Effect of preload forces on multidimensional signal dynamic behaviours for battery early safety warning

Providing early safety warning for batteries in real-world applications is challenging.In this study,comprehensive thermal abuse experiments are conducted to clarify the multidimensional signal evolution of battery failure under various preload forces.The time-sequence relationship among expansion force,voltage,and temperature during thermal abuse under five categorised stages is revealed.Three characteristic peaks are identified for the expansion force,which correspond to venting,internal short-circuiting,and thermal runaway.In particular,an abnormal expansion force signal can be detected at temperatures as low as 42.4°C,followed by battery thermal runaway in approximately 6.5 min.Moreover,reducing the preload force can improve the effectiveness of the early-warning method via the expansion force.Specifically,reducing the preload force from 6000 to 1000 N prolongs the warning time(i.e.,227 to 398 s)before thermal runaway is triggered.Based on the results,a notable expansion force early-warning method is proposed that can successfully enable early safety warning approximately 375 s ahead of battery thermal runaway and effectively prevent failure propagation with module validation.This study provides a practical reference for the development of timely and accurate early-warning strategies as well as guidance for the design of safer battery systems.

Designer uniform Li plating/stripping through lithium–cobalt alloying hierarchical scaffolds for scalable high-performance lithium-metal anodes

Lithium metal anodes are of great interest for advanced high-energy density batteries such as lithiumair, lithium-sulfur and solid-state batteries, due to their low electrode potential and ultra-high theoretical capacity. There are, however, several challenges limiting their practical applications, which include low coulombic efficiency, the uncontrollable growth of dendrites and poor rate capability. Here, a rational design of 3D structured lithium metal anodes comprising of in-situ growth of cobalt-decorated nitrogen-doped carbon nanotubes on continuous carbon nanofibers is demonstrated via electrospinning.The porous and free-standing scaffold can enhance the tolerance to stresses resulting from the intrinsic volume change during Li plating/stripping, delivering a significant boost in both charge/discharge rates and stable cycling performance. A binary Co-Li alloying phase was generated at the initial discharge process, creating more active sites for the Li nucleation and uniform deposition. Characterization and density functional theory calculations show that the conductive and uniformly distributed cobalt-decorated carbon nanotubes with hierarchical structure can effectively reduce the local current density and more easily absorb Li atoms, leading to more uniform Li nucleation during plating. The current work presents an advance on scalable and cost-effective strategies for novel electrode materials with 3D hierarchical microstructures and mechanical flexibility for lithium metal anodes.

Highly Aligned Ultra-Thick Gel-Based Cathodes Unlocking Ultra-High Energy Density Batteries

Increasing electrode thickness can substantially enhance the specific energy of lithium-ion batteries;however,ionic transport,electronic conductivity,and ink rheology are current barriers to adoption.Here,a novel approach using a mixed xanthan gum and locust bean gum binder to construct ultrathick electrodes is proposed to address above issues.After combining aqueous binder with single-walled carbon nanotubes(SWCNT),active material(LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)) and subsequent vacuum freeze-drying,highly aligned,and low-tortuosity structures with a porosity of ca.50%can be achieved with an average pore size of 10μm,whereby the gum binder-SWCNT-NMC811 forms vertical structures supported by tissue-like binder/SWCNT networks allowing for excellent electronic conducting phase percolation.As a result,ultra-thick electrodes with a mass loading of about 511 mg cm^(−2) and 99.5 wt%active materials have been demonstrated with a remarkable areal capacity of 79.3 mAh cm^(−2),which is the highest value reported so far.This represents a>25×improvement compared with conventional electrodes with an areal capacity of about 3 mAh cm^(−2).This route also can be expanded to other electrode materials,such as LiFePO_(4) and Li_(4)Ti_(5)O_(12),and thus opens the possibility for low-cost and sustainable ultra-thick electrodes with increased specific energy for future lithium-ion batteries.

Parameter-independent error correction for potential measurements by reference electrode in lithium-ion batteries

The safety monitoring of lithium-ion batteries(LIBs) is of great significance for realizing all-climate and full-lifespan battery management. In-situ measurement of anode potential with implanted reference electrodes(REs) has proven to be effective to monitor and avoid the occurrence of severe side reactions like Li plating to ensure the safe and fast charging. However, the intrinsic measurement errors caused by local blocking effects, which also can be referred to as potential artefacts, are seldom taken into consideration in existing studies, yet they highly dominate the correctness of conclusions inferred from REs. In this study, aiming at exploring the physical origin of the measurement errors and ensure reliable potential monitoring, electrochemical and post-mortem tests are conducted using commercial pouch cells with implanted REs. Corresponding electrochemical model which describes the blocking effects, is established to validate the abnormal absence of lithium plating that predicted by measured anode potentials under various charging rates. Theoretical derivation is further presented to explain the error sources, which can be attributed to increased local liquid potential of the RE position. Most importantly, with the guidance of error analysis, a novel parameter-independent error correction method for RE measurements is proposed for the first time, which is proven to be adequate to estimate the real anode potentials and deduce the critical C-rate of Li plating with extra safety margin. After error correction, the resulting critical C-rates are all within the range of 0.55 ± 0.03 C, which is close to the C-rate of 0.6–0.7 C obtained from experiments. In addition, this error correction method can be performed conveniently with only some simple RE measurements of polarization voltages, totally independent of battery electrochemical and geometric parameters. This study provides highly practical error correction method for RE measurements in real LIBs, substantially facilitating the fast diagnosis and safety evaluation of Li plating during charging of LIBs.

