Degradation Phenomena Research Articles

Characterisation of SiOX / SiNX Surface Passivation Using Time-of-Flight Elastic Recoil Detection Analysis

An accurate description of the distribution of hydrogen at solar cell interfaces is critical for understanding both passivation and degradation phenomena. Time-of-flight elastic recoil detection analysis (ToF-ERDA) has recently been employed to study this hydrogen distribution by providing a one-dimensional (1D) depth profile. In this work, ToF-ERDA was used to investigate the hydrogen profile in a SiOX / SiNX passivating stack. The ability to resolve the interface with the c-Si interface was studied by using polished wafers and thin (20 nm) passivating stacks. This approach, coupled with Monte Carlo ERD (MCERD) modelling, showed that the identification of the interfacial oxide was much more clearly defined compared with previous reports using ToF-ERDA. Annealing the SiOX / SiNX at 450 °C for 5 minutes substantially increased the effective lifetime. However, no noticeable change in the H distribution measured with ToF-ERD was observed. We comment on the difficulty of correlating physical hydrogen measurements with the surface recombination properties.

Investigation of total ionizing dose effects on SOI FinFETs at elevated temperatures

Abstract The synergistic effects of total ionization dose (TID) and high temperature (HT) are investigated for n-type Silicon-on-Insulator (n-SOI) FinFETs. Experimental results reveal that both HT and TID will lead to a negative shift in threshold voltage (ΔV TH) in n-SOI FinFETs. While the ΔV TH induced by the synergistic effects is smaller than the sum of the ΔV TH shifts caused by TID and HT effects individually. Theoretical analysis suggests that the weaken degradation phenomenon can be attributed to the decrease of shallow-level electron traps in the HfO2 layer of stacked gate oxide. Based on this analysis, an analytical model is developed to simulate the synergistic effects of TID and HT, which has been validated by both experimental results and TCAD simulations. The proposed model enables accurate prediction of the potential distribution within the fin, allowing for precise calculation of V TH variations under HT and TID irradiation.

Elucidating the Morphology of Partially Lithiated Microscale Silicon Particles using Transmission Electron Microscopy

Abstract Partial lithiation of silicon active materials for lithium-ion batteries recently gained attention as a promising mitigation strategy for the degradation phenomena associated with the severe volume expansion upon the lithiation, particularly in the case of large, microscale silicon particles. It was suggested that this is caused by the formation of a stabilizing core-shell-like particle structure in the first cycles, consisting of a crystalline core and amorphous silicon shell. In this study, we investigated the microstructure of partially lithiated microscale silicon particles using transmission electron microscopy (TEM). When observed via TEM, the contrast difference in amorphous and crystalline silicon is utilized to reveal previously lithiated areas inside the silicon microparticle. We investigated the influence of lower cutoff potentials and amorphization progress in half-cells. We also examined the changes over prolonged cycling in full-cells with an NCA cathode after 12 and 243 cycles. Silicon particle pulverization was not observed for any sample, even though we found that substantial parts of the particles' insides had been lithiated. We suggest that the diffusion of Li along grain boundaries and stacking faults plays an essential part in the amorphization and cycling of microscale Si particles but does not lead to their cracking or pulverization.

A Bayesian-interference approach to quantify degradation parameters in a water-cooled variable speed screw compressor chiller

Abstract Variable-speed screw chillers can provide effective capacity modulations in commercial buildings to reduce energy consumption, match the load requirements, and contribute to lower equivalent carbon emissions. However, variable-speed operation can also yield to degradation phenomena inside the compressor. Assessing the real-time health status of chillers and detecting anomalies are important aspects to ensure long-term operation and improve reliability. To this end, an automated accelerated life test (ALT) procedure was developed and applied to a 513 kW (145.9 RT) water-cooled variable-speed screw chiller in a laboratory test facility to experimental assess performance degradation over time. After every 1,000 operating hours of ALT, steady-state performance tests at 30%, 50%, 75% and 100% load were conducted according to AHRI Standard 550/590. Additional operating conditions were included while conducting the tests to provide a more complete assessment of the degradation trends compared to the initially measured baseline. The experimental data set was then used to quantify the performance degradation based on the impact on the screw compressor operation. A Bayesian-inference identification approach has been developed to identify changes of sensitive parameters that statistically provide evidence for the likelihood of a performance degradation of the compressor. The information was used to implement the parameters in a dynamic model which was used to perform studies to predict the degradations of a chiller. The outcomes of this study help to improve the maintenance schedule of a compressor and even the whole chiller so that the system can be operated more economically and unplanned downtime can be minimized.

