ODTÜ Teknokent (Turkey)

Digital platforms are technological applications with steadily increasing popularity. This study aims to investigate various factors associated with the purchase of transportation, accommodation, and household services via digital platforms by individuals in Türkiye. This study used the 2023 "Household Information Technologies Usage Survey Microdata Set" provided by the Turkish Statistical Institute. To identify the possible effects of factors such as gender, education level, age, income level, and household size on digital platforms, binary logistic regression analysis was used. According to the study's results, all the factors, including gender, education level, age, income level, and household size, may affect the use of digital platforms. Accordingly, the likelihood of using digital platforms is higher among men compared to women, younger individuals compared to older ones, and individuals with higher education and income compared to those with lower levels. In terms of household size, a negative relationship was found. In other words, individuals from larger households are less likely to use digital platforms. The study's findings suggest that beliefs and values, consumption habits, social roles and responsibilities, and the factor of trust in digital platforms play a role in the use of digital platforms. In the study, which includes evaluations that digital platforms will become increasingly widespread in Türkiye, where Western values and a modern lifestyle are gradually becoming more prevalent, recommendations are made regarding the perception and promotion of digital platforms and the importance of public relations practices.

Abstract Coumarin-based organic layers have attracted considerable attention in optoelectronic device applications due to their favorable optical and electronic properties. However, the incorporation of bathocuproine (BCP) into a coumarin/p-Si architecture and its systematic evaluation in terms of responsivity, detectivity, photocapacitance, and interface state density have not been systematically reported. In this study, coumarin–BCP composite layers containing 10 wt% and 20 wt% BCP were prepared, and Al/p-Si/coumarin:BCP/Al devices were fabricated. The electrical and optoelectronic properties were investigated under visible-light illumination (20–100 mW/cm 2 ). The device containing 20% BCP exhibited enhanced performance, achieving a responsivity of 54.62 mA/W and a specific detectivity of 1.69 × 10 12 Jones at 100 mW/cm 2 , compared to 18.64 mA/W and 5.77 × 10 11 Jones for the 10% BCP device. The improved photoresponse is attributed to enhanced charge transport and interface-related effects induced by increased BCP concentration. These results demonstrate that coumarin–BCP composite-based Al/p-Si devices are promising candidates for visible-light photodetector and photosensor applications.

Characterization of perovskite–silicon (Pero/Si) tandem solar cells in an industrial environment is hampered by several challenges. First, the monolithic series connection of the two subcells and the fact that the entire stack shares only two electrical terminals make it impossible to probe each subcell independently. Second, the perovskite absorber's metastability—most notably ion migration—introduces additional, often slow, time‐dependent effects. Together with the industry's requirement for high throughput, these factors complicate accurate, high‐speed characterization. In this work we propose a concept to acquire I–V data for tandem solar cells from light‐emitting diode (LED)‐based solar simulators, where we acquire an approximation of the external quantum efficiency from LED‐based measurements before conducting an I–V measurement with an adjusted LED illumination spectrum. We present results on a reference III/V and different Pero/Si solar cells. We model ion migration in perovskite subcells, which allows for assessing preconditioning and transient effects in I–V cell measurements. We recommend a short preconditioning under light to stabilize the scan time dependence and show the potential for transfer between industrial and lab conditions. Finally, we showcase concepts of camera‐based luminescence measurements for inline analysis. Specifically, we show a line‐scan photoluminescence approach, a fast electroluminescence (EL) imaging approach based on parallel data acquisition with two cameras, and an EL concept based on the application of one RGB camera.

