Degradation Path Research Articles

Quantum assimilation-based data augmentation for state of health prediction of lithium-ion batteries with peculiar degradation paths

Lithium-ion batteries with more rapid capacity loss or “peculiar degradation paths” are usually hard to completely avoid in production given complex electrochemical systems and diverse failure mechanisms. These “abnormal” batteries typically account for only a small proportion in production, and their degradation paths may be very different from most “normal” batteries in the existing dataset. Therefore, it is difficult to accurately predict their subsequent capacity degradation trends using models trained by the existing dataset. To solve this problem, this paper proposes a novel data augmentation technique based on quantum assimilation to accurately predict the state of health of lithium-ion batteries with peculiar degradation paths. The quantum assimilation algorithm has the outstanding advantage of revealing the distribution of the samples by constructing the potential energy surface of the existing data with a nonlinear Gaussian wave function, which provides a novel feature space for data augmentation. The early-cycle data of newly emerged abnormal samples can also be located on this potential energy surface, and the possible degradation increment of each subsequent cycle can be inferred based on the principle that particles tend to gather at the position with the lowest potential energy. Based on this, possible degradation paths of abnormal samples can be generated to enhance the training dataset and the machine learning model trained using it can better predict the abnormal lithium-ion batteries. The proposed method is verified on an actual lithium-ion battery dataset with mean percentage error of the prediction results less than 0.5%, which is at least 44% lower than that of the other four conventional methods.

Alkali Etching Induced CoAl‐Layered Double Oxides with Regulatable Cation and Oxygen Vacancy Defects to Promote the Photothermal Degradation of Methanol

AbstractBy controlling the alkali etching time, the cation and oxygen vacancies contents of CoAl‐LDHs were adjusted. Then CoAl‐layered double oxides catalysts (CoAl‐LDOs‐x) were prepared by calcination and applied to the photothermal catalytic degradation of methanol and acetone under the full spectrum simulated solar illumination. Compared with CoAl‐LDOs‐0 without alkali etching, CoAl‐LDOs‐9 with alkali etching for 9 h showed the most superior photothermal catalytic activity and excellent stability. A series of studies had suggested that the most superior activity of the catalyst could be ascribed to the cation vacancy produced by alkali etching, resulting in more Co3+ active sites on the surface. At the same time, alkali etching also produced oxygen vacancy, which accelerated the adsorption and conversion of surface reactive oxygen species (ROS). In addition, the activation effect of light on lattice oxygen and gas phase oxygen was proved by in‐situ DRIFTS, and the degradation path of methanol was clarified.

Visible light assisted peroxymonosulfate activation by NiO/SnO2 composite for efficient tetracycline degradation

The hybrid of NiO/SnO2 was synthesized using a simple method and employed in peroxymonosulfate (PMS) activation for tetracycline (TC) degradation. Various characterization methods were applied to identify the physicochemical properties of NiO/SnO2. The formation of the NiO/SnO2 heterojunction significantly improved the activation performance of PMS, resulting in 90.2% TC degradation within 20 min under visible light irradiation. Furthermore, the excellent degradation performance can be maintained in different aqueous substrates, and a variety of anions had a slight effect on the TC degradation process. Free radical quenching experiments and electron paramagnetic resonance technology confirmed that superoxide radical (O2•-), singlet oxygen (1O2), hydroxyl radical (OH•) and sulfate radical (SO4•-) clusters were responsible for TC degradation. Liquid chromatography/mass spectrometry (LC/MS) technology and Toxicity Estimation Software Tool (T.E.S.T) were used to detect the intermediates and toxic changes in the degradation process of TC. In addition, a possible degradation path of TC was also proposed. Overall, this work provides new insight into PMS activation in antibiotic degradation by tin-based catalysts.

Photocatalytic activation of sulfite by N-doped porous biochar/MnFe2O4 interface-driven catalyst for efficient degradation of tetracycline

A novel photo-catalytic system composed of N-doped biochars (NBCs), MnFe2O4 and sulfite activation under ultraviolet (NBCs/MnFe2O4/sulfite/UV) was constructed to realize the efficient eliminate of tetracycline (TC). As the carrier of MnFe2O4, NBCs were synthesized from alfalfa, which has large specific surface area, graphite like structure and hierarchical porous structure. The adsorption isotherm indicated that NBCs/MnFe2O4-2:1 had the best adsorption performance for TC (347.56 mg g−1). Through synergistic adsorption and photocatalysis, the removal rate of TC reached 84%, which was significantly higher than that of MnFe2O4. Electrochemical impedance spectroscopy (EIS) and Photoluminescence (PL) characterization results showed that the introduction of NBCs improved the separation efficiency of photogenerated electron and hole pairs and enhanced the photocatalytic performance. Moreover, the adsorption, degradation mechanism and degradation path of TC by the catalyst were systematically analyzed by coupling HPLC–MS measurement with the theoretical calculation. Considering the advantages of excellent degradation performance, low cost, easy separation and environmental friendliness of NBCs/MnFe2O4, this work was expected to provide a new path for the practical application of biochar.

