and grew preferentially along grain boundaries,while the fineη-Al_(8)Mn_(5)phase was dispersed in the α-Mg matrix.The mechanical properties of the CA-WAAM deposited sample showed isotropic characteristics.The ultimate tensile strength and elongation in the building direction(BD)were 282.7 MPa and 14.2%,respectively.The microhardness values of the deposited parts were relatively uniform,with an average value of HV 69.6.

Influence of material characteristics on the failure mode and process of landslide dam

Landslide dams,as frequent natural hazards,pose significant risks to human lives,property,and ecological environments.The grading characteristics and density of dam materials play a crucial role in determining the stability of landslide dams and the potential for dam breaches.To explore the failure mechanisms and evolutionary processes of landslide dams with varying soil properties,this study conducted a series of flume experiments,considering different grain compositions and material densities.The results demonstrated that grading characteristics significantly influence landslide dam stability,affecting failure patterns,breach processes,and final breach morphologies.Fine-graded materials exhibited a sequence of surface erosion,head-cut erosion,and subsequent surface erosion during the breach process,while well-graded materials typically experienced head-cut erosion followed by surface erosion.In coarse-graded dams,the high permeability of coarse particles allowed the dam to remain stable,as inflows matched outflows.The dam breach model experiments also showed that increasing material density effectively delayed the breach and reduced peak breach flow discharge.Furthermore,higher fine particle content led to a reduction in the residual dam height and the base slope of the final breach profile,although the relationship between peak breach discharge and the content of fine and coarse particles was nonlinear.To better understand breach morphology evolution under different soil characteristics and hydraulic conditions,three key points were identified—erosion point,control point,and scouring point.This study,by examining the evolution of failure patterns,breach processes,and breach flow discharges under various grading and density conditions,offers valuable insights into the mechanisms behind landslide dam failures.

New digital drilling process monitoring: Instrumentation, validation and calibration

This study aims to enhance the digital drilling process monitoring(DPM)or monitoring while drilling(MWD)technique,which is a widely recognized method in geological exploration for evaluating rock mass quality.First,robust displacement and torque measurement facilities for rotary-core drilling are discussed.The conventional cable encoder for displacement measurement is replaced with a magnetostrictive displacement sensor,which is more reliable in harsh field drilling environments.This enables the measurement of the bit position with an accuracy of<1 mm.Most importantly,this new instrument is proven to be successful in improving the detection of structural discontinuities with thicknesses>1 mm.In addition,by measuring the electric current of the driving motor,the torque applied to the bit is conveniently and accurately converted.These innovations ensure high-quality data collection for DPM practices.Second,two indices derived from DPM are proposed to quantitatively describe rock mass quality.The specific energy index(SEI)and specific penetration index(SPI)are based on the principles of energy conservation and Mohr-Coulomb failure criterion,respectively.Extensive field tests conducted in a dam grouting area confirm a linear relationship between the thrust force and penetration per rotation,and between the torque and penetration per rotation.The correlation ratios of the related regressions are typically>0.9.These two indices allow for the quantitative interpretation of DPM data into rock mechanics characteristics,such as uniaxial compressive strength,rock quality designation(RQD),and rock mass permeability,eliminating the need for subjective judgment normally involved in the currently used rock mass quality rating approaches.

Process Simulate软件在自动化生产线安装调试课程中的应用

针对自动化生产线安装调试课程的实践教学难题提出了使用仿真软件进行虚拟装调的方案。介绍了如何使用Process Simulate软件对自动化生产线进行虚拟装调。实践证明,使用Process Simulate软件能够有效提高自动化生产线安装调试课程的实践教学效果。

基于Arduino与Processing的心率检测计设计研究

随着社会经济的高速发展,人们的物质生活也有了极大的提高,但同时也伴随着各种疾病的到来,身体健康已经成为人们普遍关注的焦点,因此,心率检测仪、血压计、血糖仪等各种家用医疗监测仪器已经逐渐融入日常生活。心脏病是人们难以预防的突发致命疾病之一,本文介绍的是一款基于Arduino【是基于易用硬件和软件的原型开源平台,包由可编程的电路板(简称微控制器),以及集成开发环境(称为Arduino IDE)的现成软件组成】Processing(开源编程语言,包括编辑器、编译器、展示器)的简易心率检测计系统,其功能实用、操作简单,可以测量心率,当超出正常心率范围时及时预警,是一款便携的实时心率测试仪。

Numerical Simulation of the Self-Heating Effect Induced by Electron Beam Plasma in Atmosphere

For exploiting advantages of electron beam air plasma in some unusual applications, a Monte Carlo （MC） model coupled with heat transfer model is established to simulate the characteristics of electron beam air plasma by considering the self-heating effect. Based on the model, the electron beam induced temperature field and the related plasma properties are investigated. The results indicate that a nonuniform temperature field is formed in the electron beam plasma region and the average temperature is of the order of 600 K. Moreover, much larger volume pear-shaped electron beam plasma is produced in hot state rather than in cold state. The beam ranges can, with beam energies of 75 keV and 80 keV, exceed 1.0 m and 1.2 m in air at pressure of 100 torr, respectively. Finally, a well verified formula is obtained for calculating the range of high energy electron beam in atmosphere.

