Abstract

Research Article

Utilizing a Visual Method, Focuses on the Modeling of the Semi-empirical Mass Formula "SEMF" in Nuclear Physics

Esraa Fareed Saeed*

Published: 17 June, 2024 | Volume 8 - Issue 1 | Pages: 051-054

An empirical framework that accurately describes radioactive binding energies is the Somewhat Empirical Mass Equation (SEMF). They showcase many implementations and uses of the idea that rely on graphics and printed objects. A key new addition is a contrast with real experiments, as well as a visualization of the energy environment as supplied by the SEMF. The shortcomings of the empirical theory are shown by our visualization of this differential energy scenery, which also highlights the significance of what is known as magic numbers—an explanation provided by the outermost approach, which was developed much more recently than the water drop theory. This provides a great chance to talk about the advantages and limitations of simulations everywhere within the framework of science teaching.

Read Full Article HTML DOI: 10.29328/journal.jro.1001064 Cite this Article Read Full Article PDF

Keywords:

Binding energy; Nuclide tabletop; Semi-empirical mass equation; Nuclear science; 3D printers; Modeling; Film

References

  1. Ubben M, Heusler S. Gestalt and functionality as independent dimensions of mental models in science Res. Sci. Educ. 2019; 49:1–15.
  2. Ubben M, Heusler S. A haptic model of vibration modes in spherical geometry and its application in atomic physics, nuclear physics and beyond Eur. J. Phys. 2018; 39:045404.
  3. Martin BR, Shaw G. Nuclear and particle physics: an introduction. 3rd ed. Hoboken, NJ: Wiley; 2019. p. 62. ISBN 978-1-119-34462-9. OCLC 1078954632.
  4. Oregon State University. Nuclear masses and binding energy lesson 3. Oregon State University. cited 2015 Sep 30.
  5. Möller P. The limits of the nuclear chart set by fission and alpha decay. EPJ Web Conf. 2016; 131:03002:1-8. doi:10.1051/epjconf/201613103002.
  6. Ubben M, Heusler S. Gestalt and functionality as independent dimensions of mental models in science. RSC Educ. 2021; 51:1349.
  7. Ubben MS, Heusler S. A haptic model of vibration modes in spherical geometry and its application in atomic physics, nuclear physics, and beyond. Eur J Phys. 2018;39(d5404).
  8. Discusses the limitations of the SEMF and provides a detailed visual approach to understanding these constraints (Inspire HEP).
  9. Explores critical models of fission and includes discussions on the liquid-drop model and its relationship to the SEMF (Inspire HEP).
  10. Examines mutual influences of terms in the SEMF and extends the formula with additional terms to better fit nuclear masses (Inspire HEP).
  11. A new semi-empirical mass formula developed to improve the accuracy of nuclear binding energy predictions (Inspire HEP).
  12. Focuses on high-precision nuclear mass predictions, providing insights into modern approaches for refining the SEMF (Inspire HEP).
  13. Provides an overview of the SEMF, its corrections, and its application to nuclear binding energy calculations (Inspire HEP).
  14. Machine learning approaches to nuclear physics that involve the SEMF for modeling nuclear properties (Inspire HEP).
  15. General description and background of the SEMF, also known as the Weizsäcker formula, including its theoretical and empirical bases (Inspire HEP).
  16. Binding Blocks, Department of Physics. https://york.ac.uk/physics/public-and-schools/secondary/binding-blocks/
  17. Pluta WJ, Chinn CA, Duncan RG. Learners’ epistemic criteria for good scientific models. J. Res. Sci. Teach. 2011; 48 486–511.
  18. Bailey D. Semi-empirical Nuclear Mass Formula. PHY357: Strings & Binding Energy. University of Toronto. 2011-03-31.
  19. Khan DA, Khan N, Ilyas N, Gul MT. Mechanisms of Stress Tolerance in Halophytic Plants. Metascience. 2024;2(2):9-16.
  20. Ibrar M, Rahim K, Ullah S, Gul MT. A Brief Overview On The Highly Medicinal Plant Genus Gomphrena. Metascience. 2024;2(1):84-91.
  21. Khan N, Ilyas N, Gul MT. Mycorrhizal Associations' Significance for Plant Nutrition. Metascience. 2024;2(2):1-8.
  22. Ullah I, Khan N, Gul MT. Plants' Physiological Reactions to Climate Change. Metascience. 2024;2(1):76-83.
  23. Wang M, Audi G, Kondev FG. The AME2016 atomic mass evaluation (II). Tables, graphs and references. Chin. Phys. C. 2017; 41:030003.
  24. Wang N, Liu M, Wu XZ, et al. Surface diffuseness correction in global mass formula. Phys Lett B 2014; 734:215-219.
  25. Kanber HA, Alkhalidy ME. Google scholar and the scientific originality of the professor. Iraqi J Inf Technol. 2018;8(2):22-45. (in Arabic)
  26. Kanbar HA. Islamic Digital Library A project to Create a Digital library for the student in the Department of Holy Quran and Islamic Education Prepare. J Iraqi Univ. 2022;55(3):277-296.
  27. Zheng JS, Wang NY, Wang ZY, et al. Mass predictions of the relativistic mean-field model with the radial basis function approach. Phys Rev C. 2014;90:014303.
  28. Niu ZM, Zhu ZL, Niu YF, et al. Radial basis function approach in nuclear mass predictions. Phys Rev C. 2013;88:024325.

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