Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
Browse
48 results
Search Results
Article Rare Earth Elements in the Global Economy: Usage, Recovery, and the Quest for Supply Security – A Review(Springer Heidelberg, 2026) Top, Soner; Ayten, Asim Mustafa; Altiner, Mahmut; Demir, Idris; Kursunoglu, SaitOften described as the vitamins of modern industry, rare earth elements (REEs) are indispensable for the deployment of low-carbon and clean energy technologies. However, ensuring a secure and sustainable REE supply remains a major challenge due to the strong interdependence between application-driven demand, extraction and processing technologies, and the geopolitical concentration of resources. This review adopts an integrated analytical framework in which these three dimensions are treated as interconnected components shaping the resilience of global REE supply chains. First, the major application sectors of REEs are examined to clarify how emerging energy and advanced manufacturing technologies drive demand for specific elements and amplify their strategic importance. Second, extraction and processing technologies are reviewed in relation to both primary and secondary resources, highlighting how technological maturity, process selection, and material characteristics constrain or enable supply expansion. Finally, geopolitical and strategic aspects of the REE supply chain are analyzed to demonstrate how resource concentration, policy instruments, and international dependencies directly influence technological deployment and industrial competitiveness. By explicitly linking application-driven demand, technological pathways for extraction and processing, and geopolitical supply structures within a unified framework, this review provides a coherent understanding of the systemic challenges facing the REE sector and identifies key leverage points for improving the robustness and sustainability of REE supply chains in the context of the global clean energy transition.Article TEffectBayes: A Nextflow Pipeline for Exploring the Potential Effect of Transposable Elements in Gene Regulatory Network with Multi-Omic Bayesian Network Model(Springer Heidelberg, 2026-03-10) Karakülah, Gökhan; Güner, Hüseyin; Kutlu, Necati KaanTransposable elements (TEs) are critical contributors to gene regulatory networks, yet their repetitive and abundant nature complicates efforts to elucidate their precise regulatory roles. While existing computational tools facilitate systematic identification of associations between TEs and gene expression, these methods typically cannot account for confounding variables or capture causal and directional interactions. To address these limitations, we developed TEffectBayes, a Nextflow-based pipeline leveraging a multi-omic Bayesian network (BN) framework designed to systematically infer directional, probabilistic regulatory dependencies involving TEs. TEffectBayes integrates diverse omics datasets, including RNA-seq-derived gene and locus-specific TE expression, along with ChIP-seq-based histone modification data processed via custom R and Python scripts. Integrated multi-omic datasets are subsequently employed to build gene-centric Bayesian models, enabling robust inference of context-dependent, probabilistic relationships between TEs, chromatin modifications, and gene expression. TEffectBayes thus provides a reproducible and scalable computational framework for unraveling the complex regulatory landscape shaped by TEs. In summary, TEffectBayes supports systematic prioritization of TE-chromatin-gene regulatory candidates for downstream benchmarking and experimental validation, enabling hypothesis-driven follow-up studies in diverse biological contexts. The pipeline, along with comprehensive user tutorials and example datasets, is publicly accessible at https://github.com/nkaan-kutlu/TEffectBayes.Article Machine Learning for V2X-Enabled Microgrids: A Bibliometric and Thematic Review of Intelligent Energy Management Applications(Springer Heidelberg, 2026-03-09) Dogan, Yasemin; Unlu, RamazanModern power systems are evolving due to convergence of electric mobility, artificial intelligence, and renewable energy integration. Electric vehicles serve as dynamic, mobile energy storage units playing a vital role in ensuring resilient microgrid operations, via vehicle-to-everything (V2X) technology. However, despite the rise of machine learning (ML) in energy management, much of the existing literature remains fragmented lacking a holistic perspective across all facets of V2X-enabled microgrids. This study fills this gap by conducting a systematic