A study of self-heating characteristics of a pyrrhotite-rich sulphide ore stockpile

Original surface chemistry of sulphidesis altered upon contact with air, leading to ''oxidation'', which is accompanied by evolution of heat. The current study reports results of an investigation on extent of exothermicity of an experimental nickel-copper sulphide stockpile that was formed at a mining site in Sudbury, Canada. The ore contained pentlandite and chalcopyrite that are accompanied by a large quantity of pyrrhotite. The self-heating characteristics were recorded by temperature sensors placed inside the stockpile. Ambient conditions such as temperature, humidity, and wind velocity were simultaneously recorded. The inner temperature of the stockpile indicated significant fluctuations due to rapid changes, particularly in the outside temperature. The minimum and maximum temperatures recorded in the outside and inside were 5 and 10.5, 44.3 and 32 ℃, respectively. The self-heating capacity of the sulphide ore stockpile observed represents a mild case compared to that experienced by coals. Possible reasons are discussed.

Investigation on step overcharge to self-heating behavior and mechanism analysis of lithium ion batteries

To obtain intrinsic overcharge boundary and investigate overcharge mechanism,here we propose an innovative method,the step overcharge test,to reduce the thermal crossover and distinguish the overcharge thermal behavior,including 5%state of charge(SOC)with small current overcharge and resting until the temperature equilibrium under adiabatic conditions.The intrinsic thermal response and the self-excitation behaviour are analysed through temperature and voltage changes during the step overcharge period.Experimental results show that the deintercalated state of the cathode is highly correlated to self-heating parasitic reactions.Before reaching the upper limit of Negative/Positive(N/P)ratio,the temperature changes little,the heat generation is significantly induced by the reversible heat(endothermic)and ohmic heat,which could balance each other.Following that the lithium metal is gradually deposited on the surface of the anode and reacts with electrolyte upon overcharge,inducing selfheating side reaction.However,this spontaneous thermal reaction could be“self-extinguished”.When the lithium in cathode is completely deintercalated,the boundary point of overcharge is about 4.7 V(~148%SOC,>40℃),and from this point,the self-heating behaviour could be continuously triggered until thermal runaway(TR)without additional overcharge.The whole static and spontaneous process lasts for 115 h and the side reaction heat is beyond 320,000 J.The continuous self-excitation behavior inside the battery is attributed to the interaction between the highly oxidized cathode and the solvent,which leads to the dissolution of metal ions.The dissolved metal ions destroy the SEI(solid electrolyte interphase)film on the surface of the deposited Li of anode,which induces the thermal reaction between lithium metal and the solvent.The interaction between cathode,the deposited Li of anode,and solvent promotes the temperature of the battery to rise slowly.When the temperature of the battery reaches more than 60℃,the reaction between lithium metal and solvent is accelerated.After the temperature rises rapidly to the melting point of the separator,it triggers the thermal runaway of the battery due to the short circuit of the battery.

A large-area multi-fingerβ-Ga_(2)O_(3) MOSFET and its self-heating effect

The self-heating effect severely limits device performance and reliability.Although some studies have revealed the heat distribution ofβ-Ga_(2)O_(3) MOSFETs under biases,those devices all have small areas and have difficulty reflecting practical con-ditions.This work demonstrated a multi-fingerβ-Ga_(2)O_(3) MOSFET with a maximum drain current of 0.5 A.Electrical characteris-tics were measured,and the heat dissipation of the device was investigated through infrared images.The relationship between device temperature and time/bias is analyzed.

CFD modelling of Iongwall goaf gas flow to improve gas capture and prevent goaf self-heating

CFD models have been developed to investigate the Iongwall goaf gas flow patternsunder different mining and geological control conditions.The Iongwall goaf wastreated as porous regions and gas flow was modelled as a momentum sink added to themomentum equation.Gas desorption from the caved goaf and destressed coal seamswithin the mining disturbed area was modelled as additional mass sources in the continuityequation.These CFD models were developed according to specific Iongwall layoutsand calibrated against field monitoring data.Two case studies were presented demonstratingthe application of CFD modelling of goaf gas flow characteristics for improved goafgas capture and the reduction of oxygen ingress into the goaf areas for self-heating prevention.Results from the case studies indicate that the optimum goaf drainage strategywould be a combination of shallow (near the face) and deep holes to improve the overalldrainage efficiency and gas purity.For gassy Iongwall faces retreating against the seam dip,it is recommended to conduct cross-measure roof hole drainage targeting the fracturedzones overlying the return corner,rather than high capacity surface goaf drainage deep inthe goaf.

