Pub Date : 2023-10-27DOI: 10.3390/inventions8060136
Shyy Woei Chang
Transport phenomena draw from the fields of continuum mechanics and thermodynamics with diverse industrial applications [...]
输运现象来自连续介质力学和热力学领域，具有不同的工业应用[…]
{"title":"Recent Advances in Fluid Mechanics and Transport Phenomena","authors":"Shyy Woei Chang","doi":"10.3390/inventions8060136","DOIUrl":"https://doi.org/10.3390/inventions8060136","url":null,"abstract":"Transport phenomena draw from the fields of continuum mechanics and thermodynamics with diverse industrial applications [...]","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"14 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136262360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-26DOI: 10.3390/inventions8060135
Guillermo Pascual-Cisneros, Francisco J. Casas, Patricio Vielva
One of the main objectives of cosmology is the measurement of the Cosmic Microwave Background (CMB) polarization and, in particular, the so-called B-modes, which could demonstrate the existence of the primordial gravitational waves generated at the early stages of the Universe. For this reason, a new integrated version of the heterodyne polarimeter photonic part shown on a previously proposed scheme that can be used in both direct imaging and interferometric instruments is presented. We have tested its properties using specific commercial software, obtaining promising results. Working as a direct imaging instrument, it is shown that the proposed polarimeter can provide sufficiently low polarization angle and polarization efficiency systematic errors, which are considered acceptable for current ground-based CMB polarization experiments dedicated to the characterization of the foreground signals affecting the lowest part of the frequency spectrum.
{"title":"Photonic Integrated Circuits for Microwave Astronomy","authors":"Guillermo Pascual-Cisneros, Francisco J. Casas, Patricio Vielva","doi":"10.3390/inventions8060135","DOIUrl":"https://doi.org/10.3390/inventions8060135","url":null,"abstract":"One of the main objectives of cosmology is the measurement of the Cosmic Microwave Background (CMB) polarization and, in particular, the so-called B-modes, which could demonstrate the existence of the primordial gravitational waves generated at the early stages of the Universe. For this reason, a new integrated version of the heterodyne polarimeter photonic part shown on a previously proposed scheme that can be used in both direct imaging and interferometric instruments is presented. We have tested its properties using specific commercial software, obtaining promising results. Working as a direct imaging instrument, it is shown that the proposed polarimeter can provide sufficiently low polarization angle and polarization efficiency systematic errors, which are considered acceptable for current ground-based CMB polarization experiments dedicated to the characterization of the foreground signals affecting the lowest part of the frequency spectrum.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"4 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134908483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-26DOI: 10.3390/inventions8060134
Gabriel Henrique Grala, Lucas Lima Provensi, Rafael Krummenauer, Oswaldo Curty da Motta Lima, Glaucio Pedro de Alcantara, Cid Marcos Gonçalves Andrade
The purpose of this study is to employ and improve evolutionary algorithms, namely the genetic algorithm (GA) and the differential evolution algorithm (DE), to extract the parameters of the equivalent circuit model (ECM) of a bifacial photovoltaic module using the representative model of a diode with five parameters (1D5P). The objective is to simulate the characteristics of the I–V curves for various irradiation and temperature scenarios. A distinctive feature of this study is the exclusive use of the information in the technical sheet of the bifacial module to conduct the entire extraction and simulation process, eliminating the need to resort to external sources of data or experimental data. To validate the methods, a comparison was made between the simulation results and the data provided by the bifacial module manufacturer, contemplating different scenarios of irradiation and temperature. The DE was the most accurate algorithm for the 1D5P model, which presented a maximum average error of 1.57%. In comparison, the GA presented a maximum average error of 1.98% in the most distant scenario of STC conditions. Despite the errors inherent to the simulations, none of the algorithms presented relative errors greater than 8%, which represents a satisfactory modeling for the different operational conditions of the bifacial photovoltaic modules.
