Early warning method for thermal runaway of lithium-ion batteries under thermal abuse condition based on online electrochemical impedance monitoring

Early warning of thermal runaway(TR)of lithium-ion batteries(LIBs)is a significant challenge in current application scenarios.Timely and effective TR early warning technology is urgently required considering the current fire safety situation of LIBs.In this work,we report an early warning method of TR with online electrochemical impedance spectroscopy(EIS)monitoring,which overcomes the shortcomings of warning methods based on traditional signals such as temperature,gas,and pressure with obvious delay and high cost.With in-situ data acquisition through accelerating rate calorimeter(ARC)-EIS test,the crucial features of TR were extracted using the RReliefF algorithm.TR mechanisms corresponding to the features at specific frequencies were analyzed.Finally,a three-level warning strategy for single battery,series module,and parallel module was formulated,which can successfully send out an early warning signal ahead of the self-heating temperature of battery under thermal abuse condition.The technology can provide a reliable basis for the timely intervention of battery thermal management and fire protection systems and is expected to be applied to electric vehicles and energy storage devices to realize early warning and improve battery safety.

Online measurement of alkalinity in anaerobic co-digestion using linear regression method

Alkalinity is a reliable indicator of process stability in anaerobic digestion system.Total alkalinity(TA)and partial alkalinity(PA)are usually monitored offline as indicators for the status of anaerobic digestion process.In order to online monitor TA and PA,the linear regression method was used as estimator to predict alkalinity via software sensor method.Parameters,namely,pH,oxidation and reduction potential(ORP),and electrical conductivity(EC),were used as input variables.EC was the most significant parameter with TA and PA.Multiple linear regression(MLR)models and simple linear regression models with EC were constructed to predict TA and PA in anaerobic co-digestion system.On the basis of the evaluation of prediction accuracy,the applications of linear regression models were better for monitoring PA than TA.MLR models provided higher accuracy for alkalinity prediction than simple linear regression models.The two MLR models based on single-phase anaerobic digestion system were also feasible to predict TA in anaerobic co-digestion systems.However,the accuracy of these models should be improved by calibrating for broad applications of linear regression method in online alkalinity measurement.

Determination of gross α and β activities in Zouma River based on online HPGe gamma measurement system

This paper describes a low-cost and fast method to evaluate gross α and β^(-) radioactivities in natural water based on an online high-purity germanium detector gamma measurement system.The major gamma activities in natural water are provided by natural and artificial radionuclides such as ^(40) K,^(137)Cs,and radionuclides belonging to ^(238)U and ^(232)Th series.The main a emitters related to gamma emissions in natural water are ^(224)Ra(240.98 keV)and ^(226)Ra(186.21 keV),and the β^(-) emitters are ^(40) K(1460.85 keV),^(214)Bi(609.31 keV),^(208)Tl(583.19 keV),and ^(214)Pb(351.93 keV).The formula for gross α and β^(-) activity concentration is based on these radionuclides,and the short half-life decay products are considered in the calculation.The detection efficiency of the device across energy region(0–3 MeV)is obtained through Monte Carlo simulation,and a calibration experiment is conducted to verify the simulation results.Gamma radioactivity is measured continuously for 114 d in Pixian County and Dongfeng Canal located in the Zouma River,Chengdu,Sichuan Province,China.A comparison of the calculation results and monitoring data from the Sichuan Management and Monitoring Center Station of Radioactive Environment indicates that the percentage and absolute error of a activity concentration is lower than 53%and 0.02 Bq/L,respectively,and that of β-activity concentration is lower than 33.2%and 0.016 Bq/L,respectively.The method can rapidly determine gross α and β^(-) activity concentrations in natural water online.

Source apportionment of PM_(2.5)using PMF combined online bulk and single-particle measurements:Contribution of fireworks and biomass burning

Fireworks(FW)could significantly worsen air quality in short term during celebrations.Due to similar tracers with biomass burning(BB),the fast and precise qualification of FW and BB is still challenging.In this study,online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM_(2.5)and specific chemical species by positive matrix factorization(PMF)during the Chinese New Year in Hong Kong in February 2013.With combined information,fresh/aged FW(abundant ^(140)K_(2)NO_(3)^(+)and ^(213)K_(3)SO_(4)^(+)formed from ^(113)K_(2)Cl^(+)discharged by fresh FW)can be extracted from the fresh/aged BB sources,in addition to the Second Aerosol,Vehicles+Road Dust,and Sea Salt factors.The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region.The fresh BB/FW contributed 39.2%and 19.6%to PM_(2.5)during the Lunar Chinese New Year case.However,the contributions of aged FW/BB enhanced in the last two episodes due to the aging process,evidenced by high contributions from secondary aerosols.Generally,the fresh BB/FW showed more significant contributions to nitrate(35.1%and15.0%,respectively)compared with sulfate(25.1%and 5.9%,respectively)and OC(14.8%and11.1%,respectively)on average.In comparison,the aged FW contributed more to sulfate(13.4%).Overall,combining online bulk and single-particle measurement data can combine both instruments’advantages and provide a new perspective for applying source apportionment of aerosols using PMF.