State of charge estimation method for lithium-ion batteries based on adaptive central difference particle filter with weight reconstruction

The particle filter (PF) has been widely used for state of charge (SOC) estimation. However, the particle degradation phenomenon will affect the estimation accuracy. In response to this issue, a state of charge estimation method for lithium-ion batteries based on adaptive central difference particle filter with weight reconstruction (ACDPF-WR) is designed in this paper. This method combines the preferred importance density function and the optimized resampling strategy. Firstly, the central difference Kalman filter (CDKF) is used to update the sampled particles to reduce the influence of particle degradation. Secondly, the Gaussian process regression (GPR) model of particles and weights is constructed by combining the offline learning experimental battery data set, and the GPR is used to generate the weight distribution of the particle filter. Then, an adaptive step size mechanism is introduced, which determines the optimal step size by calculating the mean square error of the weight distribution under different steps. Finally, the weight distribution generated by the central difference particle filter (CDPF) based on the optimal step size is combined with the typical resampling algorithm to select high-quality particles to achieve the optimal estimation. The adaptability and robustness of the algorithm are verified under Beijing Dynamic Stress Test (BJDST), US06 Highway Driving Schedule (US06), and Dynamic Stress Test (DST) conditions, and evaluated by mean absolute error (MAE) and root mean square error (RMSE) indicators. The average comparison results of the three working conditions show that the MAE of ACDPF-WR is 54.1 % higher than that of EPF and 24.3 % higher than that of CDPF, and the RMSE of ACDPF-WR is 64.6 % higher than that of EPF and 24.5 % higher than that of CDPF. The proposed algorithm achieves better performance and provides new insights and methods for the optimization and improvement of the battery management system.

Effect of sub‐coercive degradation on the local piezoelectric properties in lead zirconate titanate ceramics

AbstractLead zirconate titanate (PZT) is a widely recognized piezoelectric ceramic exhibiting excellent dielectric and ferroelectric properties over a wide range of temperature and frequency, making it desirable for applications such as capacitors, piezoelectric transducers, and actuators. Being subjected to repeated electrical loading in various applications, a progressive decrease in the functionality can happen, leading to device failure over time. Therefore, understanding degradation phenomena in all aspects is of importance to expand the lifespan of electronic devices. Despite of many studies focusing on the macroscopic properties of ferroelectrics related to degradation, such as switchable polarization, little is known about the change on local ferroelectric and piezoelectric properties and the domain structure induced by degradation. This paper reports the effect of sub‐coercive electrical cycling on local static and dynamic piezoelectric properties for PZT ceramic using piezoresponse force microscopy (PFM). The piezoelectric properties are probed along the three sample directions (x, y, z) to gain comprehensive insights into the local domain orientation throughout the bulk PZT sample which is then compared with microscopically measured piezoelectric coefficients. The PFM results are analyzed with respect to changes in domain orientation (depolarization) as well as to reduction on piezoelectric material response (degradation) to identify the origin of the degradation behavior. Our results directly show a strong depolarization effect in the direction of the applied electric field because of sub‐coercive cycling although it leads to small or even no degradation in directions perpendicular to the applied electric field. However, the latter is associated with a notable change in dynamic polarization switching properties which are strongly tied to the local domain structure. Our study shows that the origin of the degradation can be identified by analyzing the statistical change of local piezoelectric properties.