{"title":"Investigation of the Use of Evolutionary Algorithms for Modeling and Simulation of Bifacial Photovoltaic Modules","authors":"Gabriel Henrique Grala, Lucas Lima Provensi, Rafael Krummenauer, Oswaldo Curty da Motta Lima, Glaucio Pedro de Alcantara, Cid Marcos Gonçalves Andrade","doi":"10.3390/inventions8060134","DOIUrl":"https://doi.org/10.3390/inventions8060134","url":null,"abstract":"The purpose of this study is to employ and improve evolutionary algorithms, namely the genetic algorithm (GA) and the differential evolution algorithm (DE), to extract the parameters of the equivalent circuit model (ECM) of a bifacial photovoltaic module using the representative model of a diode with five parameters (1D5P). The objective is to simulate the characteristics of the I–V curves for various irradiation and temperature scenarios. A distinctive feature of this study is the exclusive use of the information in the technical sheet of the bifacial module to conduct the entire extraction and simulation process, eliminating the need to resort to external sources of data or experimental data. To validate the methods, a comparison was made between the simulation results and the data provided by the bifacial module manufacturer, contemplating different scenarios of irradiation and temperature. The DE was the most accurate algorithm for the 1D5P model, which presented a maximum average error of 1.57%. In comparison, the GA presented a maximum average error of 1.98% in the most distant scenario of STC conditions. Despite the errors inherent to the simulations, none of the algorithms presented relative errors greater than 8%, which represents a satisfactory modeling for the different operational conditions of the bifacial photovoltaic modules.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"445 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134910419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.3390/inventions8060133
Anning Yi, Chen Wang, Lei Wang, Xinli Wang
The ejector drives unreacted hydrogen from the anode to improve fuel utilization ratio and discharges redundant water to prevent flooding and shutdown in the proton exchange membrane fuel cell (PEMFC). However, the traditional fixed structure ejector cannot meet the recycling requirements in the whole dynamic working condition of the fuel cell. In this article, a part nested four-nozzle (PNFN) ejector is proposed to enhance the hydrogen recycling efficiency under variable working conditions of the PEMFC by restricting the nozzle flow as 10%, 20%, 20%, and 50% of the fuel cell-rated power, respectively. Systematical analyses are performed on the experimentally verified 3D model to study inner flow characteristics and performance under different nozzle running modes. The results indicate that the PNFN ejector satisfies the recirculation ratio requirements in the power range of 34–220 kW within the 7–9 bar suitable supply pressure. By comparing with traditional ejectors, the PNFN ejector has a wider working range and especially outputs better performance in the low power range.
{"title":"A Wide Operating Range Ejector with Part Nested Nozzles for PEMFC Hydrogen Recirculation System","authors":"Anning Yi, Chen Wang, Lei Wang, Xinli Wang","doi":"10.3390/inventions8060133","DOIUrl":"https://doi.org/10.3390/inventions8060133","url":null,"abstract":"The ejector drives unreacted hydrogen from the anode to improve fuel utilization ratio and discharges redundant water to prevent flooding and shutdown in the proton exchange membrane fuel cell (PEMFC). However, the traditional fixed structure ejector cannot meet the recycling requirements in the whole dynamic working condition of the fuel cell. In this article, a part nested four-nozzle (PNFN) ejector is proposed to enhance the hydrogen recycling efficiency under variable working conditions of the PEMFC by restricting the nozzle flow as 10%, 20%, 20%, and 50% of the fuel cell-rated power, respectively. Systematical analyses are performed on the experimentally verified 3D model to study inner flow characteristics and performance under different nozzle running modes. The results indicate that the PNFN ejector satisfies the recirculation ratio requirements in the power range of 34–220 kW within the 7–9 bar suitable supply pressure. By comparing with traditional ejectors, the PNFN ejector has a wider working range and especially outputs better performance in the low power range.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"12 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134973245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.3390/inventions8060132
Brijesh Patel, Zih Fong Huang, Chih-Ho Yeh, Yen-Ru Shih, Po Ting Lin
This paper describes a non-destructive detection method for identifying cable defects using K-mer frequency encoding. The detection methodology combines magnetic leakage detection equipment with artificial intelligence for precise identification. The cable defect identification process includes cable signal acquisition, K-mer frequency encoding, and artificial intelligence-based identification. A magnetic leakage detection device detects signals via sensors and records their corresponding positions to obtain cable signals. The K-mer frequency encoding method consists of several steps, including cable signal normalization, the establishment of K-mer frequency encoding, repeated sampling of cable signals, and conversion for comparison to derive the K-mer frequency. The K-mer frequency coding method has advantages in data processing and repeated sampling. In the identification step of the artificial intelligence identification model, an autoencoder model is used as the algorithm, and the K-mer frequency coding method is used to introduce artificial parameters. Proper adjustments of these parameters are required for optimal cable defect identification performance in various applications and usage scenarios. Experiment results show that the proposed K-mer frequency encoding method is effective, with a cable identification accuracy rate of 91% achieved through repeated sampling.
