Stress Test Conditions Research Articles

An accurate state-of-charge estimation of lithium-ion batteries based on improved particle swarm optimization-adaptive square root cubature kalman filter

The state of charge (SOC) of lithium-ion batteries (LIBs) is regarded as the fundamental parameter of the battery management system (BMS). In this paper, a parameter optimization method for mobile estimation windows based on particle swarm optimization-adaptive square root cubature Kalman filter (PSO-ASRCKF) is established to improve the SOC estimation ability and accuracy of LIBs. The filtering algorithm parameters are optimized to achieve high-precision SOC estimation. An improved ASRCKF with the PSO algorithm to optimize the moving estimation window is constructed to obtain the best adaptive window value. Different temperatures and initial SOC values are used to verify the proposed method under dynamic stress test (DST) and other conditions. The results show that the relative error is mainly distributed within 0.5 % when the SOC is stable. In addition, robustness and adaptability are verified with the root mean square error (RMSE) and the mean absolute error (MAE) values of 0.0019 and 0.0017, respectively, under the DST working condition. The experimental results show that the proposed method can achieve accurate SOC estimation under different temperatures, operating conditions, and initial SOC values.

HPTLC – densitometric method of analysis for estimation of efonidipine hydrochloride and telmisartan used in treatment of hypertension

Precise, accurate, and sensitive high performance thin layer chromatographic method has been developed and validated for simultaneous determination of efonidipine hydrochloride (EFD) and telmisartan (TEL) in a tablet dosage form which is used in treatment of hypertension. The proposed method used aluminum plates pre-coated with silica gel 60 F254 as a stationary phase and n-butanol: toluene: acetic acid (3:7:0.2, v/v/v) as a mobile phase for separation purpose. Compact spots of TEL and EFD were obtained at Rf 0.73 and 0.37, respectively. Densitometric detection was carried out at 299 nm in UV. Linear responses were shown by the detector over the range of 200–1200 ng/band for both drugs. The proposed method was validated as per ICH guidelines. The method was successfully applied for estimation of both drugs in tablet formulations. Forced degradation study was carried and efonidipine was found to be susceptible to base hydrolysis and oxidative stress degradation while TEL was stable in acid-base hydrolysis, oxidative stress, dry heat and photo stability testing conditions. The developed method can be used for the analysis of stability samples. Greenness assessment of developed method was performed using AGREE software. The method was found to be greener having greenness score of 0.69.

Online state of charge estimation of LiFePO4 battery based on EKF-AUKF algorithm with reference compensation for estimation results

The state of charge(SOC) is an important index in Battery Management System(BMS) for smart grids and electric vehicles, whose accuracy is affected by model and sensor errors. In this paper, an online SOC estimation method based on EKF-AUKF algorithm with reference compensation for estimation results is proposed. Firstly, a joint estimation method based on extended Kalman filter(EKF) and adaptive unscented Kalman filter(AUKF) algorithm is adopted to estimate SOC under Beijing bus dynamic stress test(BBDST) condition. The result shows that the estimation error is within 2 %. Secondly, the characteristics of EKF-AUKF algorithm under voltage and current sampling errors are analyzed over the whole SOC range. The results indicate that voltage measurement error increases SOC estimation error. Then, an online reference is built by calculating the sum of the estimation result of ampere-hour counting(AHC) method and constant deviation, and then the difference between the estimation result of EKF-AUKF algorithm and online reference can be obtained. The absolute value of the difference is used to compare with limit deviation value and compensate the SOC of EKF-AUKF method by different compensation coefficients. Finally, the effectiveness of the proposed method is verified under different operating conditions. The experimental results show that the proposed method can greatly improve the SOC estimation accuracy under large voltage error.

Habitual Caffeine Use Is Associated With Heightened Cortisol Reactivity to Lab-Based Stress in Two Samples.

