Search Results (32)

Proton exchange membrane fuel cell (PEMFC) fault diagnosis faces two critical limitations: conventional offline methods lack real-time predictive capability, while existing prediction approaches are confined to single fault types. To address these gaps, this study proposes an online multi-fault prediction framework integrating three novel contributions: (1) a sensor fusion strategy leveraging existing thermal/electrochemical measurements (voltage, current, temperature, humidity, and pressure) without requiring embedded stack sensors; (2) a real-time sliding window mechanism enabling dynamic prediction updates every 1 s under variable load conditions; and (3) a modified CNN-based Bi-LSTM parallel model with attention mechanism (ConvBLSTM-PMwA) architecture featuring multi-input multi-output (MIMO) capability for simultaneous flooding/air-starvation detection. Through comparative analysis of different neural architectures using experimental datasets, the optimized ConvBLSTM-PMwA achieved 96.49% accuracy in predicting dual faults 64.63 s pre-occurrence, outperforming conventional LSTM models in both temporal resolution and long-term forecast reliability. Full article

Anadromous migration toward riverine tributaries is often challenged by altered environmental cues, food scarcity, and energy demands, sometimes at the expense of life itself. Tenualosa ilisha (Clupeiformes: Dorosomatidae), the national fish of Bangladesh, an anadromous shad, offers a model for understanding the molecular mechanisms of migration. To this end, we present a chromosome-level genome of T. ilisha and compare its transcriptomic imprints from muscle and liver across environments to trace the physiological shifts driving the migration. We observed rapid expansion of gene families to facilitate efficient signaling and osmotic balance, as well as a substantial selection pressure in metabolism regulatory genes, potentially relevant to a highly anadromous fish. We detected 1298 and 252 differentially expressed transcripts between sea and freshwater in the liver and muscle of T. ilisha, respectively, reflecting habitat and organ-specific adaptations. Co-expression analysis led us to hypothesize that the strength required for breeding migration toward upstream rivers is fueled by muscle protein catabolism forming ubiquitin-proteasomal complexes. In the liver, we observed a group of genes promoting fatty acid (FA) synthesis significantly in the riverine habitat. Regulation of FADS2 and ELOVL2 in the river reasoned the natural abundance of LC-PUFAs with better energy utilization in T. ilisha. Moreover, active gluconeogenesis and reduced insulin signaling in the liver are possibly linked to glucose homeostasis, potentially induced by prolonged starvation during migration. These genomic resources will accelerate the future evolutionary and functional genomics studies of T. ilisha. Full article

The measurement of hydrogen concentration in fuel cell systems is an important prerequisite for the development of a control strategy to enhance system performance, reduce purge losses and minimize fuel cell aging effects. In this perspective paper, the working principles of hydrogen sensors are analyzed and their requirements for hydrogen control in fuel cell systems are critically discussed. The wide measurement range, absence of oxygen, high humidity and limited space turn out to be most limiting. A perspective on the development of hydrogen sensors based on palladium as a gas-sensitive metal and based on the organic magnetic field effect in organic light-emitting devices is presented. The design of a test chamber, where the sensor response can easily be analyzed under fuel cell-like conditions is proposed. This allows the generation of practical knowledge for further sensor development. The presented sensors could be integrated into the end plate to measure the hydrogen concentration at the anode in- and outlet. Further miniaturization is necessary to integrate them into the flow field of the fuel cell to avoid fuel starvation in each single cell. Compressed sensing methods are used for more efficient data analysis. By using a dynamical sensor model, control algorithms are applied with high frequency to control the hydrogen concentration, the purge process, and the recirculation pump. Full article