{"title":"K-mer Frequency Encoding Model for Cable Defect Identification: A Combination of Non-Destructive Testing Approach with Artificial Intelligence","authors":"Brijesh Patel, Zih Fong Huang, Chih-Ho Yeh, Yen-Ru Shih, Po Ting Lin","doi":"10.3390/inventions8060132","DOIUrl":"https://doi.org/10.3390/inventions8060132","url":null,"abstract":"This paper describes a non-destructive detection method for identifying cable defects using K-mer frequency encoding. The detection methodology combines magnetic leakage detection equipment with artificial intelligence for precise identification. The cable defect identification process includes cable signal acquisition, K-mer frequency encoding, and artificial intelligence-based identification. A magnetic leakage detection device detects signals via sensors and records their corresponding positions to obtain cable signals. The K-mer frequency encoding method consists of several steps, including cable signal normalization, the establishment of K-mer frequency encoding, repeated sampling of cable signals, and conversion for comparison to derive the K-mer frequency. The K-mer frequency coding method has advantages in data processing and repeated sampling. In the identification step of the artificial intelligence identification model, an autoencoder model is used as the algorithm, and the K-mer frequency coding method is used to introduce artificial parameters. Proper adjustments of these parameters are required for optimal cable defect identification performance in various applications and usage scenarios. Experiment results show that the proposed K-mer frequency encoding method is effective, with a cable identification accuracy rate of 91% achieved through repeated sampling.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"C-18 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.3390/inventions8050131
Rui Han, Jiayi Chen, Taikun Guo
The main composition within a spark-generated bubble primarily consists of vapor, accompanied by a minor presence of noncondensable gases. The phase transition exerts a substantial influence on bubble dynamics throughout various stages, a facet that has been frequently overlooked in prior research. In this study, we introduce a modified theoretical model aimed at accurately predicting the multiple oscillations of spark-generated bubbles. Leveraging the Plesset equation, which integrates second-order corrections for compressibility and non-equilibrium evaporation, we further incorporate the thermal boundary layer approximation for bubbles, as proposed by Zhong et al. We employ an adjusted phase transition duration tailored to the unique characteristics of spark-generated bubbles. Furthermore, we meticulously ascertain initial conditions through repeated gas content measurements within the bubble. Our proposed theoretical model undergoes rigorous validation through quantitative comparisons with experimental data, yielding commendable agreement in modeling the dynamic behavior of bubbles across multiple cycles. Remarkably, we uncover that the condensation rate significantly governs the behavior of spark bubbles during their initial two cycles. Finally, we investigate the dependence of spark-generated bubble dynamics on the phase transition and the presence of air. Air content exhibits a minimal impact on bubble motion prior to the initial bubble collapse, but plays a role in the bubble’s rebound thereafter.
{"title":"A Modified Phase-Transition Model for Multi-Oscillations of Spark-Generated Bubbles","authors":"Rui Han, Jiayi Chen, Taikun Guo","doi":"10.3390/inventions8050131","DOIUrl":"https://doi.org/10.3390/inventions8050131","url":null,"abstract":"The main composition within a spark-generated bubble primarily consists of vapor, accompanied by a minor presence of noncondensable gases. The phase transition exerts a substantial influence on bubble dynamics throughout various stages, a facet that has been frequently overlooked in prior research. In this study, we introduce a modified theoretical model aimed at accurately predicting the multiple oscillations of spark-generated bubbles. Leveraging the Plesset equation, which integrates second-order corrections for compressibility and non-equilibrium evaporation, we further incorporate the thermal boundary layer approximation for bubbles, as proposed by Zhong et al. We employ an adjusted phase transition duration tailored to the unique characteristics of spark-generated bubbles. Furthermore, we meticulously ascertain initial conditions through repeated gas content measurements within the bubble. Our proposed theoretical model undergoes rigorous validation through quantitative comparisons with experimental data, yielding commendable agreement in modeling the dynamic behavior of bubbles across multiple cycles. Remarkably, we uncover that the condensation rate significantly governs the behavior of spark bubbles during their initial two cycles. Finally, we investigate the dependence of spark-generated bubble dynamics on the phase transition and the presence of air. Air content exhibits a minimal impact on bubble motion prior to the initial bubble collapse, but plays a role in the bubble’s rebound thereafter.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135368154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.3390/inventions8050130
Langbo Hou, Heng Chen, Jinjun Wang, Shichao Qiao, Gang Xu, Honggang Chen, Tao Liu