Habitual caffeine consumption protects against depression but through unclear mechanisms. Although habitual caffeine use predicts cortisol release in response to other acute stressors (e.g., exercise), this is less examined with lab-based psychosocial stress in healthy adults. Furthermore, caffeine-induced cortisol increases may mask theory-predicted cortisol blunting to robust stress in people with elevated depression risk. In two samples, we tested whether acute (same-day) and habitual caffeine use would predict greater cortisol reactivity to lab-based stress, and whether caffeine would "mask" the effect of a depression risk factor, trait rumination, on blunted cortisol reactivity. In sample 1, N = 128 emerging adults completed one of three Trier Social Stress Test conditions: nonevaluative control, ambiguously evaluative intermediate, or explicit negative evaluative. In sample 2, N = 148 emerging adults completed either a control or negative evaluative condition. In both samples, multilevel growth curve modeling indicated that habitual caffeine use ( t = -1.99, p = .048; t = -2.73, p = .007, samples 1 and 2, respectively) but not acute caffeine use predicted heightened cortisol reactivity as a function of condition. In sample 1, the relationship between condition, rumination, and blunted cortisol was evident only in caffeine nonusers, which differed from users ( t = 2.82, p = .005), but in sample 2, the predicted blunting pattern was evident regardless of caffeine use. The results provide evidence that habitual caffeine use is associated with greater cortisol release under psychosocial lab-based stress and may mask the influence of psychosocial variables; future research should examine whether habitual caffeine-induced cortisol release has behaviorally activating effects that protect against depression.

Lithium Battery SoC Estimation Based on Improved Iterated Extended Kalman Filter

With the application of lithium batteries more and more widely, in order to accurately estimate the state of charge (SoC) of the battery, this paper uses the iterated extended Kalman filter (IEKF) algorithm to estimate the SoC. The Levenberg–Marquardt (LM) method is used to optimize the error covariance matrix of IKEF. Based on the hybrid pulse power characteristics experiment, a second-order Thevenin model with variable parameters is established on the MATLAB platform. The experimental results show that the proposed model is effective under the constant current discharge condition, the Federal Urban Driving Schedule (FUDS) condition, and the Beijing dynamic stress test (BJDST) condition. The results show that the simulation error of the improved LM-IEKF algorithm is less than 2% under different working conditions, which is lower than that of the IKEF algorithm. The improved algorithm has a fast convergence speed to the true value, and it has a good estimation accuracy in the case of large changes in external input current. Additionally, the fluctuation of error is relatively stable, which proves the reliability of the algorithm.

Determination of Mesalamine in Bulk and Suppository Dosage Forms through the Development and Validation of Stability- indicating RP-HPLC Method

Background: In the current study, a simple and cost-effective stability-indicating RP-HPLC method was developed and validated to estimate the mesalamine from both bulk and pharmaceutical dosage forms. Methods: An isocratic HPLC method using a reverse phase HiQSilC18 column (250 x 4.6 mm, 5μm) and a mobile phase methanol: ammonium acetate buffer (90:10 v/v) were employed as the mobile phase with a flow rate of 1 mL/min at 25°C. Detection was carried out at 305 nm, and the injection volume was 20μl. The developed method was validated as per ICH Q2 guidelines. Mesalamine has been subjected to various stress testing conditions, such as hydrolysis of acid and base, thermal degradation, oxidation, and photolysis. Also, methods have been validated with regard to linearity, accuracy, precision, and robustness. Results: The RT of mesalamine was determined to be 3.550 min ± 0.024 minutes, providing a reliable marker for its identification. The method was found to be linear between 5-30 μg/mL concentration with (R²) of 0.994. This demonstrated the method's ability to measure varying concentrations of mesalamine accurately. Additionally, the percentage recovery of mesalamine was approximately 100%, confirming the accuracy of the developed method. The parameters for system suitability have also been found to be within acceptable limits. Force degradation studies reinforced the method's selectivity and sensitivity in detecting mesalamine under various degradation scenarios. Notably, mesalamine significantly degraded in an acidic environment. Conclusion: In conclusion, our proposed RP-HPLC method provides a sensitive, accurate, and precise means of analyzing mesalamine in both bulk and pharmaceutical dosage forms.

Behavior of Reinforced Lightweight Concrete Slab with Initial Cracks

The flexural behavior of lightweight concrete two-way slabs repaired or strengthened with externally bonded carbon fiber-reinforced polymer (CFRP) sheets is the subject of this study. The experiment included five reinforced lightweight concrete slab specimens with dimensions of 1000 mm in length, 1000 mm in width, and 120 mm in thickness. Tested one specimen without any strengthening and reinforced another specimen with a single layer of CFRP. The other specimens were repaired with a single layer of CFRP, applying damage ratios of 50%, 60%, or 70% of the ultimate load. Intentionally designed each slab to collapse under bending forces and maintained comparable dimensions. According to the experiment results, changing the degree of damage from 70% to 50% increases the ultimate load capacity by about 17.7%, and the ultimate deflection decreases by about 31.4%. CFRPs have the potential to fix structural damage under static stress testing conditions. However, it is essential to make sure that they stick well to surfaces that do not have suitable geometric properties or have been deformed. CFRP sheets effectively repaired the specimens, increasing the failure stress of the reinforced concrete slabs and preventing the spread of cracks.