Energy band reconstruction mechanism of Cl-doped Cu2O and photocatalytic degradation pathway for levofloxacin

Cl-doped Cu 2 O microparticles were prepared by hydrothermal synthesis . XRD, BET, SEM, TEM, UV–Vis and RSM were used to reveal the microstructure, optical properties and degradation regularity of the Cl-doped Cu 2 O microparticles. The band gap structures and state densities of Cl-doped Cu 2 O microparticles were computed based on density functional theory . The major intermediate degradation products and potential photocatalytic degradation pathways of levofloxacin were identified by HPLC–MS/MS. The photocatalytic active sites of levofloxacin and its intermediate products were calculated based on the frontier electron densities. The results showed that the prepared Cl-doped Cu 2 O microparticles increased the specific surface area and absorption efficiency of visible light compared with undoped pure Cu 2 O. The doping of Cl introduced hybrid orbitals and oxygen vacancy defects in the Cu 2 O crystal cell and decreased the forbidden bandwidth of Cu 2 O crystal microparticles, leading to a redshift of the absorption edge . Cl doping could form a shallow donor impurity energy level composed of Cl 3 p orbital in the energy gap of Cu 2 O and make the energy band denser and move to a lower energy, which could promote the electron leap to the conduction band through the impurity level . The doping of Cl can make the density of states curve of the Cu 2 O crystal shift to low-energy and the Cl-doped Cu 2 O rendered to half-metallic behavior and characteristic behavior of an n type semiconductor. The photocatalytic degradation of levofloxacin was attributed to attack of photogenerated holes and hydroxyl radicals , and the ring opening of the piperazine ring by oxidation and decarboxylation reactions from the quinolone ring might be two photocatalytic degradation pathways. This study revealed the mechanism of oxygen vacancy formation and the change rules of the band structure by doping of the nonmetal chlorine into Cu 2 O crystallites . • Migration laws of band structure and state density of Cl-doped Cu 2 O were revealed. • Doping of Cl introduced hybrid orbitals and oxygen vacancies in the Cu 2 O crystal. • Doping of Cl decreased band gap of Cu 2 O and led to red shift of absorption edge. • Holes and hydroxyl radicals are the main photocatalytic active species. • Degradation paths of levofloxacin were piperazine ring opening and decarboxylation.

Degradation of tiamulin by a packed bed dielectric barrier plasma combined with TiO2 catalyst

Recently, a plasma catalyst was employed to efficiently degrade antibiotic residues in the environment. In this study, the plasma generated in a packed bed dielectric barrier reactor combined with TiO2 catalyst is used to degrade the antibiotic tiamulin (TIA) loaded on the surface of simulated soil particles. The effects of applied voltage, composition of the working gas, gas flow rate and presence or absence of catalyst on the degradation effect were studied. It was found that plasma and catalyst can produce a synergistic effect under optimal conditions (applied voltage 25 kV, oxygen ratio 1%, gas flow rate 0.6 l min−1, treatment time 5 min). The degradation efficiency of the plasma combined with catalyst can reach 78.6%, which is 18.4% higher than that of plasma without catalyst. When the applied voltage is 30 kV, the gas flow rate is 1 l min−1, the oxygen ratio is 1% and the plasma combined with TiO2 catalyst treats the sample for 5 min the degradation efficiency of TIA reached 97%. It can be concluded that a higher applied voltage and longer processing times not only lead to more degradation but also result in a lower energy efficiency. Decreasing the oxygen ratio and gas flow rate could improve the degradation efficiency. The relative distribution and identity of the major TIA degradation product generated was determined by high-performance liquid chromatography–mass spectrometry analysis. The mechanism of TIA removal by plasma and TiO2 catalyst was analyzed, and the possible degradation path is discussed.

