Role of additives and surface passivation on the performance of perovskite solar cells

Outstanding improvement in power conversion efficiency (PCE) over 25% in a very short period and promising research developments to reach the theoretical PCE limit of single junction solar cells, 33%, enables organic–inorganic perovskite solar cells (OIPSCs) to gain much attention in the scientific and industrial community. The simplicity of production of OIPSCs from precursor solution either on rigid or flexible substrates makes them even more attractive for low-cost roll-to-roll production processes. Though OIPSCs show as such higher PCE with simple solution processing methods, there are still unresolved issues, while attempts are made to commercialize these solar cells. Among the major problems is the instability of the photoactive layer of OIPSCs at the interface of the charge transport layers and /or electrodes during prolonged exposure to moisture, heat and radiation. To achieve matched PCE and stability, several techniques such as molecular and interfacial engineering of components in OIPSCs have been applied. Moreover, in recent times, engineering on additives, solvents, surface passivation, and structural tuning have been developed to reduce defects and large grain boundaries from the surface and/or interface of organic–inorganic perovskite films. Under this review, we have shown recently developed additives and passivation strategies, which are strongly focused to enhance PCE and long-term stability simultaneously.

ANALYSIS OF EXISTING SOLUTIONS FOR IMPROVING THE MEASURING AND COMPUTING COMPLEXES OF HEAT SUPPLY NETWORKS

In the presented article, the team of authors considers the existing methods and the main modern technical solutions that are currently implemented in different countries in the diagnosis of heat supply networks. There is a selection of the main directions in the development and design of heat supply networks, which have already been implemented or supported by scientific teams from different countries. Various methods and technical features of diagnostics are reviewed, strengths and weaknesses of the presented solutions are highlighted. The reviewed works were subjected to detailed analysis, which revealed the presence of a high interest of the scientific and industrial community in the integration and improvement of existing digital technologies in the development of heat supply systems, which would be closely related to forecasting and modeling processes in this industry. The team of authors highlights the main vectors for the development of this sector, citing an example of a significant increase in the degree of digitalization of final products, which makes it possible to use data analytics to obtain effective technical solutions regarding heat supply networks. Separately, the positive experience of different countries in this industry is noted when using neural networks not only in the design of heat supply networks, but also as a target industry as a whole. Assumptions are put forward about the need for a detailed analysis of the existing foreign and domestic experience, as well as scientific developments in this area, in order to determine the most suitable technical solutions on the territory of the Russian Federation, which will take into account the climatic characteristics of the country and be based on methods of large data analysis, computer vision and simulation. modeling.

The Role of Journalists in Building Optimism in the Small Industry Community During the Corona Pandemic (Study: Formation of a Post For Journalists Covering Covid-19 for the South West Region of Aceh)

The coronavirus pandemic has made some small industrial communities complain, plus there is confusing news information so that some people feel nervous in dealing with the spread of the coronavirus. The study in this research is basically field research (field research) and literary (library research), with a historical and multidisciplinary approach. Existing data, the authors analyze using a comparative method in a qualitative paradigm, through snowball sampling. Through this method, researchers hope to collect information needed by the small industrial community, so that they are motivated and enthusiastic in moving their business in the midst of the Corona pandemic. The role of the media is not only to report but also to deny hoax information and untrue information, moreover, the media has an important and strategic role in following the development of reliable information related to Covid-19 reporting, as a trusted source for the community towards the era of adaptation of new habits (new normal). ). The presence of journalists presenting news about aid programs, business opportunities, and product marketing facilities for small industry players in circulation and online is one of the breakthroughs that can foster new optimism and hope (expectations) among small industry players in the midst of their business slump due to the pandemic. corona. The final goal of this study, the author tries to get a concrete picture of the roles and responsibilities of journalists in building the optimism of the small industrial community during the corona pandemic.