1990年和2019年中国分省精神障碍伤残负担分析

目的分析1990年和2019年中国人群精神障碍患病及伤残负担变化情况, 为降低精神障碍健康危害提供参考。方法利用2019年全球疾病负担(Global Burden of Disease Study 2019, GBD2019)中国研究结果, 分析2019年中国人群不同年龄、不同性别、不同省份精神障碍患病及伤残负担, 比较1990年与2019年中国精神障碍的患病和伤残损失寿命年(years of life lived with disability, YLDs)指标变化情况。结果 2019年中国精神障碍50~69岁年龄组患病率最高(13.2%, 患病人数为4 853.0万), 0~14岁年龄组患病率最低(7.3%, 患病人数为1 645.6万);女性总体YLDs数量高于男性(1 091.0万人年/938.2万人年);2019年抑郁障碍、焦虑症、精神分裂症的标化患病率分别为2.7%、3.2%、0.3%, 患病人数分别为5 005.6万、4 784.2万、549.9万;与1990年比较, 抑郁障碍和焦虑症的标化患病率下降幅度分别为9.1%和9.8%, 精神分裂症的标化患病率上升幅度为3.1%;2019年中国精神障碍标化患病率前3位的省份分别是湖南省(12.2%)、甘肃省(12.1%)和宁夏回族自治区(11.8%), 3个省份的精神障碍患病人数分别为890.1万、336.4万、87.3万。标化YLDs率位于前3位的省份分别为山东省(1 470.0/10万)、甘肃省(1 415.6/10万)和湖南省(1 399.3/10万)。结论精神障碍是威胁中国人群身心健康的重要疾病, 2019年中国精神障碍伤残负担仍处于较高水平;女性精神障碍伤残负担更加严重;应提早采取干预措施, 减少精神障碍伤残负担。

Review of Abnormality Detection and Fault Diagnosis Methods for Lithium‑Ion Batteries

Electric vehicles are developing prosperously in recent years.Lithium-ion batteries have become the dominant energy storage device in electric vehicle application because of its advantages such as high power density and long cycle life.To ensure safe and efficient battery operations and to enable timely battery system maintenance,accurate and reliable detection and diagnosis of battery faults are necessitated.In this paper,the state-of-the-art battery fault diagnosis methods are comprehensively reviewed.First,the degradation and fault mechanisms are analyzed and common abnormal behaviors are summarized.Then,the fault diagnosis methods are categorized into the statistical analysis-,model-,signal processing-,and data-driven methods.Their distinctive characteristics and applications are summarized and compared.Finally,the challenges facing the existing fault diagnosis methods are discussed and the future research directions are pointed out.

Superlubricity by polyimide-induced alignment

We have investigated the lubrication alignment behavior of point–plane contact and plane–plane contact between the GCr15 steel and polyimide(PI)friction pair using nematic liquid crystals(LCs)as the lubricant.In this system,rubbing orients the macromolecular PI molecules,and the oriented PI molecules induce alignment of the LC molecules in contact with or close to the oriented PI molecules.The LC molecules are aligned in the wear scar grooves of the PI film,and alignment extends to the GCr15-steel counterpart.Alignment of the LC molecules is correlated with the strong interaction force between the PI and LC molecules,the stable coordination structure of the LCs and GCr15 steel,and the weak interaction between the LC molecules.We performed simulations of the pretilt angle of PI and LCs and discussed the relationship between the pretilt angle and the friction properties.Owing to the small pretilt angle between PI and the LCs,the LC molecules orient almost parallel to the PI material,which is beneficial for superlubricity of this type of friction system.

Effect of industrial robot use on China’s labor market:Evidence from manufacturing industry segmentation

This paper empirically investigates the impact of industrial robot use on China’s labor market using data from 13 segments of manufacturing industry between 2006 and 2016.According to the findings,the use of industrial robots has a displacement effect on labor demand in manufacturing industry.The specific performance is that for every 1%increase in industrial robot stock,labor demand falls by 1.8%.After endogenous processing and a robustness test,this conclusion remains valid.This paper also discusses the effects of industrial robots across industries and genders.According to the results,industrial robot applications have a more pronounced displacement effect in low-skilled manufacturing than in high-skilled manufacturing.In comparison to female workers,industrial robot applications are more likely to decrease the demand for male workers.Moreover,this paper indicates that the displacement effect is significantly influenced by labor costs.Finally,we make appropriate policy recommendations for the labor market’s employment stability based on the findings.