A bidirectional wear model based on Inverse Gaussian (IG) process for PEEK against AISI630 stainless steel in seawater hydraulic components

With the increasing integration of seawater hydraulic components, much attention has been paid to the tribological characteristics of PEEK bidirectional sliding against AISI630 tribopair. In the study, a bidirectional wear model based on Inverse Gaussian (IG) process is proposed based on bidirectional wear experiment. Impact wear occurs when the tribopair changes the motion direction. Through analysing the wear process and worn surface morphology of PEEK against AISI630 tribopairs, it is found that the impact wear would accelerate the formation and uniform distribution of PEEK transfer film, and the increase of reversal frequency can improve the tribological characteristics of the bidirectional tribopairs. The IG model considering the reversal impact can accurately illustrate the performance degradation path of actual impact wear.

Hydrothermally modified graphite felt as the electro-Fenton cathode for effective degradation of diuron: The acceleration of Fe2+ regeneration and H2O2 production

The generation of H2O2 and the regeneration rate of Fe2+ both affect the degradation performance of the electro-Fenton (EF) process. Therefore, it is important to develop a cathode that efficiently produces H2O2 and regenerates Fe2+. In this study, graphite felt (GF) was modified via a simple hydrothermal method using ammonium persulfate as the modifier. The physicochemical and electrochemical properties of hydrothermally modified GF (H-GF) were substantially improved. The surface of H-GF was successfully doped with O and N, and its oxygen reduction reaction activity increased significantly. Compared with raw GF, the yield of H2O2 and the regeneration rate of Fe2+ of H-GFwere considerably improved. The EF system constructed with H-GF as the cathode could completely remove diuron at −0.65 V/SCE within 40 min. In the EF system, H-GF exhibited an excellent degradation effect in different types of water (tap and river water) and different pollutants (amoxicillin, atrazine, and sulfamethoxazole). After the 40th cycle, the H-GF cathode retained excellent stability. According to density functional theory calculations, H2O2 and Fe2+ were easily generated due to the low energy barrier required for the adsorption of O2 and Fe3+ on H-GF. Finally, a possible degradation path of diuron in the EF process was proposed, and the toxicity of the intermediates produced in the degradation process of diuron was analyzed.

Machine Learning Approach for Degradation Path Prediction Using Different Models and Architectures of Artificial Neural Networks

Degradation and failure prediction has become more and more crucial for maintenance planning and scheduling, the decision-making process, and many other areas of manufacturing systems. This paper presents an approach where different artificial neural network models were developed to predict the degradation path of a machine component using different architectures, including fully connected networks (FCN) and arbitrarily connected networks (ACN). These models were trained using the Neuron-by-Neuron (NBN) training algorithm with forward-backward computations, where NBN is an improved form of the Levenberg-Marquardt (LM) algorithm, combined with FCN and ACN architectures, which can be trained efficiently, it can give more accurate predictions with a fewer number of neurons used. The developed models were evaluated using the statistical performance measure of the sum of squared error (SSE). The results show that the used networks are successfully able to predict the degradation path; the 8-neurons model of FCN architecture and the 3-neurons model of ACN architecture with tanh (mbib) hidden layers activation function and linear function (mlin) of the outputs have the lowest prediction error (SSE) among all the developed models. The use of such architectures combined with NBN training algorithm can easily model manufacturing systems with complex component structures that provide a vast amount of data.

Amorphous Co@TiO2 heterojunctions: A high-performance and stable catalyst for the efficient degradation of sulfamethazine via peroxymonosulfate activation

Persulfate-based advanced oxidation processes (AOPs) cannot easily achieve the efficient degradation of persistent organic pollutants (POPs) with high stability. In this study, a simple in situ precipitation method was used to prepare an amorphous Co@TiO2 heterojunction catalyst. The deposition of Co oxide on TiO2, which is relatively nontoxic, efficiently activated peroxymonosulfate (PMS) to degrade sulfamethazine (SMT) and reduce the leaching of Co ions (0.915%). A catalytic system prepared using 0.3 g L−1 Co@TiO2 and 0.5 g L−1 PMS could degrade SMT within 30 min with a degradation rate of 95.8%. Co@TiO2 could activate PMS over a wide pH range (5.00–9.00) to efficiently degrade other antibiotics and dyes. Radical-capture experiments and electron paramagnetic resonance analysis suggested that SMT degradation occurs through a combination of the free radical and non-radical pathways, in which singlet 1O2 played a major role. Owing to the novelty of the proposed composite materials, the degradation path of SMT, which was determined through liquid chromatography–mass spectrometry, differed from that reported previously. This study provides not only an advanced and renewable catalyst for SMT degradation but also a feasible strategy for designing materials for AOPs.