Research on SOP Estimation Based on SOC Constraints under Static Operating Conditions

In a battery management system (BMS), accurate estimation of system operating power (SOP) is essential to ensure battery performance and extend service life. In this paper, an SOP estimation method based on open circuit voltage (OCV), state of charge (SOC) and battery current is studied. By analyzing the battery data under dynamic stress test (DST) conditions, the estimated value of continuous peak charge and discharge current is calculated, and the corresponding continuous peak charge and discharge power is estimated accordingly. Comparing the estimated charging and discharging power with the experimental value, the results show that the new algorithm can significantly improve the estimation accuracy of SOP. It not only improves the accuracy of SOP estimates, but also helps to optimize BMS, thereby improving the overall performance and service life of the power battery.

Evaluation of Sabkha Soil Bearing Capacity by Plate Load Test in Al Muthanna Province

For projects such as airports and road paving, an appropriate foundation must be developed in Sabkha soil, which requires a trustworthy assessment of soil-bearing capacity. When heavy traffic is expected to result in substantial wheel loads throughout pavement construction and maintenance, the plate load test helps solve these issues with subgrade and sub-base layer design. This work aims to investigate and assess the geotechnical behavior regarding soil strata from one area in southern Iraq: Sabkha. Conversely, a comparison is made between subgrade response modulus and soil-bearing capacity determined by field plate load tests and traditional laboratory investigations. The data demonstrated that the values related to Ks in the consolidation test rose as a ratio of pre-consolidation pressure of 45% and dramatically dropped with an increase in applied stress that is vertically applied below pre-consolidation stress. Furthermore, PLT data demonstrated that when pressure was applied, the modulus of the subgrade reaction did not follow a regular pattern. At the beginning of the loaded stage, after the pre-consolidation stress, Ks values at testing points 2 and 3 were high. After that, Ks abruptly decreased, particularly when the applied pressure surpassed the pre-consolidation stress before being constant again. A detailed discussion is given on the effects of stress distribution and test conditions on the elasticity stress curve's shape and the subgrade reaction modulus.

A novel least squares support vector machine-particle filter algorithm to estimate the state of energy of lithium-ion battery under a wide temperature range

The state of energy (SOE) is a key indicator for lithium-ion battery management systems (BMS). Based on the second-order resistance-capacitance equivalent circuit model and online parameter identification using the dynamic weights particle swarm optimization (DWPSO) method, a least-squares support vector machine-particle filter (LSSVM-PF) algorithm is proposed to construct a particle filter to estimate the SOE of a lithium-ion battery, and then transfer the resulting estimation error together with the experimentally measured voltage and current values to a trained LSSVM model, and use the LSSVM model to optimize the SOE estimates obtained by the PF algorithm twice to improve the accuracy of SOE estimation for lithium-ion batteries. The feasibility of the proposed algorithm is verified using two complex operating conditions and at three different temperatures. The validation results show that the maximum error of SOE estimation of the proposed algorithm is 0.0284 for a wide temperature range under Beijing Bus Dynamic Stress Test (BBDST) condition, and 0.0226 for a wide temperature range under Dynamic Stress Test (DST) condition. The proposed algorithm significantly improves the accuracy of SOE estimation and provides a reference for fundamental applications of lithium-ion batteries.

One‐Pot Synthesis of Carbon‐Supported Pd Nanoparticles with Ni and Carbon Matrix Protection for Durable Alkaline Hydrogen Oxidation Reaction

