Refractive index of ZnO ultrathin films alternated with Al(2)O(3)in multilayer heterostructures

Autor(es)

Lopez-Medina, J. ^[1] ; Carvalho, William O. F. ^[2] ; Vazquez-Arce, J. ^[3] ; Moncada-Villa, E. ^[4] ; Oliveira Jr, Osvaldo N. ; Farias, M. H. ^[5] ; Tiznado, H. ^[5] ; Mejia-Salazar, J. R. ^[2]

Afiliação do(s) autor(es)

^[1] UNAM, CONACYT Ctr Nanociencias & Nanotecnol, Km 107 Carretera Tijuana Ensenada S-N BC, Ensenada 22800, Baja California - Mexico

^[2] Natl Inst Telecommun Inatel, BR-37540000 Santa Rita Do Sapucai, MG - Brazil

^[3] Ctr Invest Cient & Educ Super Ensenada CICESE, Ensenada 22860, Baja California - Mexico

^[4] Univ Pedagog & Tecnol Colombia, Escuela Fis, Ave Cent Norte 39-115, Tunja - Colombia

^[5] Univ Nacl Autonoma Mexico, Ctr Nanociencias & Nanotecnol, Km 107 Carretera Tijuana Ensenada S-N, Ensenada 22800, Baja California - Mexico

• Tipo de documento: Artigo Científico
• Fonte: Nanotechnology; v. 31, n. 50 DEC 11 2020.
• Citações Web of Science: 0

Resumo

The design of optoelectronic devices made with ZnO superlattices requires the knowledge of the refractive index, which currently can be done only for films thicker than 30 nm. In this work, we present an effective medium approach to determine the refractive index of ZnO layers as thin as 2 nm. The approach was implemented by determining the refractive index of ZnO layers ranging from 2 nm to 20 nm using spectroscopic ellipsometry measurements in multilayers. For a precise control of morphology and thickness, the superlattices were fabricated with atomic layer deposition (ALD) with alternating layers of 2 nm thick Al(2)O(3)and ZnO, labeled as(N)ZnO-Al2O3, whereN = 10, 20, 30, 50, 75 and 100. The total thickness of all superlattices was kept at 100 nm. The approach was validated by applying it to similar superlattices reported in the literature and fitting the transmittance spectra of the superlattices. (AU)

• Processo FAPESP: 18/22214-6 - Rumo à convergência de tecnologias: de sensores e biossensores à visualização de informação e aprendizado de máquina para análise de dados em diagnóstico clínico
• Beneficiário: Osvaldo Novais de Oliveira Junior
• Modalidade de apoio: Auxílio à Pesquisa - Temático