Fabrication of a Z-scheme CeO2/Bi2O4 heterojunction photocatalyst with superior visible-light responsive photocatalytic performance

In this study, a CeO 2 /Bi 2 O 4 Z-scheme heterojunction was prepared by using a facile hydrothermal method. After 40 min of visible-light irradiation, this composite photocatalyst displayed superior photocatalytic activity for removing levofloxacin and methyl orange than pure CeO 2 and Bi 2 O 4 , achieving the degradation efficiencies of 88.75% and 90.3%, respectively. According to the results of transient photocurrent response, electrochemical impedance spectroscopy, and photoluminescence, CeO 2 /Bi 2 O 4 heterojunction photocatalyst exhibited efficient photoinduced charges separation. The enhanced photocatalytic performance was due to synergy between efficient separation of photogenerated carriers and increased solar absorption. A Z-scheme heterojunction between CeO 2 and Bi 2 O 4 was formed, which was contributed by the well-matched band structure, facilitating the fast transfer and separation of carriers. The active species, including h + , O 2 · – , and ·OH, play key roles in the photodegradation reactions, demonstrated by electron spin resonance spectroscopy. High-performance liquid chromatography-mass spectrometry was used to identify the probable degradation path of levofloxacin. This work will benefit the design of efficient Z-scheme heterojunction photocatalysts for environmental remediation. • MO and LVF were used to evaluate the photocatalytic activities. • HAADF-STEM, ESR and HPLC-MS analysis were used to analyze the mechanism. • The separation of photoinduced carriers was testified by photocurrent, PL and SPV. • A possible mechanism of CeO 2 /Bi 2 O 4 Z-scheme heterojunction is proposed.

Remaining useful life prediction using composite health index and hybrid LSTM‐SVR model

AbstractRemaining useful life (RUL) plays an important role in prognostic and health management to reduce maintenance costs and avoid possible accidents. Massive multi‐sensor data makes it challenging to extract degradation features and predict RUL. This paper develops a novel RUL prediction framework consisted of a multi‐sensor fusion model and a hybrid prediction model. HI curves are constructed by synthesizing multiple metrics including time correlation, monotonicity, robustness, and consistency, making our data fusion method different from existing methods considering only one metric. In many practical situations, the initial degradation levels of obtained HI curves are different, and treating all curves without classification will result in errors in RUL prediction. The K‐means method is used to partition degradation paths into discrete states and the obtained HI curves are grouped by their initial states and then trained separately. A hybrid prediction model combining Long Short‐Term Memory (LSTM) network and Support Vector Regression (SVR) is developed to predict the RUL. The dataset of turbofan engines is used to verify the proposed method. The results show that the proposed method performs better than many existing methods.

A novel visible-light-induced double Z-scheme photocatalytic system: NH2-UiO-66/BiOBr/Bi2S3 for degradation of tetracycline hydrochloride and rhodamine B

The unique properties of MOFs make them the best candidates for catalytic and photocatalytic applications. In this research, the NH2-UiO-66 material was prepared by solvothermal method, and different content of NH2-UiO-66 was added before the composite growth of Bi2S3 and BiOBr nanomaterials to obtain the NH2-UiO-66/BiOBr/Bi2S3 ternary composite material. In order to investigate the relationship between the structure and properties of the catalyst, XRD, FT-IR, SEM, HRTEM, UV–vis DRS, XPS and other characterization technologies were used to analyze the structure, morphology, optical properties of the samples, showing that NH2-UiO-66/BiOBr/Bi2S3 have been successfully synthesized. Their photocatalytic performance was evaluated based on the photocatalytic degradation of tetracycline hydrochloride and rhodamine B under visible light. The results show that 2% NH2-UiO-66/BiOBr/Bi2S3 has better photocatalytic activity than other materials. Moreover, NH2-UiO-66/BiOBr/Bi2S3 also demonstrated good photocatalytic reusability and stability. The formation of Bi2S3 and BiOBr heterojunctions and the introduction of NH2-UiO-66 with more active sites increase the carrier performance and separation efficiency. Then the valence band and conduction band values of the semiconductor material are calculated through the M-S curve, combined with the forbidden bandwidth deduced by UV–vis DRS and the experimental results of radical trapping, a double Z-type electron transfer mechanism suitable for this system is inferred. Finally, taking RhB as an example, the degradation path of dye pollutants was studied.