bibliometric and thematic analysis of 310 articles obtained from Web of Science (2013-2024). By combining bibliometric mapping with thematic synthesis, the research identifies dominant and emerging ML techniques-ranging from reinforcement learning to federated learning-and evaluates their roles in microgrid management. The study highlights underexplored areas, including decentralized coordination, encouraging prosumer participation, understanding user behavior, safeguarding cybersecurity, improving real-time optimization, and the effective integration and adaptation of V2X technology within microgrid ecosystems. These gaps emphasize the need for interdisciplinary research and policy frameworks to address the social dimensions of future energy systems. Beyond a comprehensive overview, this paper proposes a research roadmap integrating technical, social, and policy dimensions. It offers actionable guidance for researchers, stakeholders aiming to unlock the potential of intelligent, human-centered, and socially inclusive energy ecosystems. Furthermore, the findings align with UN Sustainable Development Goals (SDG 7, 11, and 13), while also creating a positive impact on humanity by supporting the well-being of both society and the planet. Ultimately, this reinforces the indispensable role of ML in advancing the zero-carbon transition.Article Citation - WoS: 29Citation - Scopus: 32Wind Farm Site Selection Using GIS-Based Multicriteria Analysis With Life Cycle Assessment Integration(Springer Heidelberg, 2024-01-19) Demir, Abdullah; Dincer, Ali Ersin; Ciftci, Cihan; Gulcimen, Sedat; Uzal, Nigmet; Yilmaz, KutayThe sustainability of wind power plants depends on the selection of suitable installation locations, which should consider not only economic and technical factors including manufacturing and raw materials, but also issues pertaining to the environment. In the present study, a novel methodology is proposed to determine the suitable locations for wind turbine farms by analyzing from the environmental perspective. In the methodology, the life cycle assessment (LCA) of wind turbines is incorporated into the decision process. The criteria are ranked using analytical hierarchy process (AHP). The study area is chosen as the western region of Turkiye. The obtained suitability map reveals that wind speed is not the sole criterion for selecting a site for wind turbine farms; other factors, such as bird migration paths, distance from urban areas and land use, are also crucial. The results also reveal that constructing wind power plants in the vicinity of Izmir, canakkale, Istanbul, and Balikesir in Turkiye can lead to a reduction in emissions. Izmir and its surrounding area show the best environmental performance with the lowest CO2 per kilowatt-hour (7.14 g CO2 eq/kWh), to install a wind turbine due to its proximity to the harbor and steel factory across the study area. canakkale and the northwest region of Turkiye, despite having high wind speeds, are less environmentally favorable than Izmir, Balikesir, and Istanbul. The findings of LCA reveal that the nacelle and rotor components of the wind turbine contribute significantly (43-97%) to the environmental impact categories studied, while the tower component (0-36%) also has an impact.Article Citation - WoS: 3Citation - Scopus: 2Theoretical and Experimental Analysis of Wave Impact Pressures on Curved Seawalls(Springer Heidelberg, 2013-01-10) Mamak, Mustafa; Guzel, HasanExperimental model tests were performed in a wave flume with regular waves to measure the magnitude and distribution of impact pressures caused by breaking waves on a curved seawall model having different radii of curvatures. The base structure of the wall has a foreshore slope of 1/10. Theoretical studies based on pressure impulse theory were carried out to obtain the numerical results of breaking wave impact pressures on curved seawalls. The boundary element method was used for the numerical solution of the governing equation. The novel aspect of this study was to investigate the applicability of pressure impulse theory to curved seawalls. The results showed that the pressure impulse model can be used to model the wave impact pressures and their distribution on curved seawall models with good accuracy. A slight decrease has been observed in pressures for increasing radii of curvatures, especially for the case which the water depth at wall was 14 cm. The location of the maximum impact pressure was found to occur above the still water level for all cases tested in this study.Article Citation - WoS: 174Citation - Scopus: 193The Significance