Protecting nanoparticles with a carbon matrix can enhance the durability of the catalysts in alkaline fuel cells (AFC) and is well‐documented. While others have tried complex syntheses to produce small nanoparticle catalysts, in this work, in order to scale‐up batches of 15 g or more, carbon‐cap (or carbon‐coating) protected Vulcan XC72‐supported Pd‐Ni (1‐2) nanoparticles (Pd‐Niacc/C) were successfully synthesized via a one‐step dry‐synthesis process. This catalyst was compared with a commercial Pd‐Ni/Vulcan XC72 material (PdNi/C, Premetek) in terms of hydrogen oxidation reaction (HOR) activity and stability. To produce less ordered carbon caps (versus graphite/graphene), a low‐temperature heat‐treatment (below 500°C) was used, resulting in Pd‐Niacc/C of unique electrochemical properties: easily electrochemically activated, this catalyst outperforms PdNi/C for alkaline HOR and proves more durable under highly oxidizing accelerated stress test (AST) conditions. Identical location transmission electron microscopy (ILTEM), X‐ray photoelectron spectroscopy (XPS) and rotating disk electrode (RDE) measurements demonstrate how the Ni‐rich surface plays an important role in HOR activity for both PdNi/C and PdNiacc/C and that the protective carbon‐coating of the latter ensures better durability of performance and better resistance to materials degradation.

Battery multi-time scale fractional-order modeling method for state of charge estimation adaptive to full parameters updating

The fractional-order theory has been successfully applied to battery modeling and state of charge (SOC) estimation thanks to the rapid development of smart energy storage and electric vehicles. The fractional-order model (FOM) has high nonlinearity, which makes it difficult to identify the parameters of the FOM, especially the online identification of the order. Aiming at the problem of parameter identification and SOC estimation of the FOM of battery, a multi-time scale fractional-order modeling method is proposed in this paper. Then, a multi-time scale parameter identification strategy based on feature separation is proposed, and two sub-filters are used to complete the online identification of parameters. Finally, a fractional-order multi-innovation unscented Kalman filtering (FO-MI-UKF) algorithm is proposed for SOC estimation to utilize the value of historical information better. Under dynamic stress test (DST) and Beijing bus dynamic stress test conditions (BBDST), compared with the single-time scale parameter identification algorithm and the single-innovation SOC estimation algorithm, the root mean square error of the estimation results is reduced by 13.3 % and 8.7 %, respectively. The experimental results verify the effectiveness of the modeling method and provide a new idea for fractional-order modeling.

A specific chiral HPLC method for lifitegrast and determination of enantiomeric impurity in drug substance, ophthalmic product and stressed samples

Lifitegrast is a lymphocyte function-associated antigen-1 (LFA-1) antagonist used to treat the indications and symptoms associated with dry eye disease (DED), one of the most common ocular surface diseases. Lifitegrast has a chiral center, and the S-enantiomer (S-Lif) is responsible for the therapeutic effects, while the R-enantiomer (R-Lif) lacks efficacy in the treatment of DED. Lifitegrast ophthalmic solution containing 5% lifitegrast was approved by the United States Food and Drug Administration (FDA) in July 2016 for the treatment of DED in patients 17 years of age and older. The objective of this study was to develop a chiral HPLC method for the determination of the enantiomeric impurity of lifitegrast in the drug substance and in the ophthalmic product. In addition, we aimed to investigate the effect of stress and stability conditions on the enantiomeric purity of lifitegrast in both drug substance and ophthalmic solution. During the method development studies, four known lifitegrast impurities (Lif. Imp. A-D) and stressed lifitegrast samples were injected to ensure the specificity of the developed method. The enantiomers of lifitegrast are well separated with a resolution of higher than 4.0. They are also well separated from the peaks of the diluent, impurities, and the placebo used to prepare the ophthalmic solution without interference in 20 min. Chiral separation was achieved using a Chiralpak AD-H column (250 × 4.6 mm, 5.0 μm) at 40 °C with a mobile phase consisting of a mixture of n-hexane, 2-propanol, and formic acid (500:500:2, v/v/v) at a flow rate of 1.0 mL/min and a detection wavelength of 260 nm. Methanol was used as the diluent, and the drug substance solution was found to be stable for 48 h at 15 °C. The optimized chiral HPLC method for lifitegrast was validated according to ICH Q2, and the calibration curves showed excellent linearity for R-Lif (0.0369 – 1.816 µg/mL). This is the first stability-indicating, specific / selective, sensitive, linear, precise, accurate, and robust chiral HPLC method for the determination of R-Lif in S-Lif. The amount of enantiomeric impurity R-Lif in S-Lif increased under all stress and photostability test conditions without exceeding the acceptable impurity limit, with the most significant increase observed at elevated temperatures (105 °C) for both the drug substance in powder form and the ophthalmic drug solution.