To better consume high-density photovoltaics, in this article, the application of energy storage devices in the distribution network not only realizes the peak shaving and valley filling of the electricity load but also relieves the pressure on the grid voltage generated by the distributed photovoltaic access. At the same time, photovoltaic power generation and energy storage cooperate and have an impact on the tidal distribution of the distribution network. Since photovoltaic output has uncertainty, the maximum photovoltaic output in each scenario is determined by the clustering algorithm, while the storage scheduling strategy is reasonably selected so the distribution network operates efficiently and stably. The tidal optimization of the distribution network is carried out with the objectives of minimizing network losses and voltage deviations, two objectives that are assigned comprehensive weights, and the optimization model is constructed by using a particle swarm algorithm to derive the optimal dispatching strategy of the distribution network with the cooperation of photovoltaic and energy storage. Finally, a model with 30 buses is simulated and the system is optimally dispatched under multiple scenarios to demonstrate the necessity of conducting coordinated optimal dispatch of photovoltaics and energy storage.
{"title":"Optimal Dispatch Strategy for a Distribution Network Containing High-Density Photovoltaic Power Generation and Energy Storage under Multiple Scenarios","authors":"Langbo Hou, Heng Chen, Jinjun Wang, Shichao Qiao, Gang Xu, Honggang Chen, Tao Liu","doi":"10.3390/inventions8050130","DOIUrl":"https://doi.org/10.3390/inventions8050130","url":null,"abstract":"To better consume high-density photovoltaics, in this article, the application of energy storage devices in the distribution network not only realizes the peak shaving and valley filling of the electricity load but also relieves the pressure on the grid voltage generated by the distributed photovoltaic access. At the same time, photovoltaic power generation and energy storage cooperate and have an impact on the tidal distribution of the distribution network. Since photovoltaic output has uncertainty, the maximum photovoltaic output in each scenario is determined by the clustering algorithm, while the storage scheduling strategy is reasonably selected so the distribution network operates efficiently and stably. The tidal optimization of the distribution network is carried out with the objectives of minimizing network losses and voltage deviations, two objectives that are assigned comprehensive weights, and the optimization model is constructed by using a particle swarm algorithm to derive the optimal dispatching strategy of the distribution network with the cooperation of photovoltaic and energy storage. Finally, a model with 30 buses is simulated and the system is optimally dispatched under multiple scenarios to demonstrate the necessity of conducting coordinated optimal dispatch of photovoltaics and energy storage.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135778643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.3390/inventions8050129
Catalina Mercedes Burlacu, Adrian Constantin Burlacu, Mirela Praisler, Cristina Paraschiv
The aim of this research was to develop and deploy efficient deep convolutional neural network (DCNN) frameworks for detecting and discriminating between various categories of designer drugs. These are of particular relevance in forensic contexts, aiding efforts to prevent and counter drug use and trafficking and supporting associated legal investigations. Our multinomial classification architectures, based on Attenuated Total Reflectance Fourier-Transform Infrared (ATR-FTIR) spectra, are primarily tailored to accurately identify synthetic cannabinoids. Within the scope of our dataset, they also adeptly detect other forensically significant drugs and misused prescription medications. The artificial intelligence (AI) models we developed use two platforms: our custom-designed, pre-trained Convolutional Autoencoder (CAE) and a structure derived from the Vision Transformer Trained on ImageNet Competition Data (ViT-B/32) model. In order to compare and refine our models, various loss functions (cross-entropy and focal loss) and optimization algorithms (Adaptive Moment Estimation, Stochastic Gradient Descent, Sign Stochastic Gradient Descent, and Root Mean Square Propagation) were tested and evaluated at differing learning rates. This study shows that innovative transfer learning methods, which integrate both unsupervised and supervised techniques with spectroscopic data pre-processing (ATR correction, normalization, smoothing) and present significant benefits. Their effectiveness in training AI systems on limited, imbalanced datasets is particularly notable. The strategic deployment of CAEs, complemented by data augmentation and synthetic sample generation using the Synthetic Minority Oversampling Technique (SMOTE) and class weights, effectively address the challenges posed by such datasets. The robustness and adaptability of our DCNN models are discussed, emphasizing their reliability and portability for real-world applications. Beyond their primary forensic utility, these systems demonstrate versatility, making them suitable for broader computer vision tasks, notably image classification and object detection.