ONLINE GRINDING WHEEL WEAR COMPENSATION BY IMAGE BASED MEASURING TECHNIQUES

Automatic compensation of grinding wheel wear in dry grinding is accomplished by an image based online measurement method. A kind of PC-based charge-coupled device image recognition system is schemed out, which detects the topography changes of the grinding wheel surface. Profile data, which corresponds to the wear and the topography, is measured by using a digital image processing method. The grinding wheel wear is evalualed by analyzing the position deviation of the grinding wheel edge. The online wear compensation is achieved according to the measure results. The precise detection and automatic compensation system is integrated into an open structure CNC curve grinding machine. A practical application is carried out to fulfil the precision curve grinding. The experimental results confirm the benefits of the proposed techniques, and the online detection accuracy is less than 5 um. The grinding machine provides higher precision according to the in-process grinding wheel error compensation.

Polarized imaging dynamic light scattering for simultaneous measurement of nanoparticle size and morphology

The performance of nanoparticles is often affected by particle size and morphology.Currently,electron microscopy or atomic force microscopy is typically utilized to determine the size and morphology of nanoparticles.However,there are issues such as difficult sample preparation,long processing times,and challenges in quantitative characterization.Therefore,it is of great significance to develop a fast,accu-rate,and statistical method to measure the size and morphology of nanoparticles.In this study,a new method,called polarized imaging dynamic light scattering(PIDLS),is proposed.The nanoparticles are irradiated with a vertical linearly polarized laser beam,and a polarization camera collected the dynamic light scattering images of particles at four different polarization directions(0°,45°,90°,and 135°)at a scattering angle of 90°.The average particle size and distribution are obtained using the imaging dy-namic light scattering method at 0°polarization direction,and the morphology of the particles is ob-tained based on the depolarization patterns of the scattered light.The optical sphericityΦis defined based on the degree of linear polarization(DoLP).It is also implemented for the quantitative evaluation of the sphericity of the nanoparticles,including spherical,octahedral,nanoplate,nanorod,and linear ones.Together with the Poincarésphere parameterψ,the morphology of the nanoparticles can be roughly identified.In addition,PIDLS enables the measurement of particle size and morphology distributions simultaneously for evaluating the uniformity of particles.The effectiveness of PIDLS is verified by the measurement of five kinds of industrial titanium dioxide as well.

Microinterface intensification in hydrogenation and air oxidation processes

Hydrogenations and air oxidations usually have low apparent reaction rate,generally controlled by mass transfer rate,and widely exist in the modern chemical manufacturing process.The key to increase the mass transfer rate is the reduction of the liquid film resistance 1/kLa.In this work,the original concept of microinterface intensification for mass transfer and then for these reactions has been proposed.We derived the regulation model and set up the mathematical calculation method of micron-scale gas-liquid interface structure on mass transfer and reaction,designed the mechanical energy exchange device that can produce gas-liquid microinterface system on a large scale,and established the OMIS system which is able on line to measure the diameter and distribution of millions of microbubbles,interface area a and mass transfer film thicknessδM,as well as developed a series of microinterface intensified reactor systems(MIRs)for the applications of hydrogenation and air oxidation processes.It is believed that this research will provide an up-to-date development for the intensification of hydrogenation and air oxidation reactions.

Feedback regulation system for spraying parameters based on online droplet mass deposit measurements

In order to effectively optimize and regulate spraying parameters based on actual spraying performance and improve pesticide utilization rate,in this research,a feedback regulation system for the regulation of spraying parameters was designed based on droplet mass deposit online measurement.The system consisted of an online droplet mass deposit measurement module,wireless transmission module,decision module,and spraying parameters regulation module.First,the droplet mass deposits on the sampling points were measured.Based on the deviation between the measured and expected droplet mass,the expected spraying parameters were determined by the decision module.The spraying parameter was regulated to the expected value by regulating the pulse duty cycle on the pump motor using a micro control unit and a relay.Evaluation tests were conducted indoors using an indoor spraying platform and outdoors using an unmanned aerial vehicle.The results showed that the relative errors between the expected and measured droplet mass deposit after regulation were 6.84%and 11.48%for the indoor and outdoor tests,respectively.Therefore,an optimal spraying performance was observed after regulation.This research provided an experimental platform to quickly optimize spraying parameters and also provided technical references for precision spraying.