According to the latest World Health Organization (WHO) report, an estimated 10.6 million people were diagnosed with tuberculosis (TB) in 2022, and 1.30 million died. A major concern is the emergence of multi-drug-resistant (MDR) and extensively drug-resistant (XDR) strains, fueled by the length of anti-TB treatment and HIV comorbidity. Innovative anti-TB agents acting with new modes of action are the only solution to counteract the spread of resistant infections. To escape starvation and survive inside macrophages, Mtb has evolved to become independent of the host by synthesizing its own amino acids. Therefore, targeting amino acid biosynthesis could subvert the ability of the mycobacterium to evade the host immune system, providing innovative avenues for drug discovery. The aim of this review is to give an overview of the most recent progress in the discovery of amino acid biosynthesis inhibitors. Among the hits discovered over the past five years, tryptophan (Trp) inhibitors stand out as the most advanced and have significantly contributed to demonstrating the feasibility of this approach for future TB drug discovery. Future efforts should be directed at prioritizing the chemical optimization of these hits to enrich the TB drug pipeline with high-quality leads. Full article

Hydrogen fuel-cell systems are one of the alternatives for the decarbonization of the transportation sector. In such systems, the usage of O${}_2$-enriched air has the potential to improve fuel cell performance as well as to reduce degradation phenomena linked to local O${}_2$ starvation. However, the production of an O${}_2$-enriched air stream implies energy consumption that needs to be evaluated in the overall system efficiency. In this study, the potential of a system including polymeric membranes for O${}_2$-N${}_2$ separation to produce O${}_2$-enriched air was evaluated theoretically. First, the balance of plant, including the O${}_2$-N${}_2$ separation membrane and a two-stage boosting system, was considered. Two sources of energy recovery were identified: a high-pressure H${}_2$ stream and retentate flow (N${}_2$-rich) at the outlet of the separation membrane. Then, the efficiency of the system was evaluated for different levels of O${}_2$ enrichment, with sensitivities to the main operational and design parameters, i.e., cathode excess O${}_2$ ratio, turbomachinery efficiency, essure ratios. The results show the potential for an O${}_2$-enriched system if the energy recovered reaches approximately 25% of the additional power consumption induced by the separation membrane. Full article

The hydrogen fuel cell is a quite promising green device, which could be applied in extensive fields. However, as a complex nonlinear system involving a number of subsystems, the fuel cell system requires multiple variables to be effectively controlled. Oxygen excess ratio (OER) is the key indicator to be controlled to avoid oxygen starvation, which may result in severe performance degradation and life shortage of the fuel cell stack. In this paper, a nonlinear air supply system model integrated with the fuel cell stack voltage model is first built, based on physical laws and empirical data; then, conventional proportional-integral-derivative (PID) controls for the oxygen excess ratio are implemented. On this basis, fuzzy logic inference and neural network algorithm are integrated into the conventional PID controller to tune the gain coefficients, respectively. The simulation results verify that the fuzzy PID controller with seven subsets could clearly improve the dynamic responses of the fuel cells in both constant and variable OER controls, with small overshoots and the fastest settling times of less than 0.2 s. Full article

Proton exchange membrane fuel cells (PEMFC) are vulnerable to oxygen starvation when working under variable load. To address these issues, a cascade control strategy of sliding mode control (SMC) and Proportion Integration Differentiation (PID) control is proposed in this study. The goal of the control strategy is to enhance the PEMFC’s net power by adjusting the oxygen excess ratio (OER) to the reference value in the occurrence of a load change. In order to estimate the cathode pressure and reconstruct the OER, an expansion state observer (ESO) is developed. The study found that there is a maximum error of about 2200Pa between the estimated cathode pressure and the actual pressure. Then the tracking of the actual OER to the reference OER is realized by the SMC and PID cascade control. The simulation study, which compared the control performance of several methods—including PID controller, adaptive fuzzy PID controller and the proposed controller, i.e., the SMC and PID cascade controller—was carried out under various load-changing scenarios. The outcomes demonstrate that the proposed SMC and PID cascade controller method really does have a faster response time. The overshoot is reduced by approximately 3.4% compared to PID control and by about 0.09% compared to fuzzy adaptive PID. SMC and PID cascade control reference OER performs more effectively in terms of tracking compared to PID control and adaptive fuzzy PID control. Full article