{"title":"Harnessing Deep Convolutional Neural Networks Detecting Synthetic Cannabinoids: A Hybrid Learning Strategy for Handling Class Imbalances in Limited Datasets","authors":"Catalina Mercedes Burlacu, Adrian Constantin Burlacu, Mirela Praisler, Cristina Paraschiv","doi":"10.3390/inventions8050129","DOIUrl":"https://doi.org/10.3390/inventions8050129","url":null,"abstract":"The aim of this research was to develop and deploy efficient deep convolutional neural network (DCNN) frameworks for detecting and discriminating between various categories of designer drugs. These are of particular relevance in forensic contexts, aiding efforts to prevent and counter drug use and trafficking and supporting associated legal investigations. Our multinomial classification architectures, based on Attenuated Total Reflectance Fourier-Transform Infrared (ATR-FTIR) spectra, are primarily tailored to accurately identify synthetic cannabinoids. Within the scope of our dataset, they also adeptly detect other forensically significant drugs and misused prescription medications. The artificial intelligence (AI) models we developed use two platforms: our custom-designed, pre-trained Convolutional Autoencoder (CAE) and a structure derived from the Vision Transformer Trained on ImageNet Competition Data (ViT-B/32) model. In order to compare and refine our models, various loss functions (cross-entropy and focal loss) and optimization algorithms (Adaptive Moment Estimation, Stochastic Gradient Descent, Sign Stochastic Gradient Descent, and Root Mean Square Propagation) were tested and evaluated at differing learning rates. This study shows that innovative transfer learning methods, which integrate both unsupervised and supervised techniques with spectroscopic data pre-processing (ATR correction, normalization, smoothing) and present significant benefits. Their effectiveness in training AI systems on limited, imbalanced datasets is particularly notable. The strategic deployment of CAEs, complemented by data augmentation and synthetic sample generation using the Synthetic Minority Oversampling Technique (SMOTE) and class weights, effectively address the challenges posed by such datasets. The robustness and adaptability of our DCNN models are discussed, emphasizing their reliability and portability for real-world applications. Beyond their primary forensic utility, these systems demonstrate versatility, making them suitable for broader computer vision tasks, notably image classification and object detection.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.3390/inventions8050128
Ilya V. Myachin, Leonid O. Kononov
Flow chemistry offers several advantages for performing chemical reactions and has become an important area of research. It may seem that sufficient knowledge has already been acquired on this topic to understand how to choose the design of microreactor/micromixer and flow rate in order to achieve the desired outcome of a reaction. However, some experimental data are difficult to explain based on commonly accepted concepts of chemical reactivity and performance of microfluidic systems. In this mini review, we attempt to identify such data and offer a rational explanation of unusual results based on the supramer approach. We demonstrate that variation in flow regime (determined by mixer design and flow rate) can either improve or worsen the reactivity and lead to completely different products, including stereoisomers. It is not necessary to mix the reagents with maximum efficiency. The real challenge is to mix reagents the right way since at a too high or too low flow rate (in the particular mixer), the molecules of reagents are incorrectly presented on the surface of supramers, leading to altered stereoselectivity, or form tight supramers, in which most of the molecules are located inside the supramer core and are inaccessible for attack, leading to low yields.
