In recent years, an increasing progress have been observed in application of polymer science and technology in different aspects of Energy including Energy production, conversion, and storage. Humans have been engaged with severe air pollution of the world and its adverse effects on the all aspects of life. The most reliable solution to decrease the emission of greenhouse gases and other pollutants is complete or at least partial substitution of petroleum-based fuels with Clean Energy. Therefore, finding renewable and/or sustainable Energy resources such as sunlight, internal earth heat, hydrogen and oxygen gases, wind, and hydroelectric Energy as well as extending their public usage is of vital prominence. In this regard, polymers due to their distinctive combination of desired and tailor-made properties attracted much attentions in different fields of Energy production.

The increasing consumption of fossil fuels and limited resources and the environmental problems cause to carry out extensive research on the replacement of new and Clean Energy resources. In recent years, researchers have focused on fuel cells, solar cells, lithium batteries and biomass as a Clean Energy reserves. Although these methods have disadvantages but the using of nanotechnology lead to solve significant drawback of these techniques. Graphene, as a carbon nanostructure, is a two-dimensional substance with hexagonal network and covalent bonds have unique properties including high electrical, mechanical, thermal, chemical, surface area and low density. These wonderful properties lead to graphene is considered as a good candidate in fuel cell, solar cell, ion battery and bio mass. Due to the importance of this issue, this paper reviews the graphene and its applications in Clean energies.

This study examines the potential of Clean Energy technologies in achieving Sustainable Development Goals (SDGs), particularly Goal 7 (SDG 7), in Iran. Given the environmental challenges posed by climate change and the need to reduce reliance on fossil fuels, identifying and evaluating Clean Energy technologies is essential for achieving these goals. This research utilizes multi-criteria decision-making (MCDM) methodologies to analyze and evaluate various Clean Energy technologies. The evaluation criteria in this study include Energy transition, geographic, economic, political, social, and environmental factors. These criteria comprehensively analyze different aspects of Energy sustainability, enabling the comparison and ranking of various technologies. Using MCDM methods such as Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIKOR, and PROMETHEE II, the results reveal that solar and wind Energy emerge as the top choices in various domains, including production capacity, cost-effectiveness, and social acceptance. These findings can assist policymakers and decision-makers in formulating effective strategies for sustainable Energy development. Additionally, the results of this study can contribute to improving the Energy landscape of the country and supporting the achievement of global climate goals and sustainable development objectives. Ultimately, this research highlights the importance of utilizing Clean Energy technologies and multi-criteria approaches in Energy decision-making and serves as a reference for future studies in this field.

Sediment microbial fuel cells (SMFCs) are new technologies for production of Clean Energy. SMFCs are able to convert a wide range of organic matter contained in the sediment to bioelectricity. In this study, four different ecosystems (sea, hatchery, river and spring) was evaluated to assess their potential to generate electricity. Graphites were used as anode and cathode electrode. The lowest produced voltage was around 310 mV and produced from hatchery. Compared to other ecosystems, rivers generate the highest maximum generated power density of 37.09 mw/m2. The maximum generated voltage was 740 mV and it was completely stable for 12 days.