Design and Control of Self-Heat Recuperative Distillation Process for Separation of Close-Boiling Mixtures: n-Butanol and iso-Butanol

In order to explore the advantages of self-heat recuperative distillation(SHRD) process, the design and control of the SHRD process was studied for the separation of n-butanol and iso-butanol mixtures. The economic superiority of SHRD process is presented when a comparison on the total annual cost(TAC) of the conventional distillation process, the vapor recompression distillation process and the SHRD process was made. For the SHRD process, 37.74% and 11.35% savings of TAC can be achieved as compared to the conventional distillation process and vapor recompression distillation process, respectively. The dynamic characteristics of this promising SHRD sequence had been studied, and the dynamic responses demonstrated that 10% changes in both feed flow rate and feed composition can be well handled by the control strategy with dual-temperature control. It is proven that the SHRD system not only can provide economical savings but also can operate normally with good controllability.

Electrothermal simulation of the self-heating effects in 4H-SiC MESFETs

A thermal model of 4H-SiC MESFET is developed based on the temperature dependences of material parameters and three-region I - V model. The static current characteristics of 4H-SiC MESFET have been obtained with the consideration of the self-heating effect on related parameters including electron mobility, saturation velocity and thermal conductivity. High voltage performances are analysed using equivalent thermal conductivity model. Using the physicalbased simulations, we studied the dependence of self-heating temperature on the thickness and doping of substrate. The obtained results can be used for optimization of the thermal design of the SiC-based high-power field effect transistors.

Investigation and active suppression of self-heating induced degradation in amorphous InGaZnO thin film transistors

Self-heating effect in amorphous InGaZnO thin-film transistors remains a critical issue that degrades device performance and stability, hindering their wider applications. In this work, pulsed current–voltage analysis has been applied to explore the physics origin of self-heating induced degradation, where Joule heat is shortly accumulated by drain current and dissipated in repeated time cycles as a function of gate bias. Enhanced positive threshold voltage shift is observed at reduced heat dissipation time, higher drain current, and increased gate width. A physical picture of Joule heating assisted charge trapping process has been proposed and then verified with pulsed negative gate bias stressing scheme, which could evidently counteract the self-heating effect through the electric-field assisted detrapping process. As a result, this pulsed gate bias scheme with negative quiescent voltage could be used as a possible way to actively suppress self-heating related device degradation.

Influence of self-heating on the millimeter-wave and terahertz performance of MBE grown silicon IMPATT diodes

The influence of self-heating on the millimeter-wave(mm-wave)and terahertz(THz)performance of double-drift region(DDR)impact avalanche transit time(IMPATT)sources based on silicon(Si)has been investigated in this paper.The dependences of static and large-signal parameters on junction temperature are estimated using a non-sinusoidal voltage excited(NSVE)large-signal simulation technique developed by the authors,which is based on the quantum-corrected drift-diffusion(QCDD)model.Linear variations of static parameters and non-linear variations of large-signal parameters with temperature have been observed.Analytical expressions representing the temperature dependences of static and large-signal parameters of the diodes are developed using linear and 2nd degree polynomial curve fitting techniques,which will be highly useful for optimizing the thermal design of the oscillators.Finally,the simulated results are found to be in close agreement with the experimentally measured data.

Machine Learning-Based Predictions on the Self-Heating Characteristics of Nanocomposites with Hybrid Fillers

A machine learning-based prediction of the self-heating characteristics and the negative temperature coefficient(NTC)effect detection of nanocomposites incorporating carbon nanotube(CNT)and carbon fiber(CF)is proposed.The CNT content was fixed at 4.0 wt.%,and CFs having three different lengths(0.1,3 and 6 mm)at dosage of 1.0 wt.%were added to fabricate the specimens.The self-heating properties of the specimens were evaluated via self-heating tests.Based on the experiment results,two types of artificial neural network(ANN)models were constructed to predict the surface temperature and electrical resistance,and to detect a severe NTC effect.The present predictions were compared with experimental values to verify the applicability of the proposed ANN models.The ANN model for data prediction was able to predict the surface temperature and electrical resistance closely,with corresponding R-squared value of 0.91 and 0.97,respectively.The ANN model for data detection could detect the severe NTC effect occurred in the nanocomposites under the self-heating condition,as evidenced by the accuracy and sensitivity values exceeding 0.7 in all criteria.