Hydrogen starvation leads to the extreme deterioration of fuel cell performance due to the induced voltage reversal and carbon corrosion in the anode catalyst layer (ACL) and gas diffusion layer. In this paper, reversal-tolerant anodes (RTAs) with different ACL configurations are proposed, where IrO_x/C is used as a water electrolysis catalyst. Experimental results show that the separate IrO_x/C catalyst layer of MEA samples, layered reversal-tolerant catalyst-coated membrane (layered-RTA), and reversal-tolerant gas diffusion electrode (GDE-RTA) significantly enhance the reversal tolerance and cell performance compared to conventional anode and common RTA consisting of a homogeneous catalyst layer mixed with IrO_x/C and Pt/C (hybrid-RTA). Of these, GDE-RTA possessed a reversal tolerance time of 86 min, a power density of 1.42 W cm⁻², and a minimum degradation rate of 2.4 mV min⁻¹, suggesting it to be the best RTA structure. Cyclic voltammetry and electrochemical impedance spectrum were used to detect the properties of each sample. Additionally, the degradation mechanisms of the three RTAs are thoroughly investigated and discussed by means of microstructural characterization through scanning electron microscopy and transmission electron microscopy. This work provides novel ideas for the fabrication of a robust RTA by tuning the ACL configuration, which is practical for the commercialization of fuel cells. Full article

Cereal crops can differ greatly in tolerance to oxygen shortage under germination and seedling establishment. Rice is able to germinate and elongate the coleoptile under submergence and anoxia. This capacity has been attributed to the successful use of starchy reserves through a molecular pathway activated by sugar starvation and low oxygen. This pathway culminates with the expression of α-amylases to provide sugars that fuel the sink organs. On the contrary, barley and wheat are unable to germinate under anoxia. The sensitivity of barley and wheat is likely due to the incapacity to use starch during germination. This review highlights what is currently known about the molecular mechanisms associated with cereal germination and seedling establishment under oxygen shortage with a special focus on barley and rice. Insights into the molecular mechanisms that support rice germination under low oxygen and into those that are associated with barley sensitivity may be of help for genetic improvement programs. Full article

Fuel starvation is a major cause of anode corrosion in low temperature polymer electrolyte fuel cells. The fuel cell start-up is a critical step, as hydrogen may not yet be evenly distributed in the active area, leading to local starvation. The present work investigates the hydrogen distribution and risk for starvation during start-up and after nitrogen purge by extending an existing computational fluid dynamic model to capture transient behavior. The results of the numerical model are compared with detailed experimental analysis on a 25 cm² triple serpentine flow field with good agreement in all aspects and a required time step size of 1 s. This is two to three orders of magnitude larger than the time steps used by other works, resulting in reasonably quick calculation times (e.g., 3 min calculation time for 1 s of experimental testing time using a 2 million element mesh). Full article

The reliability and durability of the proton exchange membrane (PEM) fuel cells are vital factors restricting their applications. Therefore, establishing an online fault diagnosis system is of great significance. In this paper, a multi-stage fault diagnosis method for the PEM fuel cell is proposed. First, the tests of electrochemical impedance spectroscopy under various fault conditions are conducted. Specifically, prone recoverable faults, such as flooding, membrane drying, and air starvation, are included, and different fault degrees from minor, moderate to severe, are covered. Based on this, an equivalent circuit model (ECM) is selected to fit impedance spectroscopy by the hybrid genetic particle swarm optimization algorithm, and then fault features are determined by the analysis of each model parameter under different fault conditions. Furthermore, a multi-stage fault diagnosis model is constructed with the support vector machine with the binary tree, in which fault features obtained from the ECM are used as the characteristic inputs to realize the fault classification (including fault type and fault degree) online. The results show that the accuracy of the basic fault test and subdivided fault test can reach 100% and 98.3%, respectively, which indicates that the proposed diagnosis method can effectively identify flooding, drying, and air starvation of PEM fuel cells. Full article