A Methodology of DASs Benchmarking to Support Industrial Community Characteristics in Designing and Implementing Advanced Driver Assistance Systems Within Vehicles

This study presents a novel benchmarking methodology for Data Acquisition System (DAS) types to support industrial community characteristics in designing and implementing the advanced driver assistance systems within vehicles, which is considered multicriteria decision-making (MCDM) problems. Four issues support this claim. Multiple criteria need to be considered in the evaluation, data variation, trade-off and conflict. Thus, an MCDM solution is essential to overcome problem complexity. In the last years, MCDM developed methods have been studied and criticised from different theoretical aspects. The most recent method, fuzzy decision by opinion score method (FDOSM), has proven its power in solving other methods challenges. However, the FDOSM technique and its extension were based on traditional fuzzy set theory, which is limited and unable to deal with the membership and non-membership hesitation simultaneously and that affect the accuracy of final decision especial among the group of decision-makers. Therefore, this study extended FDOSM into an intuitionistic fuzzy environment that considers the hesitation index in the membership definition, then discuss the power of such membership in evaluating and benchmarking the DAS systems. The proposed methodology comprises two consecutive phases. In the first phase, a decision matrix is formulated based on the crossover of the ‘DAS systems’ and ‘multiple evaluation criteria’. In the second phase, the new method (the intuitionistic FDOSM method) has two main stages (i.e. data transformation unit and data processing). The dataset was used to prove the concept. A total of 39 DASs were evaluated based on 14 DASs criteria, involving seven sub-criteria for “comprehensive complexity assessment” purpose and eight sub-criteria for “design and implementation” purpose, which highly affected the design of DAS when implantation occurred by industrial communities. The results of this study are as follows: (1) Individual results of benchmarking, which used three decision-makers are broad, with consensus on the DAS#1 system ranked as the best. (2) The results of the proposed GDMs proved quality in DASs benchmarking, and the DAS#1 system is also the best. (3) Intuitionistic FDOSM can deal with hesitation and uncertainty problems properly. (4) Significant differences were indicated among the groups’ scores, which proves the validity of the intuitionistic FDOSM results.

Processing Optimization and Toxicological Evaluation of “Lead-Free” Piezoceramics: A KNN-Based Case Study

Due to the ever-increasing limitations of the use of lead-based materials, the manufacturing of lead-free piezoceramics with competitive piezoelectric properties and established nontoxicity is considered a priority for the scientific and industrial community. In this work, a lead-free system based on sodium potassium niobate (KNN), opportunely modified with MgNb2O6 (MN), was prepared through a combination of a mechanochemical activation method and air sintering, and its toxicity was evaluated. The effect of the mechanical processing on the microstructure refinement of the processed powders was established by X-ray diffraction and the average crystallite size content of the Nb2O5 species was evaluated. The experimental evidence was rationalized using a phenomenological model which permitted us to obtain the amount of powder processed at each collision and to optimize the activation step of the pre-calcined reagents. This influenced the final density and piezoresponse of the as-sintered pellets, which showed optimal properties compared with other KNN systems. Their toxicological potential was evaluated through exposure experiments to the pulverized KNN-based pellets, employing two widely used human and environmental cellular models. The in vitro assays proved, under the selected conditions, the absence of cytotoxicity of KNN-bases systems here studied.

Reasons and Strategies for Privacy Features in Tracking and Tracing Systems—A Systematic Literature Review

In the course of the digitization of production facilities, tracking and tracing of assets in the supply chain is becoming increasingly relevant for the manufacturing industry. The collection and use of real-time position data of logistics, tools and load carriers are already standard procedure in entire branches of the industry today. In addition to asset tracking, the technologies used also offer new possibilities for collecting and evaluating position and biometric data of employees. Thus, these technologies can be used for monitoring performance or for tracking worker behaviour, which can lead to additional burdens and stress for employees. In this context, the collection and evaluation of employee data can influence the workplace of the affected employee in the company to his or her disadvantage. The approach of Privacy by Design can help to benefit from all the advantages of these systems, while ensuring that the impact on employee privacy is kept to a minimum. Currently, there is no survey available that reviews tracking and tracing systems supporting this important and emerging field. This work provides a systematic overview from the perspective of the impact on employee privacy. Additionally, this paper identifies and evaluates the techniques used with regard to employee privacy in industrial tracking and tracing systems. This helps to reveal new privacy preserving techniques that are currently underrepresented, therefore enabling new research opportunities in the industrial community.