Isosteric design of friction-reduction and anti-wear lubricant additives with less sulfur content

To reduce harmful sulfur content in lubricant additives, making use of isosterism has been shown to be an effective strategy. When thiobenzothiazole compounds were used as templates, the exchange of sulfur atoms in the thiazole ring with oxygen atoms and NH groups produced twelve isosteres. Similarly, 2-benzothiazole- S-carboxylic acid esters were used as template molecules to produce six isosteres. About 30% of the isosteres exhibited a satisfactory deviation of ±5% relative to the template, ignoring the specific changes in the base oils, the differences in molecular structure, and the friction or wear properties. The template molecules and isosteres in triisodecyl trimellitate exhibited better tribological properties than in trimethylolpropane trioleate or bis(2- ethylhexyl) adipate. Comparative molecular field analysis(CoM FA)- and comparative molecular similarity index analysis(CoMSIA)-quantitative structure tribo-ability relationship(QSTR) models were employed to study the correlation of molecular structures between the base oils and additives. The models indicate that the higher the structural similarities of the base oils and additives are, the more synergetic the molecular force fields of the lubricating system are; the molecular force fields creating synergistic effects will improve tribological performance.

Estimating antiwear properties of esters as potential lubricantbased oils using QSTR models with CoMFA and CoMSIA

Comparative molecular field analysis and comparative molecular similarity indices analysis were employed to analyze the antiwear properties of a series of 57 esters as potential lubricant-based oils. Predictive 3D-quantitative structure tribo-ability relationship models were established using the SYBYL multifit molecular alignment rule with a training set and a test set. The optimum models were all shown to be statistically significant with cross-validated coefficients q^2 > 0.5 and conventional coefficients r^2 > 0.9, indicating that the models are sufficiently reliable for activity prediction, and may be useful in the design of novel ester-based oils.

Multi‑scale Battery Modeling Method for Fault Diagnosis

Fault diagnosis is key to enhancing the performance and safety of battery storage systems.However,it is challenging to realize efficient fault diagnosis for lithium-ion batteries because the accuracy diagnostic algorithm is limited and the features of the different faults are similar.The model-based method has been widely used for degradation mechanism analysis,state estimation,and life prediction of lithium-ion battery systems due to the fast speed and high development efficiency.This paper reviews the mainstream modeling approaches used for battery diagnosis.First,a review of the battery’s degradation mechanisms and the external factors affecting the aging rate is presented.Second,the different modeling approaches are summarized,from microscopic to macroscopic scales,including density functional theory,molecular dynamics,X-ray computed tomography technology,electrochemical model,equivalent circuit model,distributed model and neural network algorithm.Subsequently,the advantages and disadvantages of these model approaches are discussed for fault detection and diagnosis of batteries in different application scenarios.Finally,the remaining challenges of model-based battery diagnosis and the future perspective of using cloud control and battery intelligent networking to enhance diagnostic performance are discussed.

Relationship between contact size and static friction:An approach for rigid crystalline surfaces

Relationship between contact size(A)and static friction(f)has been studied for rigid crystalline systems.We built a series of systems with two identical surfaces but different orientations and investigated the effects of the size and shape of the contact area on static friction.In these systems,there are numerous nontrivial commensurate contacts.Our results confirmed that the relationship between A and f was determined by both commensurability and shape of the contact.For commensurate contacts,f∝A independent of the shape.For incommensurate contacts,generally f∝A^(0) for regular shapes or f∝A^(1/4) for irregular shapes;however,in very few cases of regular shapes,f∝A^(1/2).Moreover,in above systems,commensurability of a contact can be easily changed by a perturbation of the misfit angle.Therefore,if the perturbation caused by the lateral force and the deformation of the surface are considered(as is the case in real systems),further research is necessary.

Non-invasive Characteristic Curve Analysis of Lithium-ion Batteries Enabling Degradation Analysis and Data-Driven Model Construction:A Review

Power battery technology is essential to ensuring the overall performance and safety of electric vehicles.Non-invasive char-acteristic curve analysis(CCA)for lithium-ion batteries is of particular importance.CCA can provide characteristic data for further applications such as state estimation and thermal runaway warning without disassembling the batteries.This paper summarizes the characteristic curves consisting of incremental curve analysis,differential voltage analysis,and differential thermal voltammetry from the perspectives of exploring the aging mechanism of batteries and constructing the data-driven model.The process of quantitative analysis of battery aging mechanism is presented and the steps of constructing data-driven models are induced.Moreover,the recent progress and application of the main features and methodologies are discussed.Finally,the applicability of battery CCA is discussed by converting non-quantifiable battery information into transportable data covering macrostate and micro-reaction information.Combined with the cloud-based battery management platform,the above-mentioned battery characteristic curves could be used as a valuable dataset to upgrade the next-generation battery management system design.