Photosystem I application in biohybrid polymer solar cells

The use of Bio-photonic systems has attracted a lot of attention recently specially in the field of solar energy conversion and photovoltaic materials the use of photosynthetic organs of plants is very promising. The energy conversion in the process of photosynthesis is close to 100% and it’s environmental compatibly are the main reasons for why photosynthesis has attracted the attention of energy system designers and researchers. The way of solar energy conversion in photosynthesis indicates a great potential as a fount of renewable energy. Use of the photosynthetic components in photosensors and photovoltaic devices solitarily, has disadvantages such as low extracted current compared to other kinds of photovoltaic materials. Accordingly, for more useful and better application, these photosynthetic components could be used as the optimizer of the other species of photovoltaic materials and solar cells. photosystem1 protein complex, which is the main member of photosynthetic components has maximum absorption spectrum wavelength at 430nm and 665nm. Therefore, it can be an appropriate complement for polymeric solar cells with their absorption spectrum at the green wavelength region. In this paper we have used the photosystem1 protein complex in the inverted polymer solar cell with structure of ITO/P3HT:ICBA/PS1/Al and positive results have been observed. So that the polymer solar cells efficiency was enhanced from 4.3% to 4.53%

Validation of the training and human resource development of excellence model in Iran

Aim: The main objective of this study was to validate Training and Development of Excellence Model (TDEM) in Iran. Method: This study is a descriptive research and was conducted by using survey method. The statistical society contains specialists, experts, and key knower of training area about TDEM in Iran. Statistical sample included 154 people selected using a stratified random sampling method. The tool used is a questionnaire containing 124 items. Obtained results were analyzed using statistical methods of structural equation benchmarking and using LISREL statistical software (lisrel 8.5). Results: The research findings showed that the amount of the Adjusted Goodness-of-Fit Index was 0.91, and the amount of the Root Mean Squared Error of Approximation was estimated by 0.08, therefore model validation indexes are desirable. Furthermore, by using t-test, investigation of the model parameters is discussed. Conclusions: The results of this study have been indicated favorable validation indexes of TDEM. The segmentation of the model is also supported by the findings (segmentation into three parts; enablers, processes, and results)

Unraveling the Interconnected Axes of Heterogeneity in Machine Learning for Democratic and Inclusive Advancements

The growing utilization of machine learning (ML) in decision-making processes raises questions about its benefits to society. In this study, we identify and analyze three axes of heterogeneity that significantly influence the trajectory of ML products. These axes are i) values, culture and regulations, ii) data composition, and iii) resource and infrastructure capacity. We demonstrate how these axes are interdependent and mutually influence one another, emphasizing the need to consider and address them jointly. Unfortunately, the current research landscape falls short in this regard, often failing to adopt a holistic approach. We examine the prevalent practices and methodologies that skew these axes in favor of a selected few, resulting in power concentration, homogenized control, and increased dependency. We discuss how this fragmented study of the three axes poses a significant challenge, leading to an impractical solution space that lacks reflection of real-world scenarios. Addressing these issues is crucial to ensure a more comprehensive understanding of the interconnected nature of society and to foster the democratic and inclusive development of ML systems that are more aligned with real-world complexities and its diverse requirements

Microstructure and optical properties of cobalt–carbon nanocomposites prepared by RF-sputtering

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