Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-07-03T12:42:00Z No. of bitstreams: 1 AcassioRochaSantos_DISSERT.pdf: 9390259 bytes, checksum: d25d8e92963faba78cb36774741179e4 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-07-06T11:41:22Z (GMT) No. of bitstreams: 1 AcassioRochaSantos_DISSERT.pdf: 9390259 bytes, checksum: d25d8e92963faba78cb36774741179e4 (MD5) / Made available in DSpace on 2017-07-06T11:41:22Z (GMT). No. of bitstreams: 1 AcassioRochaSantos_DISSERT.pdf: 9390259 bytes, checksum: d25d8e92963faba78cb36774741179e4 (MD5) Previous issue date: 2017-02-21 / O estudo te?rico de clusters met?licos tem despertado um interesse consider?vel, devido ? possibilidade de criar novas ligas de materiais em nanoescala, as chamadas "nanoligas". Pesquisas sobre nanoligas desempenham papel significativo na Ci?ncia de Materiais, pois, entre seus objetivos mais importantes, est?o o de prever a estabilidade das estruturas, seus modos de crescimento, bem como o de auxiliar a interpreta??o de medidas espectrosc?picas e outras medi??es experimentais. Nesse contexto, um grande n?mero de m?todos foi relatado nos ?ltimos anos para a otimiza??o do m?nimo global de grupos at?micos e moleculares, sendo um dos mais utilizados atualmente o do Algoritmo Gen?tico (doravante, GA), o qual baseia-se em princ?pios relacionados a processos evolutivos, em operadores inspirados na Teoria da Evolu??o e na Gen?tica, isto ?, na recombina??o, muta??o e sele??o natural. Particularmente, o GA com a implementa??o do potencial Gupta tem se mostrado eficiente na busca de solu??es ??timas? em problemas de otimiza??o de clusters met?licos. Esta disserta??o ? composta por cap?tulos de introdu??o, de metodologia, de abordagem te?rica (Cap. 1, 2 e 3); e tamb?m por cap?tulos que cont?m artigos sobre o tema proposto (Cap. 4, 5 e 6). No primeiro artigo (Cap. 4), analisaram-se clusters bimet?licos AlxNay (x+y?55) por meio da aplica??o do GA com a implementa??o do potencial Gupta. Com base tamb?m na aplica??o do GA, no segundo cap?tulo (Cap. 5) foram estudados clusters de AlxLiy e AlxKy (x+y ? 55). Em ambos os trabalhos, para elevar a efici?ncia do GA, introduziu-se mais dois operadores: o Aniquilador e o Hist?ria. Ao serem comparadas as estruturas obtidas por meio do GA com potencial Gupta para clusters de alum?nio puro, l?tio puro e alum?nio-l?tio com resultados recentes da literatura, verificou-se que para os sistemas Al2, Al3, Al6, Al8, Al9, Li5, Li6, Li7, Al1Li5, Al1Li7 e Al1Li8 as geometrias obtidas foram muito semelhantes ?quelas resultantes de c?lculos de funcional de densidade e ab initio[como CCSD(T)]. No terceiro artigo (Cap. 6), analisou-se um novo algoritmo gen?tico qu?ntico (Q-GA) para pequenos sistemas de clusters NaxLiy com (x+y ? 10). Constatou-se que o Q-GA apresenta maior efici?ncia na busca do m?nimo global em rela??o ao GA com o potencial Gupta. Isso porque o primeiro utiliza m?todo qu?ntico, enquanto o segundo usa um m?todo cl?ssico. Por ser mais preciso, o Q-GA possui uma abrang?ncia menor. Neste artigo, al?m de c?lculos ab inito, tamb?m foram realizados c?lculos topol?gicos a partir da Teoria Qu?ntica de ?tomos em Mol?culas (QTAIM) para as estruturas Na1Li5, Na2Li4, Na3Li3, Na4Li2 e Na5Li1, obtidas pelo Q-GA. Nessas estruturas, chama a aten??o o fato de n?o haver caminho de liga??o envolvendo diretamente os metais, sendo unidos por pseudo?tomos, com exce??o do Na5Li1. Algumas intera??es at?micas n?o foram indicadas pelo caminho de liga??o e sua an?lise foi feita pelo ?ndice de deslocaliza??o (DI). No sistema Na1Li5, os pares at?micos Na1-Li2 e Na1-Li6 t?m as intera??es mais fortes (e equivalentes ? do sistema NaLi) de todos os pares Na-Li de todos clusters NaxLiy(x+y=6); ao mesmo tempo, os outros pares Na-Li t?m intera??es dez vezes mais fracas do que aquelas do sistema NaLi. As intera??es Na-Na dos clusters Na4Li2 e Na5Li1 s?o as mais fortes quando comparadas com sistemas puros. Por fim, verificou-se