Degradation of sulfamethazine sodium salt by peroxymonosulfate activated by biochar supported CoFe2S4: Performance, mechanism and response surface method optimization

The persulfate oxidation process plays a critical role in eliminating antibiotics in wastewater, so it is urgent to develop a cheap, environmentally friendly and effective catalyst. In this study, CoFe2S4/BC catalyst was synthesized by a two-step hydrothermal method and combined with peroxymonosulfate (PMS) to degrade sulfamethazine sodium salt (SMT). The degradation results can be effectively predicted by establishing the response surface model. In order to maximize the removal rate of SMT, the optimization conditions are: catalyst dosage is 0.8 mg·L−1, PMS dosage is 0.5 mM, the pH value is 9.0 and the predicted degradation rate of SMT is 86.87% under these conditions. Also, the effects of PMS dosage, catalyst dosage, pH value and coexisting substances in the water on the degradation of SMT were also systematically studied. Besides, In the CoFe2S4/BC/PMS system, there are both free radical and non-free radical pathways, in which the contribution of SO4·- was dominant. And the possible reaction mechanism and degradation path of SMT was proposed. In consequence, these results describe that CoFe2S4/BC is an excellent catalytic material and can be regarded as a catalyst for the catalytic degradation of antibiotics in wastewater treatment.

Insight into the mechanisms of BPS degradation by electro-Fenton method modified by Co-based nanoparticles on the oxidized carbon cathode

4,4′-sulfonyldiphenol, as one type of persistent organic pollutants, has become an environmental problem because of its toxicity and harmfulness. In this study, cobalt-based nanoparticles on oxidized carbon black (Co-OBC) rich in oxygen functional groups and pyrrole nitrogen, which were adopted as catalyst to promote the performance for BPS degradation using electro-Fenton method. The results show that Co-OBC exhibited better performance in degradation of BPS by electro-Fenton than cobalt-based nanoparticles on carbon black (Co-BC), and BPS could be completely degraded within 15 min under optimal conditions (c(Fe2+) = 0.3 mM, pH 3, U = -0.5 V). In order to explore the degradation mechanisms of BPS, Liquid Chromatography-Mass Spectrometry (LC-MS) analysis was combined with Density Functional Theory (DFT) calculation. Three degradation paths were proposed. More importantly, the decomposition free energy of BPS in path I was 15.5 kcal/mol, which is the lowest of three paths. Therefore, path I was the main pathway of BPS degradation, and other pathways were secondary. Finally, ECOSAR software prediction revealed that the degradation of BPS could reduce the toxicity step-by-step, which was beneficial for environmental protection. By analyzing the degradation mechanisms and toxicity prediction of BPS, we can better understand the characteristics of persistent compounds and their harm to the environment, which can be beneficial to solve environmental pollution.

Fe3O4–CuO@Lignite activated coke activated persulfate advanced treatment of phenolic wastewater from coal chemical industry

In this study, lignite activated coke (LAC) was used as the carrier for the first time, Fe3O4–CuO composite metal oxide was used as the main active material, and the nano-scale magnetic supported composite metal oxide Fe3O4–CuO@LAC catalyst was synthesized for the first time, which can effectively activate the active oxygen in peroxodisulfate (PS). XRD, FTIR, BET, SEM, XPS and other analysis results showed that there was particulate matter with spherical structure on the surface of the active coke, and its diffraction peaks matched well with the characteristic peaks of Fe3O4 and CuO, and it was a mesoporous structure with a specific surface area of 619.090 m2 g−1. By optimizing the experimental conditions, the results showed that more than 92% of hydroquinone can be removed under the conditions of hydroquinone concentration of 50 mg/L, pH = 5, adding 0.1 g/L catalyst and 3 mmol/L PS. EPR and quenching experiments proved that there were four reactive oxygen species in the reaction system ·OH, SO4−·, O2−· and 1O2. According to the degradation products of hydroquinone detected by LC-MS, the possible degradation path was deduced which laid a foundation for solving the problem of difficult treatment of phenol-containing wastewater in coal chemical industry.