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

AbstractState of charge (SOC) is a key state variable in lithium‑ion battery management system. The battery model and estimation algorithm are important factors that affect the accuracy of SOC estimation. In this paper, the optimization battery model is created by optimizing the hybrid power pulse characteristic (HPPC) parameter combination through orthogonal analysis. The simulation results demonstrate that optimizing the HPPC parameter combinations can improve battery modeling accuracy. Then, an extended Kalman particle filter (EKPF) algorithm is proposed by using the extended Kalman filter (EKF) algorithm as the density function of the particle filter (PF) algorithm. The EKPF algorithm is verified under the dynamic stress test and Beijing bus dynamic stress test conditions, the root mean absolute errors and root mean square errors in all cases are less than 1.5%. The experimental results show that the EKPF algorithm can combine the advantages of EKF and PF to estimate lithium‐ion battery SOC accurately.

Separation and quantification of organic‐related impurities of anti‐histamine drug hydroxyzine in pharmaceutical dosage forms using stability‐indicating high‐performance liquid chromatography, liquid chromatography‐mass spectrometry, and high‐resolution mass spectrometry techniques

AbstractA simple and robust high‐performance liquid chromatography (HPLC) method was developed for organic impurities of hydroxyzine hydrochloride in pharmaceuticals. The developed method was designed to estimate all organic impurities of hydroxyzine. The HPLC separation was achieved using C18 column (150 × 3.9 mm, 5 μm) along with a binary gradient consisting of mobile phases A (0.1%, trifluoroacetic acid in purified water) and B (0.05%, trifluoroacetic acid in acetonitrile), a flow rate of 0.7–mL/min, a column temperature of 30°C and a sample temperature of 25°C. The detection wavelength used was 230 nm for the estimation of impurity‐A, impurity‐B, and all unspecified impurities and degradation products, whereas impurity‐C was quantitated using 254 nm. The stability‐indicating property of the developed HPLC technique was assessed using stress testing conditions of hydrolysis, oxidation, thermal, photo‐light, and humidity. The validation study was performed for the limit of detection and limit of quantification, linearity, and recoveries were 0.03%, 0.05%, and 0.1132–2.9920 μg/mL (R2 > 0.999), and 84.09%–109.74%, respectively. The proposed method is highly suitable for the determination of assay, organic impurities, and degradation products of the hydroxyzine. The chemical structure of degradation product 1 (hydroxyzine N‐Oxide) and degradation product 2 (O‐Acetyl hydroxyzine) were identified with the supporting data of LC‐mass spectrometry (LC‐MS) and high‐resolution MS.

Smartphone ECG Based Successful Diagnosis of WPW Syndrome Under Both Resting and Stress Test Conditions: A Case Report

Background: Wolff-Parkinson-White (WPW) syndrome arises from the presence of an accessory pathway in the heart, disrupting normal electrical conduction between the atria and ventricles. Diagnosis via electrocardiography typically reveals characteristic features such as Delta waves, shortened PR intervals, and RR variabilities. Case Summary: The authors present the case of a 23-year-old male with a history of tobacco and alcohol use, exhibiting electrocardiographic manifestations consistent with WPW syndrome. Employing a Smartphone-based 12-lead ECG and bicycle ergometer, additional testing under resting and stressed conditions revealed a spectrum of abnormalities including T-wave inversions, tachyarrhythmias, conduction blocks, ST depressions, shortened PR intervals, and persistent Delta waves. Despite the absence of symptoms, a stress test achieving 10 METS over 5 minutes demonstrated the potential for ventricular tachycardia. Discussion: Following evaluation by a cardiologist, a watchful waiting approach was recommended, with no pharmacological intervention prescribed. This report underscores the utility of smartphone ECG technology in managing WPW syndrome, offering insights into dynamic cardiac responses during stress and informing clinical decision-making. Regular follow-up ECG assessments at six-month intervals were advised to monitor for emerging symptoms. The importance of prompt consultation with a cardiologist upon symptom onset cannot be overstated, given the inherent risk of life-threatening arrhythmias associated with WPW syndrome.

