Nd:YAG laser pulses of 9 nanosecond pulse duration and operating wavelength at 1.06 μm, were utilized to drill high thermal conductivity and high reflectivity aluminum and copper foils. The results showed a dependence of drilled holes characteristics on laser power density and the number of laser pulses used. Drilled depth of 74 ϻm was obtained in aluminum at 11.036×108 W/cm2 of laser power density. Due to its higher melting point, copper required higher laser power density and/or larger number of laser pulses to melt, and a maximum depth of 25 μm was reached at 13.46×108 W/cm2 using single laser pulse.
Receipt date:6/3/2021 acceptance date:4/5/2021 Publication date:31/31/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
The research in the role of variables contact for non-state actors have become more influential in the current of contemporary events, that related with the reality of seeking services and providing all of that in favor of maintaining the social peace, and ensuring its empowerment in order to make peace and stability outcomes as a real fa
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The current study aimed to use some bacterial isolates from the local soil of Baghdad city by study the effects of temperature, pH and incubation period on the growth rates of isolated bacteria and choose the optimal conditions for their diversity and for understanding bacterial growth and their requirements for survival and proliferation. This information can be applied to obtain their high growth rate for use in various fields such as agriculture, medicine and environmental sciences in the future. And it used to assess the degree of variation in across bacteria species in pH, temperature and incubation period. A number of local bacterial isolates as
Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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