Perfluorinated sulfonic acid ionomer degradation after a combined chemical and mechanical accelerated stress test to evaluate membrane durability for polymer electrolyte fuel cells

Investigating the chemical and mechanical degradation phenomena of polymer electrolyte membranes (PEMs) is crucial, as they significantly influence the electrochemical performance and lifetime of fuel cell electric vehicles. For this, the combined use of chemical and mechanical accelerated stress test (AST) protocols has proven effective and reliable in evaluating PEMs durability within a relatively short period. However, it remains unclear whether the combined AST protocols exclusively affect PEMs durability, since the AST evaluation is performed not in the membrane states but in the membrane-electrode assembly (MEA) state. To address this question, a combined AST protocol consisting of a single cycle involving a chemical degradation phase followed by a mechanical degradation phase, was applied. The influence of the combined AST on both the membrane and electrodes was investigated using a variety of electrochemical evaluations conducted after each cycle. Additionally, the study includes changes in the physical characteristics of each MEA component.

Modelling of SiOx electrode degradation based on latent variables from 2D-SEM images

Si-based materials have gained attention as negative electrode materials for lithium-ion batteries. However, it is still difficult to model and predict their degradation phenomena using electrochemistry-based simulations because they undergo significant volume changes during charging and discharging, resulting in complex degradation phenomena such as pulverization of active materials, electrode delamination, and growth of solid electrolyte interphase (SEI) films. In this study, we present a comprehensive generative model using FIB-SEM images of pure SiOx anodes under various cycling conditions combined with principal component analysis (PCA), linear regression (LR), and Gaussian Process Regression (GPR) methods combined with electrochemistry-based simulation. The FIB-SEM images were converted to three-valued images after cropping and augmentation, and a PCA including 256 vectors of latent variables was thereby constructed. In addition, the LR and GP models were developed and compared using the time series data of the latent variables. The present model enables prediction of not only the capacity but also detailed information of the sample, including the structure of the active material and the area and discharge performances, via electrochemistry-based simulations.

Harnessing Extrinsic Dissipation to Enhance the Toughness of Composites and Composite Joints: A State-of-the-Art Review of Recent Advances.

Interfaces play a critical role in modern structures, where integrating multiple materials and components is essential to achieve specific functions. Enhancing the mechanical performance of these interfaces, particularly their resistance to delamination, is essential to enable extremely lightweight designs and improve energy efficiency. Improving toughness (or increasing energy dissipation during delamination) has traditionally involved modifying materials to navigate the well-known strength-toughness trade-off. However, a more effective strategy involves promoting non-local or extrinsic energy dissipation. This approach encompasses complex degradation phenomena that extend beyond the crack tip, such as long-range bridging, crack fragmentation, and ligamentformation. This work explores this innovative strategy within the arena of laminated structures, with a particular focus on fiber-reinforced polymers. This review highlights the substantial potential for improvement by presenting various strategies, from basic principles to proof-of-concept applications. This approach represents a significant design direction for integrating materials and structures, especially relevant in the emerging era of additive manufacturing. However, it also comes with new challenges in predictive modeling of such mechanisms at the structural scale, and here the latest development in this direction is highlighted. Through this perspective, greater durability and performance in advanced structural applications can beachieved.

Degradation evaluation on the mechanical properties of composite electrode through an integrated phase field and continuum simulation

The electrochemical degradation phenomena in lithium-ion batteries imply that the mechanical properties of a composite electrode may deteriorate during cycling, however, there are still lack of detail information on their direct correlations. Here, we proposed an integrated phase field-continuum simulation method to track the process of mechanical degradation. Based on scanning electron microscope images of a composite electrode, a representative volume element microstructural model was constructed and the damage evaluations caused by lithiation and delithiation were estimated though the phase-field method. Then a subsequent continuum mechanical model was performed on meso-structures with damage to evaluate their mechanical properties. The results show that damage primarily occurs during the initial cycle, and decreasing particle sizes and the cycling rate can effectively mitigate damage. This work bridges the relationship between the particle damage and mechanical properties of composite electrodes, and thus, provides an important insight on the stress evaluation and optimal design in service.

