Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Torres, Jorge Andres Guerra

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in Cooperation with on an Cooperation-Score of 37%

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Publications (5/5 displayed)

  • 2023New optical dispersion models for the accurate description of the electrical permittivity in direct and indirect semiconductors6citations
  • 2022Raman, TEM, EELS, and Magnetic Studies of a Magnetically Reduced Graphene Oxide Nanohybrid following Exposure to Daphnia magna Biomarkers7citations
  • 2021Silicon interface passivation studied by modulated surface photovoltage spectroscopy1citations
  • 2021Analysis of the physical and photoelectrochemical properties of c-Si(p)/a-SiC:H(p) photocathodes for solar water splitting2citations
  • 2020Capacitance voltage curve simulations for different passivation parameters of dielectric layers on siliconcitations

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Co-Authors (by relevance)

  • Llontop, Paul
  • Lizarraga Olivares, Kevin
  • Piñeiro, Miguel
  • Korte, Lars
  • M., Luis A. Enrique
  • Tejada Esteves, Alvaro
  • Zarria-Romero, Jacquelyne Y.
  • Ramos Guivar, Juan Adrian
  • Castro-Merino, Isabel-Liz
  • Mejia, María Del Carmen
  • Camargo, Magali
  • Rumiche, Francisco
  • Tejada, Alvaro
  • Bund, Andreas
  • Sánchez, Luis Francisco
  • Eggert, Lara
  • Díaz, Isabel
  • Grieseler, Rolf
  • Kurniawan, Mario
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article

Capacitance voltage curve simulations for different passivation parameters of dielectric layers on silicon

  • Torres, Jorge Andres Guerra
Abstract

<jats:title>Abstract</jats:title><jats:p>Surface passivation is a widely used technique to reduce the recombination losses at the semiconductor surface. The passivating layer performance can be mainly characterized by two parameters: The fixed charge density (<jats:italic>Q</jats:italic><jats:sub>ox</jats:sub>) and the interface trap density (<jats:italic>D</jats:italic><jats:sub>it</jats:sub>) which can be extracted from Capacitance-Voltage measurements (CV). In this paper, simulations of High-Frequency Capacitance-Voltage (HF-CV) curves were developed using simulated passivation parameters in order to examine the reliability of measured results. The <jats:italic>D</jats:italic><jats:sub>it</jats:sub> was modelled by two different sets of functions: First, the sum of Gaussian functions representing different dangling bond types and exponential tails for strained bonds. Second, a simpler U-shape model represented by the sum of exponential tails and a constant value function was employed. These simulations were validated using experimental measurements of a reference sample based on silicon dioxide on crystalline silicon (SiO<jats:sub>2</jats:sub>/c-Si). Additionally, a fitting process of HF-CV curves was proposed using the simple U-shape <jats:italic>D</jats:italic><jats:sub>it</jats:sub> model. A relative error of less than 0.4% was found comparing the average values between the approximated and the experimentally extracted <jats:italic>D</jats:italic><jats:sub>it</jats:sub>’s. The constant function of the approximated <jats:italic>D</jats:italic><jats:sub>it</jats:sub> represents an average of the experimentally extracted <jats:italic>D</jats:italic><jats:sub>it</jats:sub> for values around the midgap energy where the recombination efficiency is highest.</jats:p>

Topics
  • density
  • impedance spectroscopy
  • surface
  • simulation
  • semiconductor
  • laser emission spectroscopy
  • Silicon