of Renewable Energy Use for Economic Output and Environmental Protection: Evidence From the Next 11 Developing Economies(Springer Heidelberg, 2017-04-08) Paramati, Sudharshan Reddy; Sinha, Avik; Dogan, EyupIncreasing economic activities in developing economies raise demand for energy mainly sourced from conventional sources. The consumption of more conventional energy will have a significant negative impact on the environment. Therefore, attention of policy makers has recently shifted towards the promotion of renewable energy generation and uses across economic activities to ensure low carbon economy. Given the recent scenario, in this paper, we aim to examine the role of renewable energy consumption on the economic output and CO2 emissions of the next fastest developing economies of the world. The study employs several robust panel econometric models by using annual data from 1990 to 2012. Empirical findings confirm the significant long-run association among the variables. Similarly, results show that renewable energy consumption positively contributes to economic output and has an adverse effect on CO2 emissions. Given our findings, we suggest policy makers of those economies to initiate further effective policies to promote more renewable energy generation and uses across economic activities to ensure sustainable economic development.Article Citation - WoS: 347Citation - Scopus: 388The Influence of Renewable and Non-Renewable Energy Consumption and Real Income on CO2 Emissions in the USA: Evidence From Structural Break Tests(Springer Heidelberg, 2017-03-14) Dogan, Eyup; Ozturk, IlhanThe objective of this study is to explore the influence of the real income (GDP), renewable energy consumption and non-renewable energy consumption on carbon dioxide (CO2) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980-2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO2 emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO2 emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.Correction Citation - WoS: 1Citation - Scopus: 1The Influence of Cement Kiln Dust on Strength and Durability Properties of Cement-Based Systems(Springer Heidelberg, 2022-06-15) Hakkomaz, Hadiye; Yorulmaz, Hediye; Durak, Ugur; Ilkentapar, Serhan; Karahan, Okan; Atis, Cengiz DuranArticle Citation - WoS: 6Citation - Scopus: 6The Influence of Cement Kiln Dust on Strength and Durability Properties of Cement-Based Systems(Springer Heidelberg, 2022-06-06) Hakkomaz, Hadiye; Yorulmaz, Hediye; Durak, Ugur; Ilkentapar, Serhan; Karahan, Okan; Atis, Cengiz DuranThere are very few studies in the literature on the usage of CKD in cementitious systems. This article presents the laboratory study results on the influence of cement kiln dust (CKD) on the properties of mortar made with cement kiln dust and Portland cement. The article aims to prevent CKD's (known as a hazardous waste product) damage to nature by utilizing CKD in cementitious systems and contributing to sustainability by reducing cement amount in the cementitious system. For this purpose, 5%, 10%, 15%, and 20% of CKD were replaced with cement and binary cementitious systems were formed. For all mortar mixes, the water/binder ratio was kept constant at 0.5, and the sand/binder ratio was 3. Workability, dry unit weight, water absorption ratio and porosity, flexural strength, compressive strength, abrasion, carbonation, and high-temperature resistance tests were performed on the mortar specimens. Based on the results of laboratory work, it was observed that the replacement of CKD with cement reduces the workability of fresh mortar. Compressive and flexural strengths of CKD-added mixtures were found to be equivalent or insignificantly lower than that of the control sample. The addition of CKD had a negligible effect on water absorption and porosity of samples. Besides, the residual compressive strength determined after the elevated temperature test for the sample made with CKD were found to be equivalent or higher compared to the control sample. Present laboratory studies showed that utilization of CKD in cementitious mortar system is feasible in terms of testing conducted.Article Citation - WoS: 131Citation - Scopus: 135The Influence of Biomass Energy Consumption on CO2 Emissions: A Wavelet Coherence Approach(Springer Heidelberg, 2016-06-23) Bilgili, Faik; Ozturk, Ilhan; Kocak, Emrah; Bulut, Umit; Pamuk, Yalcin; Mugaloglu, Erhan; Baglitas, Hayriye H.In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables' efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO2 emissions in the long run cycles after the year 2005 in the USA.