Determining the Boundary of Molten Electrolyte and Aluminum in Electrolytic Cells by Detecting Their Vertical Distribution of Potential

Aluminum production is a high energy consumption process so that maintaining fundamental compositions in balance and optimal conditions are essential.The molten electrolyte and melted aluminum are primary materials and their boundary needs to be monitored from time to time.An automatic measurement technic is presented in the paper to substitute for the traditional manual measurement work that is dull,poor efficiency and dangerous for operators.The boundary forming mechanism is analyzed,the vertical profile of electric potential is simulated,an automatic instrument is developed to sense the potential distribution,and a strategy is provided to identify the boundary according to the potential curves.Finally,some practical results are compared with manual measurements,which shows good consistency.

Characteristics and source apportionment of ambient volatile organic compounds and ozone generation sensitivity in urban Jiaozuo,China

In recent years,many cities have taken measures to reduce volatile organic compounds(VOCs),an important precursor of ozone(O_(3)),to alleviate O_(3) pollution in China.116 VOC species were measured by online and offline methods in the urban area of Jiaozuo from May to October in 2021 to analyze the compositional characteristics.VOC sources were analyzed by a positive matrix factorization(PMF)model,and the sensitivity of ozone generation was determined by ozone isopleth plotting research(OZIPR)simulation.The results showed that the average volume concentration of total VOCs was 30.54 ppbv and showed a bimodal feature due to the rush-hour traffic in the morning and at nightfall.The most dominant VOC groups were oxygenated VOCs(OVOCs,29.3%)and alkanes(26.7%),and the most abundant VOC species were acetone and acetylene.However,based on the maximum incremental reactivity(MIR)method,the major VOC groups in terms of ozone formation potential(OFP)contribution were OVOCs(68.09μg/m^(3),31.5%),aromatics(62.90μg/m^(3),29.1%)and alkene/alkynes(54.90μg/m^(3),25.4%).This indicates that the control of OVOCs,aromatics and alkene/alkynes should take priority.Five sources of VOCs were quantified by PMF,including fixed sources of fossil fuel combustion(27.8%),industrial processes(25.9%),vehicle exhaust(19.7%),natural and secondary formation(13.9%)and solvent usage(12.7%).The empirical kinetic modeling approach(EKMA)curve obtained by OZIPR on O_(3) exceedance days indicated that the O_(3) sensitivity varied in different months.The results provide theoretical support for O_(3) pollution prevention and control in Jiaozuo.

Online Energy Measure and Analysis System for Large-Scale Public Buildings

Large-scale public buildings have high energy density, which on average consume 5 to 15 times more electricity than residential buildings. In Beijing, those public buildings account for about ten percent of the total building area, but their energy consumption （except heating） amounts to more than thirty percent of the total. Few electric meters are installed in those public buildings, however, making it more difficult to monitor how the energy is used.

Understanding Sybil Groups in the Wild

Sybil attacks are one kind of well-known and powerful attacks against online social networks （OSNs）. In a sybil attack, a malicious attacker generates a sybil group consisting of multiple sybil users, and controls them to attack the system. However, data confidentiality policies of major social network providers have severely limited researchers＇ access to large-scale datasets of sybil groups. A deep understanding of sybil groups can provide important insights into the characteristics of malicious behavior, as well as numerous practical implications on the design of security mechanisms. In this paper, we present an initial study to measure sybil groups in a large-scale OSN, Renren. We analyze sybil groups at different levels, including individual information, social relationships, and malicious activities. Our main observations are： 1） user information in sybil groups is usually incomplete and in poor quality; 2） sybil groups have special evolution patterns in connectivity structure, including bursty actions to add nodes, and a monotonous merging pattern that lacks non-singleton mergings; 3） several sybil groups have strong relationships with each other and compose sybil communities, and these communities cover a large number of users and pose great potential threats; 4） some sybil users are not banned until a long time after registration in some sybil groups. The characteristics of sybil groups can be leveraged to improve the security mechanisms in OSNs to defend against sybil attacks. Specifically, we suggest that OSNs should 1） check information completeness and quality, 2） learn from dynamics of community connectivity structure to detect sybil groups, 3） monitor sybil communities and inspect them carefully to prevent collusion, and 4） inspect sybil groups that behave normally even for a long time to prevent potential malicious behaviors.