Evaluation of degradation phenomena in the electric potential distribution inside organic light-emitting diodes by electron holography

Understanding the intrinsic degradation processes of organic light-emitting diodes is necessary to improve their lifetimes. This intrinsic degradation is typically caused by carrier injection at the interface between the hole transport layer (HTL) and the emissive layer (EML). However, revealing the charge behavior in this local region with a high spatial resolution remains challenging. Thus, this study employed electron holography, a transmission electron microscopy (TEM) technique, to measure the nanometer scale potential distribution inside an OLED composed of N,N′-di-[(1-naphthyl)-N,N′-diphenyl]-(1,1′-biphenyl)-4,4′-diamine (α-NPD) and tris-(8-hydroxyquinoline)aluminum (Alq3) that was degraded via continuous voltage application. The α-NPD and Alq3 functioned as the HTL and EML, respectively. The degraded OLED was found to exhibit several potential distributions, depending on the local positions from which the TEM samples were lifted out of the same bulk sample. The distributions included (i) formation of a potential valley at the α-NPD/Alq3 interface, (ii) disappearance of electric fields within the organic layers, and (iii) similar distribution to original before degradation. We suggest that the degradation was caused by charge accumulation, cationization of Alq3, and local failures. Thus, this study revealed the influence of electric degradation at the nanometer scale because of charge injection to the α-NPD/Alq3 interface. Electron holographic degradation analysis near the HTL/EML interface is expected to aid in the development of design guidelines for preventing device degradation and thus extend device lifetime.

Long‐Term Estimation of SoH Using Cascaded LSTM‐RNN for Lithium Batteries Subjected to Aging and Accelerated Degradation

ABSTRACTAccurate estimation of state of health (SoH) of the battery over long‐term is a critical challenge for the battery management systems in electric vehicles. This is due to the challenges in accurately modeling the accelerated aging and degradation phenomena caused by diverse operating conditions of the battery. This paper presents a cascaded recurrent neural networks (RNN) with long short‐term memory (LSTM) to estimate the internal resistance and SoH, taking account of various abnormal operating conditions of the battery. A datasheet‐based degradation model of the battery is developed using fade equations. The training and validation data set for LSTM‐RNN are generated by subjecting the battery model to various factors that cause accelerated degradation, such as fast charging, varying operating temperatures, overutilization, and cell imbalance. The cascaded LSTM‐RNN is trained to estimate SoH only once after the completion of every charge–discharge cycle. The training error index parameters of the proposed SoH estimator are well within 1%, demonstrating the reliability and robustness of the estimator to diverse operating conditions of the battery.

Towards resilient pipeline infrastructure: lessons learned from failure analysis

Understanding the mechanisms of pipeline failures is crucial for identifying vulnerabilities in gas transmission pipelines and planning strategies to enhance the reliability and resilience of energy supply chains. Existing studies and the American Society of Mechanical Engineers’ (ASME) Code for Pressure Piping primarily focus on corrosion, recommending inspections every 10 years to prevent incidents due to this time-dependent threat. However, these guidelines do not provide comprehensive regulation on the likelihood of incidents due to other causes, especially non-time-dependent events (i.e. do not provide any indication of the inspection frequency or the most likely time for an incident to occur). This study adopts an innovative approach adopting machine learning, particularly artificial neural networks (ANNs), to analyse historical pipeline failure data from 1970 to 2023. By analysing records from the US Pipeline & Hazardous Materials Safety Administration, the model captures the complexity of various degradation phenomena, predicting failure years and hazard frequencies beyond corrosion. This innovative approach allows adopting more informed preventive measures and response strategies, offering deep insights into incident causes, consequences, and patterns. The results provide practical insights for maintenance planning, offering an estimation of periods when a pipeline may be more susceptible to incidents based on various factors. However, since all models inherently present uncertainties, both in the data and the modelling process, these estimates should be interpreted as probabilistic assessments. This study provides operators with a strategic framework to prescriptively address potential vulnerabilities, thereby promoting sustained operational integrity and minimising the occurrence of unexpected events throughout the service life of pipelines. By expanding the scope of risk assessment beyond corrosion, this study significantly advances the field of pipeline safety and reliability, setting a new standard for comprehensive incident prevention.

Solid-State Diffusion Bonding of Aluminum to Copper for Bimetallic Anode Fabrication.