As an important part of the fuel cell subsystem, the air supply system of the proton exchange membrane fuel cell (PEMFC) plays an important role in improving the output performance and durability of fuel cells. It is necessary to control the oxygen excess ratio of fuel cell systems in the process of variable load, preventing the oxygen starvation in the loading process and excessive parasitic power consumption caused by oxygen saturation. At this time, the modeling of fuel cell systems and the development of control strategies are critical. The development of a control strategy depends on the construction of the control model. Aiming at the difficulty of air supply system modeling, this paper uses radial basis function (RBF) neural network and state equation method to establish the dynamic model of air supply systems. At the same time, PID, fuzzy logic plus PID (FL + PID), feedforward plus PID (FF + PID), fuzzy feedforward plus fuzzy PID (FF + FLPID) control strategy are proposed to control the oxygen excess ratio of the system. The simulation results show that fuzzy feedforward plus fuzzy PID (FF + FLPID) has the best effect and the oxygen excess ratio can be followed in 1 s. Full article

The electric power characteristic of solid oxide fuel cells (SOFCs) depends on numerous influencing factors. These are the mass flow of supplied hydrogen, the temperature distribution in the interior of the fuel cell stack, the temperatures of the supplied reaction media at the anode and cathode, and—most importantly—the electric current. Describing all of these dependencies by means of analytic system models is almost impossible. Therefore, it is reasonable to identify these dependencies by means of stochastic filter techniques. One possible option is the use of Kalman filters to find locally valid approximations of the power characteristics. These can then be employed for numerous online purposes of dynamically operated fuel cells such as maximum power point tracking or the maximization of the fuel efficiency. In the latter case, it has to be ensured that the fuel cell operation is restricted to the regime of Ohmic polarization. This aspect is crucial to avoid fuel starvation phenomena which may not only lead to an inefficient system operation but also to accelerated degradation. In this paper, a Kalman filter-based, real-time implementable optimization of the fuel efficiency is proposed for SOFCs which accounts for the aforementioned feasibility constraints. Essentially, the proposed strategy consists of two phases. First, the parameters of an approximation of the electric power characteristic are estimated. The measurable arguments of this function are the hydrogen mass flow and the electric stack current. In a second stage, these inputs are optimized so that a desired stack power is attained in an optimal way. Simulation results are presented which show the robustness of the proposed technique against inaccuracies in the a-priori knowledge about the power characteristics. For a numerical validation, three different models of the electric power characteristic are considered: (i) a static neural network input/output model, (ii) a first-order dynamic system representation and (iii) the combination of a static neural network model with a low-order fractional differential equation model representing transient phases during changes between different electric operating points. Full article

An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified. Full article

ADP/ATP carriers (AACs) are mitochondrial transport proteins playing a strategic role in maintaining the respiratory chain activity, fueling the cell with ATP, and also regulating mitochondrial apoptosis. To understand if AACs might represent a new molecular target for cancer treatment, we evaluated AAC expression levels in cancer/normal tissue pairs available on the Tissue Cancer Genome Atlas database (TCGA), observing that AACs are dysregulated in most of the available samples. It was observed that at least two AACs showed a significant differential expression in all the available kidney cancer/normal tissue pairs. Thus, we investigated AAC expression in the corresponding kidney non-cancer (HK2)/cancer (RCC-Shaw and CaKi-1) cell lines, grown in complete medium or serum starvation, for investigating how metabolic alteration induced by different growth conditions might influence AAC expression and resistance to mitochondrial apoptosis initiators, such as “staurosporine” or the AAC highly selective inhibitor “carboxyatractyloside”. Our analyses showed that AAC2 and AAC3 transcripts are more expressed than AAC1 in all the investigated kidney cell lines grown in complete medium, whereas serum starvation causes an increase of at least two AAC transcripts in kidney cancer cell lines compared to non-cancer cells. However, the total AAC protein content is decreased in the investigated cancer cell lines, above all in the serum-free medium. The observed decrease in AAC protein content might be responsible for the decrease of OXPHOS activity and for the observed lowered sensitivity to mitochondrial apoptosis induced by staurosporine or carboxyatractyloside. Notably, the cumulative probability of the survival of kidney cancer patients seriously decreases with the decrease of AAC1 expression in KIRC and KIRP tissues making AAC1 a possible new biomarker of metabolic remodeling and survival in kidney cancers. Full article