Microbiological quality and efficacy of preservatives in marigold-based skin care products

<p>The microbiological stability of cosmetic products is crucial, especially in products with high water content, such as creams. Therefore, preservatives are used in order to protect consumers from harmful pathogens that would otherwise invade the cosmetics. Despite their function, the addition of preservatives can be considered controversial in the cosmetics industry. Parabens are frequently used synthetic preservatives in various industries. According to regulatory directives concerning cosmetics (Cosmetic Directive by the European Commission) usage of some parabens (methylparaben, propylparaben, butylparaben, and ethylparaben) is safe and permitted in allowed concentrations. On the other hand, the European Commission prohibited the use of isopropylparaben, isobutylparaben, phenylparaben, benzylparaben and pentylparaben. Therefore, a comprehensive stability study was conducted to evaluate the influence of paraben-based preservative (Gujsol-1<sup>®</sup>, INCI name: Phenoxyethanol, Methylparaben, Ethylparaben, Propylparaben, Butylparaben) and potassium sorbate in order to preserve plant extracts-based skin-care products, Day and Night creams with marigold extract. Previously, mentioned skin-care products were preserved with the preservative Dekaben C<sup>®</sup>, which contained paraben mixture with banned isobutylparaben. All tested formulations showed favorable texture and sensory characteristics, desirable mild acidic pH values, satisfactory physical stability and appropriate microbiological quality at the initial point, as well as after storage at elevated temperature or at cyclic stress test conditions and at room temperature during two years. In addition, both preservatives significantly reduced the number of inoculated microorganisms during the challenge test. It can be concluded that potassium sorbate in plant-based creams could be an efficient alternative to paraben-based preservatives.</p>

State-of-charge estimation of lithium-ion battery based on second order resistor-capacitance circuit-PSO-TCN model

Accurate state-of-charge (SOC) estimation of lithium-ion battery is directly related to the reliability, performance, and safety of the battery. In this work, the second order resistor-capacitance (RC) circuit is equivalent to the battery model and the particle swarm optimization (PSO) algorithm is employed for achieving accurate identification of the parameters of circuit model under dynamic stress test (DST) conditions. Furthermore, the values of open circuit voltage (OCV) obtained from the identification results are input into the temporal convolutional network instead of the terminal voltages, and then the SOC of the Li-ion battery is estimated by directly learning the mapping relationship of OCV-SOC curves, which further improves the estimation accuracy and robustness of the proposed method. Finally, the SOC estimation is validated with the public dataset of LiFePO4 batteries under all driving conditions at different temperature and compared with the individual TCN method. Results show that the SOC estimation of the second order resistor-capacitance circuit-PSO-TCN model is optimal with a root mean square error (RMSE) and maximum error (MAXE) less than 1.8% and 7.65%, respectively.

Accelerated stress tests for Pt/C electrocatalysts: An approach to understanding the degradation mechanisms

The degradation of the nanostructured platinum-based electrocatalysts during their operation poses a major problem for the performance and durability of PEMFCs and devices based on them. Therefore, the methodological aspects of research related to the quantitative assessment of the materials’ degradation as well as the mechanism of the processes causing it are gaining increasing attention. The degradation processes of the same Pt/C catalyst containing the nanoparticles of similar size uniformly distributed over the surface of the carbon support were studied using eight relevant protocols of the accelerated stress testing. Special attention was paid to electron microscopy examination of the catalyst’s microstructure before and after stress tests as well as to determination of the electrochemically active surface area and the activity of the catalyst in the ORR after the stress testing. We also studied the influence of the atmosphere, in which testing was performed, as well as the effect of the electrode rotation on the degradation rate. The results of the study carried out demonstrate the features of the catalyst’s degradation in different modes and facilitate the choice of optimal protocols and stress testing conditions.

Unveiling Local Aging Patterns Following Accelerated Stress Testing of High-Performance Polymer Electrolyte Fuel Cells.

This study presents an in-depth analysis of heterogeneous aging patterns in membrane electrode assemblies (MEAs) subjected to diverse accelerated stress test (AST) conditions, simulating carbon corrosion (CC AST) and Pt particle size growth in fully humidified (Pt AST-Wet) and underhumidified (Pt AST-Dry) H2/N2 atmospheres. Multimodal characterization techniques are used to focus on heterogeneous aging patterns, primarily examining the variations in current distributions and Pt particle size maps. The findings reveal distinct characteristics of current distributions for all the AST cases, with substantial changes and strong current gradients in the CC AST case, indicative of severe performance degradation. Notably, despite significant differences in Pt particle size growth at the end-of-life (EOL), the Pt AST-Wet and Pt AST-Dry cases show minor changes in spatial current distributions. Moreover, a preferential growth of Pt particles under serpentine flow field bends in the Pt AST-Wet case is observed for the first time. This study provides crucial insights into the role of mass transport properties in shaping fuel cell performance, and highlights the need to consider factors beyond electrochemically-active surface area (ECSA) when assessing fuel cell durability.