Publikační činnost Centra energetických a environmentálních technologií / Publications of Centre of Energy and Environmental Technologies (9390)

Permanent URI for this collectionhttp://hdl.handle.net/10084/158299

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Centra energetických a environmentálních technologií (9390) v časopisech registrovaných ve Web of Science od roku 2025 po současnost.
Do kolekce jsou zařazeny:

publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

Bibliografické záznamy byly původně vytvořeny v kolekci Publikační činnost akademických pracovníků VŠB-TUO, která sleduje publikování akademických pracovníků od roku 1990.

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Now showing 1 - 5 out of 5 results

The innovative design of carbon dots on polymer texture for highly selective detection of amino compounds
(Elsevier, 2024) Maruthapandi, Moorthy; Durairaj, Arulappan; Saravanan, Arumugam; Luong, John H. T.; Bakandritsos, Aristides; Gedanken, Aharon; Zbořil, Radek
Volatile organic compounds (VOCs) are of growing concern due to their toxicity and environmental impact. Their facile detection is thus of a high importance but still challenging because they are unreactive and often present at very low concentrations. Developing sensing schemes for VOCs based on low-cost, sensitive, selective, and user-friendly methods is therefore crucial for environmental monitoring. To address these issues, we herein developed polymer supported carbon dots (CDs) by reacting tetraminobenzene with 2,4,6-trichlorophenyl oxalate using a simple reflux method. Owing to the selection of precursors, polymer supported fluorescent carbon dots (P-CDs) were grown decorating the synthesized polymeric spheres. The P-CDs composites were highly stable, and their fluorescence was drastically quenched by several VOC analytes (ethanolamine, diethanolamine, triethanolamine, and ammonia) due to the rich surface functional groups that could effectively and selectively interact with amines. The polymer component contributed to ascribing excellent photophysical and chemical stability, which is valuable particularly for sensing in complex matrices. As a result, the developed P-CDs exhibited superior properties when applied as VOC sensors, including high selectivity for several amines but not for other organic species, fast response, and very high stability, while offering a simple detection method, and minimum sample pre-treatment. The PCD design has extended potential for diverse sensing applications, including, for instance, control of prohibited transport of chemicals and post-toxic analysis.
A comparison between the quality of two level and three levels bidirectional buck-boost converter using the neural network controller
(IEEE, 2024) Gaied, Hajer; Flah, Aymen; Kraiem, Habib; Prokop, Lukáš
A comparison between two-phase and three-phase interlaced DC converter with parallel MOSFET is presented. PWM is evaluated using a two-way DC-DC converter to charge and discharge a battery. The results show an excellent DC voltage gain without an extremely high cycle load. The interlaced DC-DC converters with MOSFETs in parallel in two and three phases offer distinct advantages and limitations. The two-phase converter has a simpler design and a potentially lower cost due to the reduced number of components. However, it can present challenges in terms of precise voltage regulation and current balancing, due to the limited number of switching phases. On the other hand, the three-phase converter offers more precise voltage regulation and improved current balance thanks to its higher number of phases. While this results in increased design complexity and potentially higher cost, it allows for a more uniform distribution of current load among MOSFETs. The choice between the two will depend on the specific requirements of the application, acceptable trade-offs in terms of complexity, cost and performance, as well as the need for accurate voltage regulation and optimal current balancing.
Advancing short-term solar irradiance forecasting accuracy through a hybrid deep learning approach with Bayesian optimization
(Elsevier, 2024) Molu, Reagan Jean Jacques; Tripathi, Bhaskar; Mbasso, Wulfran Fendzi; Naoussi, Serge Raoul Dzonde; Bajaj, Mohit; Wira, Patrice; Blažek, Vojtěch; Prokop, Lukáš; Mišák, Stanislav
The optimization of solar energy integration into the power grid relies heavily on accurate forecasting of solar irradiance. In this study, a new approach for short-term solar irradiance forecasting is introduced. This method combines Bayesian Optimized Attention-Dilated Long Short-Term Memory and Savitzky-Golay filtering. The methodology is implemented to analyze data obtained from a solar irradiance probe situated in Douala, Cameroon. Initially, the unprocessed data is augmented by integrating distinctive solar irradiation variables, and the Savitzky-Golay filter with Bayesian Optimization is used to enhance its quality. Subsequently, multiple deep learning models, including Long Short-Term Memory, Bidirectional Long Short-Term Memory, Artificial Neural Networks, Bidirectional Long Short-Term Memory with Additive Attention Mechanism, and Bidirectional Long Short-Term Memory with Additive Attention Mechanism and Dilated Convolutional layers, are trained and evaluated. Out of all the models considered, the proposed approach, which combines the attention mechanism and dilated