Molecular Geometry in Polymerization Formation

Research Article | Open Access

Volume 2021 - 1 | Article ID 169 |

Molecular Geometry in Polymerization Formation

Academic Editor: Ana Maria

Received 2021-02-27
Revised 2021-03-08
Accepted 2021-03-12
Published 2021-03-18

Wesley Bruski Barbero

Medical Student, Harvard Medical School

Corresponding Author: Wesley Bruski Barbero, Pharm Medical Student, Harvard Medical School, Email: wb-barbero@uol.com.br, Ph: 55-49-98418-8853

Citation: Wesley Bruski Barbero (2021) Molecular Geometry in Polymerization Formation. World J Multidiscip Res Rev, 1(1); 1-2.

Copyright: © 2021, Wesley Bruski Barbero. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

ABSTRACT

The crosslinking agent used to obtain a MIP (Molecularly Printed Polymer) performs the following three main functions: control of the morphology of the polymeric matrix (gel-like polymer, macroporous polymer or microgel powder); stabilization of binding sites capable of molecular recognition; mechanical stabilization of the polymeric matrix. Proposal: Molecular modeling observing a polymerizable scale factor in k set of functional monomers using the cross-linking agent tetra-methylene-dimethacrylate. Where the equation is: k. (K-n) = Rt¹ -Rt² / Rr It is explained that k is the subset of parameters obtained in distribution of probability density between the AB interval, with the total number of events possible being equal to the solvent ratio that occurs in T1 initial time and T2 time interval to be measured divided by the ratio crosslinking. Diffusion coefficient of chemical species: k¹. (Kn - plim∞) = DX + DY + DZ where k¹ which is the initial coefficient of molar ratio / kinetic ratio multiplied by kn which is the exponential critical exponent of renormalized reactivity decreased by progression critical kinetic limit equal to the correlation to the three-dimensional chemical crossing matrix determinants in X, Y and Z.

KEYWORDS

Polymerization, matrix determinants, Polymers

INTRODUCTION

CONFLICT OF INTEREST

None

ACKNOWLEDGEMENTS

None

REFERENCES

1. Albeverio S, Hoegh-Krohn R. A Remark on the Connection Batween Stochastic Jl.1echanics and the Heat Equation. J Phys. 1974;15(10):1745.

2. Aguirre, Luiz Antonio. Introdução À Identiﬁcação de Sistemas . Minas Gerais: UFMG, 2007.

3. Ballentine, L.S. The Statistical Interpretation of Quantum Mechanics. Rev Mod Phys. 1970;42:358.

4. Boldrini, José Luiz. Álgebra linear. São Paulo: Harba, 1980.

5. Bohm, D. Causality and Chance in Modern Physics. Routledge & Kegan Paul, LTD. 1967.

6. Carmen Lys Ribeiro Braga. Notas de Física-Matemática: Equações Diferenciais, Funções de Green e Distribuições. Editores: Walter F. Wreszinski, Jose F. Perez, Domingos H. U. Marchetti e João C. A. Barata. Ed. Livraria da Física, São Paulo. 1a edição, 2006.

7. C.H. Bennett. Logical reversibility of computation. IBM Journal of Research and Development. 1973;17:525.

8. Curso de Física-Matemática, J.C.A. Barata, http://denebola.if.usp.br/~jbarata/Notas_de_aula/ Capítulo 16, Capítulo 19, Capítulo 36, Capítulo 37, Capítulo 38.

9. David J. Griffits, Mecânica quântica, ed. 2, tradução Lara freitas, (Pearson, São Paulo).

10. Díaz, J. L. F. Geração de emaranhamento de polarização entre pares de fótons no regimede femtossegundos.Dissertação (Mestrado)– Universidade Federalde Pernambuco. 2014.

11. D. Deutsch, R. Jozsa. Rapid solution of problems by quantum computation. Proceedings of the Royal Society A. 1992;43:553.

12. FAS. Barbosa, AS. Coelho, KN. Cassemiro, P. Nussenzveig, C. Fabre, M. Martinelli, AS. Villar. Beyond spectral homodyne detection: Complete quantum measurement of spectral modes of light. Physical Review Letters. 2013;111:200402.

13. Hänsch, TW, Schawlow A.L. Cooling of gases by laser radiation. Opt Commun. 1975;13:1.

14. H Jeﬀreys. Theory of Probability (Oxford University Press, 1998).

15. Kobayashi K, Ohtsuki, T, Slevin K. Critical exponent for the quantum spin Hall transition in Z2 Network Model. Phys Rev B, 2011;1:1-5.

16. Kok, P. et al. Linear optical quantum computing with photonic qubits. Rev. Mod. Phys., v. 79, n. 1, 2007.

17. Mandelbrot, Benoit B. The Fractal Geometry of Nature. New York: W. H. Freeman and Company, 1977.

18. Reed M., Simon B. M.O. Scully, M.S. Zubairy. Methods of Modern Mathematical Physics Vol. 1-4, Quantum Optics (Cambridge University Press, 1997).

19. Parisio, F. Estimating the reduction time of quantum states. Phys Rev A. 2011;84(6).

20. R. Cleve, A. Ekert, C. Macchiavello, M. Mosca. Quantum algorithms revisited. Proceedings of the Royal Society A. 1998;454:339.

21. Stewart, James. Antonio Carlos Moretti. Cálculo, volume 1. São Paulo: Cengage Learning, 2012.

22. Varriale, M. C. Transição de localização em potenciais aleatórios com correlações de longo alcance,. Tese (Doutorado) — UFRGS, Porto Alegre, (1994).

23. Wegner, F. Electrons in disordered systems. Scaling near the mobility edge Zeits. Phys B Condens Matt. 1976;25(4)327-337.