A model of participatory learning process for management of environmental health impacts in industrial communities area

PurposeThe purpose of this paper is to implementing environmental education concepts to manage environmental health impacts by letting the people in the community learn through the participatory learning process.Design/methodology/approachThe participatory action research (PAR) and the environmental education concept were conducted in managing the learning process for the people in Map Kha Sub-district, Rayong province. The purposive sampling technique and the stakeholder analysis were used to derive the informants of this study. They are those people living or working in the Mab Kha Sub-district area at least 2 years, aged more than 20 years old, and were willing to participate in all steps of the study. A total of 30 informants were divided into three groups as follows: The Key Informants, The Casual Informants and The General Informants. Data collection employed workshops with three techniques – Participatory Rural Appraisal (PRA), Future Search Conference (FSC) and Appreciation Influence Control (AIC) – to organize cooperative learning processes to managing environmental health impacts. The Content Analysis was utilized in this study through the categorization, grouping, analysis, interpretation and systemization of data. The study period was from June 2014 to December 2015.FindingsThe study found that most people are concerned and aware of the environmental pollution problems affecting the health in the areas and need to solve such problems. They are also prepared for various problems. However, they face the problems on that they still lack of the chance to be informed about the information on the pollution problems and lack of the chance to participate. For the participatory learning process used to manage the environmental health impacts in the industrial community, it is found that the people and the leading network partners perform well through the knowledge building process on the environmental pollution problems and the planning and evaluation lead to desired behavior of people and industrial community to manage environmental health impacts.Originality/valueThe study results emphasized that the participatory learning process of the network associates was the critical key in forming the community power to manage the environmental health impacts. Therefore, the learning process should be easy, not complicated, take a short time and be friendly that will make the community understand the problem and help protect the environment systematically.

SECURITY ECOLOGIES OF A COLLABORATIVE ENGINEERING ORGANIZATION IN A REVITALIZING CITY

In 2014, the organizers of Bowman Creek Educational Ecosystem (BCe2) designed a project to revive a vital but polluted tributary to the St. Joseph River through a growing collaboration of dozens of institutions, community groups, schools, and universities in the revitalizing city of South Bend, Indiana. In 2020, BCe2 continues to work in a post-industrial community still facing many challenges from lack of mobility to declining infrastructure and high crime rates. This article focuses on this ecological coalition’s first year of full-scale programs in 2016, when its organizers often expressed BCe2’s neighborhood development interests through the framework of safety concerns. In an effort to develop a long-neglected waterway, the organization’s safety orientations presented an underlying framework of security agendas emerging from perceptions of South Bend’s Southeast neighborhood as an embattled urban community. BCe2 planners often conceptually militarized its operations in a security ecology, a pervasive order of surveillance practices and perceptions that attempted to neutralize longstanding community defense strategies by engineering development interventions.

Niching Grey Wolf Optimizer for Multimodal Optimization Problems

Metaheuristic algorithms are widely used for optimization in both research and the industrial community for simplicity, flexibility, and robustness. However, multi-modal optimization is a difficult task, even for metaheuristic algorithms. Two important issues that need to be handled for solving multi-modal problems are (a) to categorize multiple local/global optima and (b) to uphold these optima till the ending. Besides, a robust local search ability is also a prerequisite to reach the exact global optima. Grey Wolf Optimizer (GWO) is a recently developed nature-inspired metaheuristic algorithm that requires less parameter tuning. However, the GWO suffers from premature convergence and fails to maintain the balance between exploration and exploitation for solving multi-modal problems. This study proposes a niching GWO (NGWO) that incorporates personal best features of PSO and a local search technique to address these issues. The proposed algorithm has been tested for 23 benchmark functions and three engineering cases. The NGWO outperformed all other considered algorithms in most of the test functions compared to state-of-the-art metaheuristics such as PSO, GSA, GWO, Jaya and two improved variants of GWO, and niching CSA. Statistical analysis and Friedman tests have been conducted to compare the performance of these algorithms thoroughly.