Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms

Optimization is important to identify optimal parameters in many disciplines to achieve high quality products including optimization of thin film coating parameters. Manufacturing costs and customization of cutting tool properties are the two main issues in the process of Physical Vapour Deposition (PVD). The aim of this paper is to find the optimal parameters get better thin film roughness using PVD coating process. Three input parameters were selected to represent the solutions in the target data, namely Nitrogen gas pressure (N2), Argon gas pressure (Ar), and Turntable speed (TT), while the surface roughness was selected as an output response for the Titanium nitrite (TiN). Atomic Force Microscopy (AFM) equipment was used to characterize the coating roughness. In this study, an approach in modeling surface roughness of Titanium Nitrite (TiN) coating using Response Surface Method (RSM) has been implemented to obtain a proper output result. In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. Finally, to validate the developed model, actual data were conducted in different experimental run. In RSM validation phase, the actual surface roughness fell within 90% prediction interval (PI). The absolute range of residual errors (e) was very low less than 10 to indicate that the surface roughness could be accurately predicted by the model. In terms of optimization and reduction the experimental data, GAs could get the best lowest value for roughness compared to experimental data with reduction ratio of 46.75%

Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters

Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected,namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. Additionally,analysis of variance (ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters,genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively

Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology

Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected, namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively

The Role of Alginate Hydrogels as a Potential Treatment Modality for Spinal Cord Injury: A Comprehensive Review of the Literature

Objective To comprehensively characterize the utilization of alginate hydrogels as an alternative treatment modality for spinal cord injury (SCI). Methods An extensive review of the published literature on studies using alginate hydrogels to treat SCI was performed. The review of the literature was performed using electronic databases such as PubMed, EMBASE, and OVID MEDLINE electronic databases. The keywords used were “alginate,” “spinal cord injury,” “biomaterial,” and “hydrogel.” Results In the literature, we identified a total of 555 rat models that were treated with alginate scaffolds for regenerative biomarkers. Alginate hydrogels were found to be efficient and promising substrates for tissue engineering, drug delivery, neural regeneration, and cellbased therapies for SCI repair. With its ability to act as a pro-regenerative and antidegenerative agent, the alginate hydrogel has the potential to improve clinical outcomes. Conclusion The emerging developments of alginate hydrogels as treatment modalities may support current and future tissue regenerative strategies for SCI

The impact of storytelling and narrative variables on skill acquisition in gamified learning

This research attempts to better understand how students in Saudi Arabia benefit from narrative and story aspects in gamified learning environments. Data from a sample of 500 persons with varying levels of education are analyzed using quantitative methods such as descriptive statistics, correlation analysis, and multiple regression analysis. The findings point to strong positive correlations between the use of gamification in education, the influence of storytelling, narrative variables, and the acquisition of new skills. There has been a significant shift toward the use of narrative variables as measures of mastery in gamified classrooms. This study's results show that using gamified learning with story elements may increase students' interest, motivation, and knowledge retention. Efforts are now being made by Saudi Arabia to update its educational system and provide its youth with the tools they'll need to succeed in the country's emerging knowledge-based economy. The use of game-based learning and narrative-rich experiences has promising results in this setting

Characterization of the rhizophora particleboard as a tissue-equivalent phantom material bonded with bio–based adhesive

In this study, some characteristics of Rhizophora spp. particleboards bonded with Serishoom (traditional animal–based adhesive) as a phantom material was investigated. The Rhizophora spp. particleboards were fabricated in two Serishoom adhesive treatment levels (6% and 12%) with three Rhizophora spp. particle sizes (≤ 149 µm, 149 µm – 500 µm, and 500 µm – 1000 µm) at 1 g.cm-3 of the target density. The internal bond strength and the dimensional stability of the Serishoom-bonded Rhizophora spp. particleboards were improved by using the smaller Rhizophora spp. particle size and the higher Serishoom adhesive treatment level. The effective atomic numbers of the Serishoom-bonded Rhizophora spp. particleboards were determineted to be 7,56 to 7,58 by an energy dispersive X-ray, which is in good agreement with those of water and breast tissue. In addition, the density distribution profiles of the fabricated Serishoom-bonded Rhizophora spp. particleboards were determined by the Kriging method with the use Surfer8 computer software, which indicated that there was good density homogeneity throughout the Serishoom-bonded Rhizophora spp. particleboards. The results showed a potential of the Serishoom-bonded Rhizophora spp. particleboard bonded with Serishoom to be used as a phantom material