Data-level transfer learning for degradation modeling and prognosis

The typical way to conduct data-driven prognosis is to train a degradation model with historical data, then apply the model to predict failure for in-service units. Most existing works assume the historical data and in-service data are from the same process. In practice, however, different but related processes can share similar degradation patterns. Thus, the historical data from these processes are expected to provide useful prognosis information for each other. In this article, we propose a data-level transfer learning framework to extract useful and shared information from different processes to benefit the prognosis of in-service units. In this framework, the degradation data in each process is modeled by a mixed effects model. To facilitate the information sharing among different mixed effects models, a hierarchical Bayesian structure is proposed to model and connect the distributions of mixed effects in different mixed models. Because the degradation paths in different processes are rarely the same, the dimension of the mixed effects/regressor in each process can be different. To handle this issue, we propose a tailored linear transformation to marginalize or expand the distributions of mixed effects in different degradation processes to achieve consistent dimensions. The transferred information is finally incorporated with the degradation data from in-service units to conduct prognosis. The proposed method is validated and compared with various benchmarks in extensive numerical studies and two case studies. The results show the proposed method can successfully transfer useful information in different processes to benefit the prognosis.

Ultradurable fluorinated V2AlC for peroxymonosulfate activation in organic pollutant degradation processes

Vanadium-based catalysts are considered the most promising materials to replace cobalt-based catalysts for the activation of peroxymonosulfate (PMS) to degrade organic pollutants. However, these traditional vanadium species easily leak out metal ions that can affect the environment, even though the of vanadium is much less than that of cobalt. Compared to other vanadium-based catalysts, e.g., V 2 O 3 , fluorinated V 2 AlC shows a high and constant activity and reusability regarding PMS activation. Furthermore, it features extremely low ion leakage. Active oxygen species scavenging and electron spin resonance measurements reveal that the main reactive oxygen species was 1 O 2 , which was induced by a two-dimensional confinement effect. More importantly, for the real-life application of tetracycline (TC) degradation, the introduction of fluorine changed the adsorption mode of TC over the catalyst, thereby changing the degradation path. The intermediate products were detected by liquid-chromatography mass spectroscopy (LC-MS), and a possible degradation path was proposed. The environmental impact test of the decomposition products showed that the toxicity of the degradation intermediates was greatly reduced. Therefore, the investigated ultradurable catalyst material provides a basis for the practical application of advanced PMS oxidation technology. F-V 2 AlC showed higher activity and better reusability than V 2 O 3 for PMS activation with extremely low ion leakage. And mechanism investigation showed that the main reactive oxygen specie was 1 O 2 , which induced by the two-dimensional confinement effect. In addition, the introduction of F changed the adsorption mode of TC over catalyst, thereby changing the degradation path.

Passivation of degradation path enables high performance perovskite nanoplatelet lasers with high operational stability

MAPbI 3 perovskite has attracted widespread interests for developing low-cost near infrared semiconductor gain media. However, it faces the instability issue under operation conditions, which remains a critical challenge. It is found that the instability of the MAPbI 3 nanoplatelet laser comes from the thermal-induced degradation progressing from the surface defects towards neighboring regions. By using PbI 2 passivation, the defect-initiated degradation is significantly suppressed and the nanoplatelet degrades in a layer-by-layer way, enabling the MAPbI 3 laser to sustain for 4500 s ( 2.7 × 10 7 pulses ), which is nearly three times longer than that of the nanoplatelet laser without passivation. Meanwhile, the PbI 2 passivated MAPbI 3 nanoplatelet laser with the nanoplatelet cavity displays a maximum quality factor up to ∼ 7800 , the highest reported for all MAPbI 3 nanoplatelet cavities. Furthermore, a high stability MAPbI 3 nanoplatelet laser that can last for 8500 s ( 5.1 × 10 7 pulses ) is demonstrated based on a dual passivation strategy, by retarding the defect-initiated degradation and surface-initiated degradation simultaneously. This work provides in-depth insights for understanding the operating degradation of perovskite lasers, and the dual passivation strategy paves the way for developing high stability near infrared semiconductor laser media.

Stochastic comparisons of linear degradation and failure time models with dependent failure modes

The paper considers a reliability model for system which fails due to degradation failure or catastrophic failure. The linear degradation path is adopted to model the degradation process, and catastrophic failure rate is dependent on the degradation rate. Firstly, we conduct some stochastic comparisons between two systems when their respective degradation rate variables are ordered in the sense of various stochastic orders. Secondly, we conduct some stochastic comparisons between two systems with different conditional catastrophic failure rates. Finally, we give some examples with respect to some well-know models to illustrate the validity of the results.