que a f?rmula do grau de degeneresc?ncia do ?ndice de aromaticidade D3BIA e a carga at?mica indicaram que os ?tomos de l?tio mais pr?ximo ao ?tomo de s?dio transferem carga para esse ?ltimo. / The theoretical study of metal clusters has drawn considerable interest due to the possibility of creating new alloys from materials in nanoscale, the so-called "nanoalloys". Research on nanoalloys has had an important role in materials science, since, among some of its most relevant objectives, we may find the prediction of stability in structures, their manners of growth and further assistance in the interpretation of spectroscopic and other experimental measures. In this context, several methods have been reported in the last few years towards the global minimum optimization of atomic and molecular groups, where the Genetic Algorithm (henceforth GA) is currently considered one of the most used methods, whilst based on principles related to evolutionary processes as well as operators inspired by the Theory of Evolution and Genetics, i. e., by recombination, mutation and natural selection. The GA method in particular, and altogether with the implementation of the Gupta potential, has become efficient in the search for ?optimal? solutions for optimization problems in metallic clusters. The present dissertation is composed of chapters consisting of introduction, methodology and theoretical considerations (Chap. 1, 2 and 3), as well as of chapters containing articles on the proposed subject (Chap. 4, 5 and 6). In the first article (Chap. 4), we may find the analysis of AlxNay (x + y ? 55) bimetallic clusters through the Genetic Algorithm method with the implementation of the Gupta potential. Also based on the GA application, in the following chapter (Chap. 5) we may find a study regarding AlxLiy e AlxKy (x+y ? 55) clusters. In both works, in order to improve GA efficiency, two additional operators have been introduced: Annihilator and History. By being compared to structures obtained by means of GA with Gupta potential for pure aluminum, pure lithium and aluminum-lithium clusters in recent results from literature, it has been verified that, regarding systems Al2, Al3, Al6, Al8, Al9, Li5, Li6, Li7, Al1Li5, Al1Li7 e Al1Li8, the obtained geometries were very similar to those resulting from density functional and ab initio calculations [such as CCSD(T)]. In the third chapter (Chap. 6), we analyzed a new quantum genetic algorithm (QGA) for small cluster systems NaxLiy with (x+y ? 10). It has been observed that Q-GA presents an improved efficiency towards a global minimum regarding the GA with the Gupta potential. That has been the case since the former uses the quantum method, while the latter uses a classic method. More specifically, the Q-GA has a narrower scope. In this article, besides ab initio calculations, topological calculations were performed as well, grounded on the Quantum Theory of Atoms in Molecules (QTAIM) for the structures Na1Li5, Na2Li4, Na3Li3, Na4Li2 e Na5Li1 obtained by the Q-GA. In these structures, it is evident that there is no bonding path between the metals, since they are bonded by pseudo atoms, with the exception of the Na5Li1. Some of the atomic interactions have not been suggested by the bonding path, being their analysis performed according to the delocalization index (DI). In the Na5Li1 system, the atomic pairs Na1-Li2 and Na1-Li6 have the strongest interactions (equivalent to the NaLi system) of all Na-Li pairs in all of the NaxLiy (x+y=6) clusters; concurrently, other Na-Li pairs bear interactions ten times weaker than those from the NaLi system. The Na-Na interactions from the clusters Na4Li2 e Na5Li1 are stronger when compared to pure systems. Finally, it has been verified that the degree of degeneracy formula of the aromaticity index D3BIA and the atomic charge suggest that the lithium atoms that are closer to the sodium atom transfer charge to the latter.