Introduction: Environmental disasters, stakeholder pressure, and global trends have caused the discussion of new energies and businesses in this field to be the focus of researchers. In Iran, the issue of sanctions, dependence of industries on fossil fuels and the traditional mentality of managers has restricted growth and development of Clean Energy. Development in this field requires a correct understanding of the future and fundamental planning. Without paying attention to financing, which is one of the most important challenges for the development of any business, it will not be possible to continue the activity. Therefore, the current research identified drivers and investment scenarios in the field of Clean Energy.Materials and Methods: The current research is pragmatic in terms of philosophy and applied in terms of orientation. Also, this study is exploratory in terms of objective and mixed in terms of methodology. The statistical population of the research were experts in the field of Clean Energy and financing. Using judgmental sampling, 15 managers working in Iran Renewable Energy Association, Iran Energy Association, Environmental Protection Organization and university professors in the relevant fields have been used. The research has been done in five steps. In the first step, key drivers were identified through background review and interviews with experts. In the second step, the drivers were screened through an expert questionnaire and using the fuzzy Delphi method. In the third step, the screened propellants were analyzed through the effect measurement questionnaire and using the fuzzy Dimetal method, and the final propellants were identified based on the degree of effectiveness. In the fourth step, believable scenarios were developed using CATWOE. The probable scenario was identified with CODAS technique.Results: By reviewing the background and interviewing experts, 24 drivers were extracted. Using the fuzzy Delphi method, 12 drivers whose diphasis number was higher than the threshold (0.7) were selected. Then, with the Fuzzy Dimetal technique, the two drivers of the laws related to the Energy field and the government's view on the need to enter the field of Clean Energy were identified and evaluated as suitable for the development of scenarios. Based on these two drivers, four scenarios of soul prison, auspicious, Anti-innovation culture, and poisonous structure were developed. The soul prison scenario depicts the pessimistic future and the auspicious scenario shows the best scenario. Then, using CODAS technique, the soul prison scenario was selected as the most probable scenario.Discussion: Policy makers should try to make Karmiar's ideal scenario happen instead of realizing the soul prison scenario, which happens to be the worst scenario. For this purpose, laws and policies should be established to improve the business environment in the field of Clean Energy. Such laws should remove obstacles to attract foreign capital while increasing domestic capital. These laws should enable the transfer of advanced technologies through fiscal and financial support. The view of government officials on the need to enter into Clean Energy as the second most important driver has cultural roots and originates from managers' ignorance of Clean Energy and its advantages in the business environment. For this reason, universities, research centers, social media, non-governmental organizations supporting the environment, global and regional developments and environmental disasters play an important role in changing this attitude. In Iran, because managers are forced to accept change at the last moment, change is sudden and has increasing costs. It is hard to expect change without doing inclusive and spontaneous cultural work. Cultivation plays an important role in favoring green products. In addition, changing the attitude of managers can lead to the facilitation of financing as a key challenge in the field of Clean Energy.

Using wind Energy for hydrogen production in Iran can be important for reasons such as abundant wind resources in Iran, reducing dependence on fossil fuels, ensuring Clean Energy supply, the potential for hydrogen exports, technology development and job creation. Therefore, this study signifies the first exploration into the potential for generating electricity and producing hydrogen in ten wind-rich cities in Iran. HOMER V.2.81 software was used for simulations, and the wind data used are averaged over a 25-year period. The results show that in Iran, the price range for wind power is $0.515-$0.620 per kWh in the top 10 stations. Bandar Abbas, Parsabad, and Khalkhal had the best economic and environmental performance, respectively. The highest percentage of renewable electricity production is 71% in Bandar Abbas. Finally, the amount of hydrogen produced based on four common electrolyzer types in Iran was investigated. The total annual hydrogen production per ton for SOE, MCE, AE, and PEME electrolysis method at the examined stations is 131.29, 93.43, 40.99, and 30.69, respectively. According to the results, the highest hydrogen production with a value of 16.87 tons per year is related to the Bandar Abbas station and the SOE electrolysis method. The lowest hydrogen production, with a value of 2.36 tons per year, is related to Alvand station and the PEME electrolysis method.

BACKGROUND AND OBJECTIVES: A solar panel is a device that converts solar rays into electricity. It is a step to reduce emissions from fossil Energy, which is to replace it with renewable Energy. It requires a control system to ensure that the position of the solar panel is always perpendicular to the sun’, s rays. This study aims to modify the fuzzy set based on fuzzy entropy in the control system that has been developed. The modifications made are expected to increase the efficiency of solar panels in harvesting Energy. METHODS: Type II fuzzy sliding mode control is used, along with a modified fuzzy set based on the entropy value. Before modification, the system containing the fuzzy set generates a histogram of entropy and voltage performance, which is the initial value and the comparison value. The algorithm alters the footprint of the uncertainty limit. This change results in a new fuzzy set, which results in a new histogram and voltage. The final step is to compare the initial and final parameters based on the results of the modifications. FINDINGS: The solar panels require only 7. 3x10-5 degrees of movement per second. This is a very slow movement for a dc motor with a maximum voltage of 12 volts. The simulation produced a stable speed of 7. 297x10-5 on the unmodified system and 7. 295x10-5 on the modified system. The modified system experiences a slight delay towards the stable point because the fuzzy entropy method reduces the dominance of set point positions in the system. CONCLUSION: The modified fuzzy set is good at controlling the solar panel driving motor based on the output voltage value. On both controllers under consideration, the voltages follow the same pattern. However, it experienced a control mismatch at the point towards the set point. Finally, by changing the foot of uncertainty and adjusting it proportionally according to control needs, the control system based on fuzzy sets with fuzzy entropy can be further developed.