The diffusion-bonding technique has been utilized to join various Al alloys (AA1060, AA2024, AA3003) to Cu for bimetallic anode application. This process aims to achieve robust metallic continuity to facilitate electron transfer, while carefully managing the growth of the intermetallic layer at the bonding interface. This control preserves the active volume of aluminum and prevents excessive brittleness of the anode. Optimization efforts have focused on different pressures, surface treatments of parent materials, and bonding parameters (temperature 450-500 °C and time 5-60 min). The optimal conditions identified include low bonding pressures (8 MPa), surface treatment involving polishing followed by chemical cleaning of the surfaces to be bonded, and energetic bonding conditions tailored to each specific aluminum alloy. Preliminary electrochemical characterization via cyclic voltammetry (CV) tests has demonstrated high reversibility intercalation/deintercalation reactions for up to seven cycles. The presence of the different alloying elements appears to contribute significantly to maintaining the high intercalation/deintercalation reaction reversibility without considerable modification of the reaction potentials. This effect may be attributed to alloying elements effectively reducing the overall alloy volume expansion, potentially forming highly reversible ternary/quaternary active phases, and creating a porous reaction layer on the exposed aluminum surface. These factors along with the influence of the Cu parent material collectively reduce the stress during volume expansion, which is the responsible phenomenon of the anode degradation in common Al anodes.

Mechanical properties and restoring force model of Squeezing Rub-type Particle Damper

The sliding effect of isolation bearings has been proven to effectively mitigate the seismic effects on large-span bridges. However, it also results in excessive relative displacement between the main girder and piers during earthquakes. In this study, a pioneering Squeezing Rub-type Particle Damper (SRPD) is developed to address this issue. In order to verify the damping characteristics of SRPDs and investigate the working principle of squeezing friction energy dissipation, five quasi-static tests were conducted on SRPDs using two particle damping materials with different compactness levels. In order to compare the energy dissipation performance, comparative tests were conducted on Non-Squeezing-type Particle Dampers (NSPDs) and SRPDs. Utilizing regression analysis, two skeletal curve models for SRPDs were proposed, alongside a detailed restoring force model that incorporates considerations for both the pinching effect and stiffness degradation phenomena observed during the loading and unloading phases. The experimental results demonstrate that the maximum damping force of SRPDs can reach 16 times that of NSPDs, and the energy dissipation of each loading cycle can reach 21.06 times that of NSPDs. SRPDs exhibits improved energy dissipation performance when using high-density blended quartz sand. After sand replenishment repairs,damping force and energy dissipation per cycle of SRPDs were significantly enhanced. The proposed restoring force models of SRPDs aligns well with the experimental curves, underscoring its efficacy in accurately characterizing the hysteresis performance of SRPDs.

Impact of bias stress and endurance switching on electrical characteristics of polycrystalline ZnO-TFTs with Al2O3 gate dielectric

Abstract This study experimentally investigates electrical characteristics and degradation phenomena in polycrystalline zinc oxide thin-film transistors (ZnO-TFTs). ZnO-TFTs with Al2O3 gate dielectric, Al-doped ZnO (AZO) source–drain contacts, and AZO gate electrode are fabricated using remote plasma-enhanced atomic layer deposition at a maximum process temperature of 190 °C. We employ positive bias stress (PBS), negative bias stress (NBS), and endurance cycling measurements to evaluate the ZnO-TFT performance and examine carrier dynamics at the channel-dielectric interface and at grain boundaries in the polycrystalline channel. DC transfer measurements yield a threshold voltage of −5.95 V, a field-effect mobility of 53.5 cm2/(V∙s), a subthreshold swing of 136 mV dec−1, and an on-/off-current ratio above 109. PBS and NBS measurements, analysed using stretched-exponential fitting, reveal the dynamics of carrier trapping and de-trapping between the channel layer and the gate insulator. Carrier de-trapping time is 88 s under NBS at −15 V, compared to 1856 s trapping time under PBS at +15 V. Endurance tests across 109 cycles assess switching characteristics and temporal changes in ZnO-TFTs, focusing on threshold voltage and field-effect mobility. The threshold voltage shift observed during endurance cycling is similar to that of NBS due to the contrast in carrier trapping/de-trapping time. A measured mobility hysteresis of 19% between the forward and reverse measurement directions suggests grain boundary effects mediated by the applied gate bias. These findings underscore the electrical resilience of polycrystalline ZnO-TFTs and the aptitude for 3D heterogeneous integration applications.