Telecardiology Application in Jordan: Its Impact on Diagnosis and Disease Management, Patients’ Quality of Life, and Time- and Cost-Savings

Objectives. To assess the impact of live interactive telecardiology on diagnosis and disease management, patients’ quality of life, and time- and cost-savings. Methods. All consecutive patients who attended or were referred to the teleclinics for suspected cardiac problems in two hospitals in remote areas of Jordan during the study period were included in the study. Patients were interviewed for relevant information and their quality of life was assessed during the first visit and 8 weeks after the last visit. Results. A total of 76 patients were included in this study. Final diagnosis and treatment plan were established as part of the telecardiology consultations in 71.1% and 77.3% of patients, respectively. Patients’ travel was avoided for 38 (50.0%) who were managed locally. The majority of patients perceived that the visit to the telecardiology clinic results in less travel time (96.1%), less waiting time (98.1%), and lower cost (100.0%). Telecardiology consultations resulted in an improvement in the quality of life after two months of the first visit. Conclusions. Telecardiology care in remote areas of Jordan would improve the access to health care, help to reach proper diagnosis and establish the treatment plan, and improve the quality of life

Effect of dental trauma management resources on dental practitioners' confidence and knowledge: A pilot cross-sectional study

Background/Aim: The knowledge of standardized care guidelines is critical to the confidence of practitioners in managing dental trauma. Therefore, the aim of this study was to assess the awareness, use and impact of the International Association of Dental Traumatology guidelines, and the online Dental Trauma Guide on general dental practitioners' self-reported confidence and knowledge in managing traumatic dental injuries in the primary and permanent dentitions. Materials and Methods: A cross-sectional, pre-piloted, 27-item self-administered questionnaire survey was distributed electronically to general dental practitioners' working within five member states of the Gulf Cooperation Council countries (Kingdom of Bahrain, Kingdom of Saudi Arabia, Kuwait, Oman, and Qatar) between September and December 2020. Data were collected and analysed using descriptive statistics and Wilcoxon Signed Rank test analysis for relevant comparisons. Results: A total of 294 respondents completed the survey, with the majority being from the Kingdom of Saudi Arabia (47.4%) and Qatar (27.3%). A lack of evidence-based knowledge in managing traumatic dental injuries was evident among more than half of the respondents. Respondents who were cognizant of the recent International Association of Dental Traumatology guidelines (2020) and those who use the Dental Trauma Guide routinely demonstrated a higher self-reported confidence level in managing both simple and complex primary dentition trauma, as well as simple traumatic dental injuries in the permanent dentition (p <.05). Conclusion: This survey highlights critical deficiencies in the knowledge of a large number of the respondents in the management of dental trauma which is likely to cause irreversible long-term patient effects.Open Access funding provided by the Qatar National Library

Modeling of TiN coating roughness using fuzzy logic approach

In this paper, a new approach in predicting the Titanium Nitrite (TiN) coating roughness using fuzzy logic is implemented. Insert cutting tools were coated with TiN using Physical Vapor Deposition (PVD) sputtering process. Central cubic design (CCD) was used to design the optimum experimental point and the collected experimental data was used to develop the fuzzy rules. Bell shape and triangular membership functions were proposed in developing the fuzzy rule-based model. Result of the fuzzy rule-based model was validated using residual error and prediction accuracy. The fuzzy rule based model with triangular membership function showed less residual error and higher prediction accuracy with 7.85% and 95.05%, respectively. The result showed that the fuzzy logic could be a good alternative approach in predicting TiN coatings roughness