{"title":"Mixer Design and Flow Rate as Critical Variables in Flow Chemistry Affecting the Outcome of a Chemical Reaction: A Review","authors":"Ilya V. Myachin, Leonid O. Kononov","doi":"10.3390/inventions8050128","DOIUrl":"https://doi.org/10.3390/inventions8050128","url":null,"abstract":"Flow chemistry offers several advantages for performing chemical reactions and has become an important area of research. It may seem that sufficient knowledge has already been acquired on this topic to understand how to choose the design of microreactor/micromixer and flow rate in order to achieve the desired outcome of a reaction. However, some experimental data are difficult to explain based on commonly accepted concepts of chemical reactivity and performance of microfluidic systems. In this mini review, we attempt to identify such data and offer a rational explanation of unusual results based on the supramer approach. We demonstrate that variation in flow regime (determined by mixer design and flow rate) can either improve or worsen the reactivity and lead to completely different products, including stereoisomers. It is not necessary to mix the reagents with maximum efficiency. The real challenge is to mix reagents the right way since at a too high or too low flow rate (in the particular mixer), the molecules of reagents are incorrectly presented on the surface of supramers, leading to altered stereoselectivity, or form tight supramers, in which most of the molecules are located inside the supramer core and are inaccessible for attack, leading to low yields.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Insular networks constitute ideal fields for investment in renewables and storage due to their excellent wind and solar potential, as well the high generation cost of thermal generators in such networks. Nevertheless, in order to ensure the stability of insular networks, network operators impose strict restrictions on the expansion of renewables. Storage systems render ideal solutions for overcoming the aforementioned restrictions, unlocking additional renewable capacity. Among storage technologies, hybrid battery-hydrogen demonstrates beneficial characteristics thanks to the complementary features that battery and hydrogen exhibit regarding efficiency, self-discharge, cost, etc. This paper investigates the economic feasibility of a private investment in renewables and hybrid hydrogen-battery storage, realized on the interconnected island of Crete, Greece. Specifically, an optimization formulation is proposed to optimize the capacity of renewables and hybrid battery-hydrogen storage in order to maximize the profit of investment, while simultaneously reaching a minimum renewable penetration of 80%, in accordance with Greek decarbonization goals. The numerical results presented in this study demonstrate that hybrid hydrogen-battery storage can significantly reduce electricity production costs in Crete, potentially reaching as low as 64 EUR/MWh. From an investor’s perspective, even with moderate compensation tariffs, the energy transition remains profitable due to Crete’s abundant wind and solar resources. For instance, with a 40% subsidy and an 80 EUR/MWh compensation tariff, the net present value can reach EUR 400 million. Furthermore, the projected cost reductions for electrolyzers and fuel cells by 2030 are expected to enhance the profitability of hybrid renewable-battery-hydrogen projects. In summary, this research underscores the sustainable and economically favorable prospects of hybrid hydrogen-battery storage systems in facilitating Crete’s energy transition, with promising implications for investors and the wider renewable energy sector.
{"title":"Sustainable Power Generation Expansion in Island Systems with Extensive RES and Energy Storage","authors":"Emmanuel Karapidakis, Christos Kalogerakis, Evangelos Pompodakis","doi":"10.3390/inventions8050127","DOIUrl":"https://doi.org/10.3390/inventions8050127","url":null,"abstract":"Insular networks constitute ideal fields for investment in renewables and storage due to their excellent wind and solar potential, as well the high generation cost of thermal generators in such networks. Nevertheless, in order to ensure the stability of insular networks, network operators impose strict restrictions on the expansion of renewables. Storage systems render ideal solutions for overcoming the aforementioned restrictions, unlocking additional renewable capacity. Among storage technologies, hybrid battery-hydrogen demonstrates beneficial characteristics thanks to the complementary features that battery and hydrogen exhibit regarding efficiency, self-discharge, cost, etc. This paper investigates the economic feasibility of a private investment in renewables and hybrid hydrogen-battery storage, realized on the interconnected island of Crete, Greece. Specifically, an optimization formulation is proposed to optimize the capacity of renewables and hybrid battery-hydrogen storage in order to maximize the profit of investment, while simultaneously reaching a minimum renewable penetration of 80%, in accordance with Greek decarbonization goals. The numerical results presented in this study demonstrate that hybrid hydrogen-battery storage can significantly reduce electricity production costs in Crete, potentially reaching as low as 64 EUR/MWh. From an investor’s perspective, even with moderate compensation tariffs, the energy transition remains profitable due to Crete’s abundant wind and solar resources. For instance, with a 40% subsidy and an 80 EUR/MWh compensation tariff, the net present value can reach EUR 400 million. Furthermore, the projected cost reductions for electrolyzers and fuel cells by 2030 are expected to enhance the profitability of hybrid renewable-battery-hydrogen projects. In summary, this research underscores the sustainable and economically favorable prospects of hybrid hydrogen-battery storage systems in facilitating Crete’s energy transition, with promising implications for investors and the wider renewable energy sector.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136212652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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