Experimental investigation of novel hybrid phase change materials

Jurčević, Mišo; Nižetić, Sandro; Čoko, Duje; Hoang, Anh Tuan; Papadopoulos, Agis M.

doi:10.1007/s10098-021-02106-y

Cited by 22 publications

(4 citation statements)

References 29 publications

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“…The growth of an average temperature sensor is dependent on the sensor diameter, the general properties of the specimen material, the number of concentric rings, and the input heat. Based on the temperature function, thermal constants, namely thermal conductivity and thermal diffusivity, can be precisely assessed [33]. It was suggested by Gustafsson [30] that the first couple of seconds of the measurement should be dismissed because of the existence of insulation on the sensor.…”

Section: Measurement Techniquementioning

confidence: 99%

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Experimental Investigation of Thermal Properties of Frozen Tap, Demineralized, and Sea Water

Bošnjak,

Jurčević,

Bodrožić Ćoko

et al. 2023

Energies

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This paper reports an experimental investigation of the thermal properties of frozen tap, demineralized, and sea water. The presented research assists in a better understanding of the thermal properties of ice and the processes within it and contributes regarding the generation of novel experimental data. The thermal conductivity was measured in a range from −14 °C to −33 °C using the Transient Plane Source (TPS) method. Ice blocks were placed in an expanded polystyrene box in the freezer, which is where the measurements took place. The thermal conductivity of the tap water ice was observed to vary in a range from 1.915 ± 0.005 Wm−1K−1 at −14 °C to 2.060 ± 0.004 Wm−1K−1 at −33 °C. The values obtained for the ice made of demineralized water differed by less than 10%. The thermal conductivity of the sea ice was shown to be more temperature dependent, with the values ranging from 1.262 ± 0.005 Wm−1K−1 at −14 °C to 1.970 Wm−1K−1 ± 0.004 at −33 °C. A noticeable fall in the thermal conductivity of the sea ice was observed in the temperature range from −26 °C to −19 °C. A possible reason for this could be the increased precipitation of salt in that temperature range. Measurements of thermal diffusivity displayed similar trends as those of thermal conductivity. Specific volumetric heat capacity was indirectly calculated.

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Section: Measurement Techniquementioning

confidence: 99%

“…To measure the specimens' temperatures, a K-type thermocouple with Class 1 accuracy [35] and the Pico TC-08 data logger from 2023 Pico Technology Ltd., Cambridgeshire, United Kingdom, [36] were used. The calculation of the uncertainty of the temperature measurements was as follows [33]:…”

Section: Sample Preparation and Examination Proceduresmentioning

confidence: 99%

Experimental Investigation of Thermal Properties of Frozen Tap, Demineralized, and Sea Water

Bošnjak,

Jurčević,

Bodrožić Ćoko

et al. 2023

Energies

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“…These trends encompass decreasing costs, technological advancements, regulatory support, efforts to combat climate change, and a growing recognition of the significance of environmental sustainability [64]- [66]. Despite facing challenges like grid integration and intermittency [67], [68], ongoing developments in energy storage [69], [70], using phase change materials [71]- [73], grid infrastructure [74], [75], and renewable energy forecasting [76]- [78] are addressing these issues and creating new opportunities for the expansion of renewable energy. Ultimately, renewable energy has transformed from a niche option to a widely adopted energy source, vital in the global shift towards a sustainable, low-carbon future [79]- [82].…”