Abstract Smart Flock Manager (SFM) is an artificial intelligence (AI)-driven decision support system (DSS) designed to enhance precision livestock farming (PLF) through machine learning, cloud computing, and Radio Frequency Identification technology. It enables real-time data collection, predictive analytics, and automated decision making to optimize reproductive efficiency, health monitoring, and economic sustainability while ensuring animal welfare. A comparative analysis of flock performance before and after SFM implementation highlights key trade-offs. While pre-SFM conditions resulted in higher birth (256%) and weaning (225%) rates, they also increased metabolic stress on ewes, shortening reproductive lifespan and raising replacement rates. In contrast, SFM improved reproductive efficiency and lamb survival, reducing stillbirths (4 to 1%), lamb mortality (12.22 to 6.78%), and increasing pregnancy rates (79 to 85.29%). However, earlier weaning (69 to 52 days) led to reduced average daily gains (222.46 g/day to 196.15 g/day) prior to weaning, emphasizing the need for optimized post-weaning nutrition. This study highlights the importance of balancing high output with ewe longevity and welfare. A moderate prolificacy rate (200–220%) with improved weaning strategies enhances sustainability and productivity. Future recommendations include optimizing reproductive selection, maternal nutrition, and weaning protocols. SFM’s AI-driven insights offer a scalable solution for sustainable and economically viable intensive sheep farming. Information © The Authors 2025

Thermoelectric materials have gained significant attention for energy harvesting and waste heat recovery, particularly in aerospace applications. The layered Ca3Co4O9 structure, a member of the misfit‐layered cobaltite family, has been extensively studied for its high thermoelectric performance. Herein, Ca2.5Ag0.3Sm0.2Co4O9 ceramic materials are synthesized via the sol–gel method to enhance their thermoelectric properties. Various characterization techniques, including differential thermal analysis thermogravimetry, X‐ray diffraction, X‐ray Photoelectron Spectroscopy, scanning electron microscopy, and thermoelectric characterization, are employed to analyze the thermal, structural, and morphological properties of the synthesized materials. The thermoelectric properties are evaluated through the Seebeck coefficient, electrical resistivity, and power factor measurements. The incorporation of Ag and Sm as dopants improves the electrical conductivity and thermopower, making these materials suitable for aerospace thermoelectric systems.

The continuous change in the entrance cross-section of a parallel-plate flow channel generally affects the mass and heat transfer on the walls of the channel. In this paper, an electrochemical parallel-plate flow channel equipped with a selenoid pulse generator has been developed to enhance the convective mass transfer on the walls of a mass transfer flow system such as an electrodeposition cell, absorption column, flow reactor, etc. A number of experimental studies have been conducted to determine the distribution of the mass transfer coefficients on the bottom wall of a parallel-plate channel for the flow conditions with/without a pulse in the research. Here, the distribution of the convective mass transfer coefficients has been determined by the electrochemical limiting diffusion current technique (ELDCT) using nickel local cathodes arranged on the bottom surface of the flow channel. The experimental results show the effects of the parameters used, which are the flow Reynolds number, opened/closed (OP/CL) ratio, and pulse number, on the distribution of mass transfer coefficients. The results have revealed that the pulse generator altered the flow structure and increased the turbulent intensity at Re < 2860 flow conditions. Within the range of Reynolds number 950 < Re < 2860, the mass transfer correlation was given as Sh=67.02Re0.897OpCl−0.059Sc1/3. According to the research findings, the highest kM values were obtained at Re = 2860 with an (OP/CL) ratio of 1/2. If a parallel-plate flow reactor with a pulse generator is designed using these flow conditions, it will yield a reactor that is both more efficient and more compact than a reactor without a pulse generator.

The performance provided by graphene (Gr) and graphene oxide (GO) additives can be improved by achieving strong adhesion and uniform dispersion in the epoxy resin matrix. In this study, molecular modeling and simulation of DGEBA/DETA based epoxy nanocomposites containing Gr and GO additives were performed. Density functional theory and molecular dynamics simulations were used to investigate interfacial interaction energies and Young's Modulus. Improvement in the interaction energies was studied by controlling the epoxy:hardener ratio, type and the number of oxygen-containing functional groups on the GO, the mass percentage of Gr/GO filler in the epoxy matrix, size and dispersion of GO in the cell. It was demonstrated that functional groups with up to 10 % oxygen content in GO significantly increase interfacial interaction energy for large size Gr/GO. Increasing DETA type amine ratio in the preparation of epoxy polymers increases the interaction energy for high oxygen content while decreasing the interaction energy for low oxygen content in GO for small size GO with edge functional groups. The performance of material dramatically decreased even at high DETA hardener and high GO mass percentages when the aggregation factor of Gr/GO was included in simulations that explain lower Gr/GO percentages in the experimental studies.