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Evidence of a Proximity Effect in a  Mixture Using a Simulation Model Based on Random Variable Theory
Evidence of a Proximity Effect in a Mixture Using a Simulation Model Based on Random Variable Theory
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Evidence of a Proximity Effect in a Mixture Using a Simulation Model Based on Random Variable Theory
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Evidence of a Proximity Effect in a  Mixture Using a Simulation Model Based on Random Variable Theory
Evidence of a Proximity Effect in a Mixture Using a Simulation Model Based on Random Variable Theory

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Evidence of a Proximity Effect in a Mixture Using a Simulation Model Based on Random Variable Theory
Evidence of a Proximity Effect in a  Mixture Using a Simulation Model Based on Random Variable Theory
Journal Article

Evidence of a Proximity Effect in a Mixture Using a Simulation Model Based on Random Variable Theory

2024
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Overview
Silver iodide is a prototype compound of superionic conductors that allows ions to flow through its structure. It exhibits a first-order phase transition at 420 K, characterized by an abrupt change in its ionic conductivity behavior, and above this temperature, its ionic conductivity increases by more than three orders of magnitude. Introducing small concentrations of carbon into the silver iodide structure produces a new material with a mixed conductivity (ionic and electronic) that increases with increasing temperature. In this work, we report the experimental results of the ionic conductivity as a function of the reciprocal temperature for the (AgI)x − C[sub.(1−x)] mixture at low carbon concentrations (x = 0.99, 0.98, and 0.97). The ionic conductivity behavior as a function of reciprocal temperature was well fitted using a phenomenological model based on a random variable theory with a probability distribution function for the carriers. The experimental data show a proximity effect between the C and AgI phases. As a consequence of this proximity behavior, carbon concentration or temperature can control the conductivity of the (AgI)x − C[sub.(1−x)] mixture.