Section: Introductionmentioning

confidence: 99%

Harnessing a Better Future: Exploring AI and ML Applications in Renewable Energy

Nguyen,

Paramasivam,

Dong

et al. 2024

JOIV : Int. J. Inform. Visualization

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Integrating machine learning (ML) and artificial intelligence (AI) with renewable energy sources, including biomass, biofuels, engines, and solar power, can revolutionize the energy industry. Biomass and biofuels have benefited significantly from implementing AI and ML algorithms that optimize feedstock, enhance resource management, and facilitate biofuel production. By applying insight derived from data analysis, stakeholders can improve the entire biofuel supply chain - including biomass conversion, fuel synthesis, agricultural growth, and harvesting - to mitigate environmental impacts and accelerate the transition to a low-carbon economy. Furthermore, implementing AI and ML in combustion systems and engines has yielded substantial improvements in fuel efficiency, emissions reduction, and overall performance. Enhancing engine design and control techniques with ML algorithms produces cleaner, more efficient engines with minimal environmental impact. This contributes to the sustainability of power generation and transportation. ML algorithms are employed in solar energy to analyze vast quantities of solar data to improve photovoltaic systems' design, operation, and maintenance. The ultimate goal is to increase energy output and system efficiency. Collaboration among academia, industry, and policymakers is imperative to expedite the transition to a sustainable energy future and harness the potential of AI and ML in renewable energy. By implementing these technologies, it is possible to establish a more sustainable energy ecosystem, which would benefit future generations.

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“…Phase transition temperatures generally range from 100 to 250 kJ kg À1 . [16] It is possible to modify organic PCMs to alter their functional properties. Studies of esters produced for this reason in the literature, [17][18][19][20] diesters, [21][22][23] alcohols, [24] dicarboxylic acid esters, [25] amides, [26][27][28] diamides, [29,30] sulfones, [31] and ureas [32] are increasing.…”

mentioning

confidence: 99%

Synthesis and Characterization of Dicarboxylic Acid Esters of 1‐Hexadecanol for a Thermal Energy Storage Application Range of 50–55 °C

Alkan¹,

Tosun²,

Kaplan³

2023

Energy Tech

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The increase in population and energy usage rates also continuously increases energy demand. Therefore, the use of renewable resources will become mandatory in the following periods. Orientation to renewable resources is also a necessity due to the increase in carbon dioxide emissions and the associated global warming. Solar energy, wind, and geothermal energy are the most popular known renewable energy sources, but they have some handicaps in terms of the continuity of energy supply. These handicaps can be prevented by storing energy when it is produced excessively. Heat can be efficiently stored in various systems. However, heat storage by phase change takes place at a very high density. In this regard, thermal energy storage (TES) systems ignoring the cost of phasechange materials (PCMs) are exploited in many applications. [1] Studies on PCMs are increasing rapidly. Liu et al. examined high-temperature PCMs and found that such materials could be used as potential energy storage materials. They also explored the possibilities of improving the heat exchange properties of the PCMs used. [2] A wide variety of studies have also been conducted on the encapsulation of PCMs. In one of them, Salunkhe and Shembekar studied encapsulation and its effect on the thermal performance of the energy storage medium. This study examined properties such as shell material and thickness, encapsulation size, and geometry. [3] Xu et al. focused on PCMs and examined the economic aspects of their conversion to a power generation approach and latent heat systems. [4] Gracia and Cabeza reviewed different numerical models used in a PCM-assisted bearing system as an application study. [5] Kalidasan et al. examined high-, medium-, and lowtemperature solar TES methods and their environmental and economic impacts. [6] Yang et al. explored the issue of enhancing thermal response and adding nanoparticles to PCMs for photochromic effect. [7] Yang et al. examined heat transfer modeling in PCM in terms of potential applications of PCMs. [8] Klimeš et al. reviewed and summarized newly published experimental and simulation methods focusing on subcooling PCMs and phasechange hysteresis. [9] Zayed et al., unlike other studies, aimed to increase the efficiency of temperature retention systems and focused on the design parameters and geometric arrangement of PCM containers in their studies. In addition, different heat transfer phenomena, such as the development of photochromic properties with the addition of nanoparticles, the use of metal foams and graphite, and the effectiveness of microencapsulated PCMs, were investigated in this study. [10] Kumar et al.

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Experimental investigation of novel hybrid phase change materials

Cited by 22 publications

References 29 publications

Experimental Investigation of Thermal Properties of Frozen Tap, Demineralized, and Sea Water

Experimental Investigation of Thermal Properties of Frozen Tap, Demineralized, and Sea Water

Harnessing a Better Future: Exploring AI and ML Applications in Renewable Energy

Synthesis and Characterization of Dicarboxylic Acid Esters of 1‐Hexadecanol for a Thermal Energy Storage Application Range of 50–55 °C

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