Current Challenges in Corrosion Research

Corrosion is a degradation phenomenon with huge economic consequences and severe security implications [...]

Innovative Materials for Lamination Encapsulation in Perovskite Solar Cells

AbstractPerovskite solar cells (PSCs), as the forefront of third‐generation solar technology, are distinguished by their cost‐effectiveness, high photovoltaic efficiency, and the flexibility of their bandgap tunability, positioning them as formidable contenders in the photovoltaic market. However, the stability of PSCs remains a significant barrier to their widespread commercialization. Lamination encapsulation is identified as a pivotal intervention to enhance the durability of PSCs under external environmental stress. This review initiates with an in‐depth exploration of the degradation phenomena in PSCs, triggered by environmental stressors such as water, oxygen, light, and heat. This analysis lays bare the degradation mechanisms, thereby highlighting the specific demands for effective encapsulation materials. Subsequently, the review presents a systematic discourse on the latest developments in encapsulation materials, dissecting their molecular structures and linking these to their physical properties and performance in encapsulation applications. The narrative concludes by charting potential future research pathways intended to refine and enhance the encapsulation performance of PSCs, offering several routes for overcoming current limitations and propelling PSCs toward their full commercial potential.

Improved Understanding of PEMFC Stack Durability Testing through Comprehensive In-Situ and Ex-Situ Characterization Techniques

Durability testing of Proton Exchange Membrane Fuel Cells for mobile applications remains a critical challenge. While most academic studies focus on single-cell testing, there are only few publications on stack testing of technical relevant sizes. This study utilizes comprehensive characterization techniques to enhance understanding of PEMFC stack durability, aiming to meet the currently targeted durability targets. A 5,500-hour long-term test, based on the Auto Stack Industry (ASI) test protocol, was performed on a 7-cell short stack of 240 cm² active area. In-situ techniques, such as spatially resolved current density measurement, cyclic voltammetry, and electrochemical impedance spectroscopy, provided real-time degradation insights, while ex-situ methods, including FIB-SEM analysis, infrared thermography or contact angle measurements provided information on material degradation mechanisms. Membrane degradation was found to be negligible. Slight thinning of the cathode indicates carbon corrosion of the catalyst support. Catalyst aging was observed in the form of Pt band formation and Co leaching. Gas diffusion layers showed hydrophobicity loss, and increased resistance in bipolar plates contributed to reduced performance. Our findings demonstrate that PEMFC stacks operated under automotive drive cycle protocols can meet the actual targeted durability objectives. Moreover, it illustrates the degradation phenomena that occur under realistic operating conditions and modes, and how they evolve over the duration of thousands of hours of operation.

Improved Understanding of PEMFC Stack Durability Testing through Comprehensive In-Situ and Ex-Situ Characterization Techniques

Durability testing of Proton Exchange Membrane Fuel Cells for mobile applications remains a critical challenge. While most academic studies focus on single-cell testing, there are only few publications on stack testing of technical relevant sizes. This study utilizes comprehensive characterization techniques to enhance understanding of PEMFC stack durability, aiming to meet the currently targeted durability targets. A 5,500-hour long-term test, based on the Auto Stack Industry (ASI) test protocol, was performed on a 7-cell short stack of 240 cm² active area. In-situ techniques, such as spatially resolved current density measurement, cyclic voltammetry, and electrochemical impedance spectroscopy, provided real-time degradation insights, while ex-situ methods, including FIB-SEM analysis, infrared thermography or contact angle measurements provided information on material degradation mechanisms. Membrane degradation was found to be negligible. Slight thinning of the cathode indicates carbon corrosion of the catalyst support. Catalyst aging was observed in the form of Pt band formation and Co leaching. Gas diffusion layers showed hydrophobicity loss, and increased resistance in bipolar plates contributed to reduced performance. Our findings demonstrate that PEMFC stacks operated under automotive drive cycle protocols can meet the actual targeted durability objectives. Moreover, it illustrates the degradation phenomena that occur under realistic operating conditions and modes, and how they evolve over the duration of thousands of hours of operation.