convolutional layers, demonstrates exceptional performance with the best convergence and accuracy in forecasting. Bayesian Optimization is further utilized to fine -tune the polynomial and window size of the Savitzky-Golay filter and optimize the hyperparameters of the deep learning models. The results show a Symmetric Mean Absolute Percentage Error of 0.6564, a Normalized Root Mean Square Error of 0.2250, and a Root Mean Square Error of 22.9445, surpassing previous studies in the literature. Empirical findings highlight the effectiveness of the proposed methodology in enhancing the accuracy of short-term solar irradiance forecasting. This research contributes to the field by introducing novel data pre-processing techniques, a hybrid deep learning architecture, and the development of a benchmark dataset. These advancements benefit both researchers and solar plant managers, improving solar irradiance forecasting capabilities.
Single atom catalysts based on earth-abundant metals for energy-related applications
(American Chemical Society, 2024) Kment, Štěpán; Bakandritsos, Aristides; Tantis, Iosif; Kmentová, Hana; Zuo, Yunpeng; Henrotte, Olivier; Naldoni, Alberto; Otyepka, Michal; Varma, Rajender S.; Zbořil, Radek
Anthropogenic activities related to population growth, economic development, technological advances, and changes in lifestyle and climate patterns result in a continuous increase in energy consumption. At the same time, the rare metal elements frequently deployed as catalysts in energy related processes are not only costly in view of their low natural abundance, but their availability is often further limited due to geopolitical reasons. Thus, electrochemical energy storage and conversion with earth-abundant metals, mainly in the form of single-atom catalysts (SACs), are highly relevant and timely technologies. In this review the application of earth-abundant SACs in electrochemical energy storage and electrocatalytic conversion of chemicals to fuels or products with high energy content is discussed. The oxygen reduction reaction is also appraised, which is primarily harnessed in fuel cell technologies and metal-air batteries. The coordination, active sites, and mechanistic aspects of transition metal SACs are analyzed for two-electron and four-electron reaction pathways. Further, the electrochemical water splitting with SACs toward green hydrogen fuel is discussed in terms of not only hydrogen evolution reaction but also oxygen evolution reaction. Similarly, the production of ammonia as a clean fuel via electrocatalytic nitrogen reduction reaction is portrayed, highlighting the potential of earth-abundant single metal species.
Reformer + Membrane separator plant for decarbonized hydrogen production from Biogas/Biomethane: An experimental study combined to energy efficiency and exergy analyses
(Elsevier, 2024) Ruales, Henry Bryan Trujillo; Spadafora, Alex; Fiore, Piergiuseppe; Vereš, Ján; Caravella, Alessio; Iulianelli, Adolfo
Nowadays, the world energy production is still based on the exploitation of fossil fuels, mainly oil, coal, and natural gas, responsible for large greenhouse emissions in the environment. According to the measures proposed by the European Green Deal to meet the carbon neutrality by 2050, the decarbonisation of the global energy production processes represents a top priority. Hydrogen represents a carbon-free energy carrier, useful to drive the society toward a decarbonized-economy. The novelty of this work is represented by the experimental generation of clean hydrogen by a two stages plant constituted of a biogas/biomethane steam reformer and a Pd-Ag membrane separator, meanwhile applying on this simple case the methodology of the exergy analysis, identifying the main losses and suggesting improvements. Hence, it deals with the exergy analysis of the whole system with the process intensification operated by the membrane separator adopted instead of using several stages to separate/purify hydrogen - as conventionally done after the reforming stage (two water gas shift reactors, high and low temperature, followed by a pressure swing adsorption stage) - with the objective of recovering decarbonized hydrogen coming from the biogas/biomethane steam reformer, meeting the European targets indicated by the Clean Hydrogen Alliance. This approach allowed to understand the amount of irreversibilities present in such a system as well as how the thermal efficiency may be influenced by a number of parameters, constituting globally a baseline for the scaling up of this process technology from lab to bench/pilot scale. The best results of this work highlight that the utilization of biomethane in the feed stream to generate hydrogen resulted to be a better choice than biogas in terms of thermal efficiency (based on the lower heating value) of the whole system, equal to 73 % at 773 K, while the highest percentage of exergy destruction was concentrated in the condensation stage, with values varying between 76 % and 93 %, depending on the feed stream typology. The two stages system was able to meet the "decarbonized hydrogen production target 2027", with a hydrogen recovery of 90 % and a purity of 99.9999 %. Last but not least, the overall exergy destroyed efficiency of the overall system in the two analyzed cases was 92 % (biomethane feed stream) and 88 % (biogas feed stream), respectively.

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