Energy characterization and instruction-level energy model of Intel's Xeon Phi processor

2013 ◽  
Author(s):  
Yakun Sophia Shao ◽  
David Brooks
Keyword(s):  
Energy Model ◽  
Level Energy ◽  
Xeon Phi

scholarly journals Statistical study of thermoradiative and photovoltaic cells based on a two-level model

2021 ◽  
Author(s):  
J. J. Fernández
Keyword(s):  
Statistical Study ◽  
Open Circuit Voltage ◽  
Chemical Potential ◽  
Photovoltaic Cells ◽  
Open Circuit ◽  
Energy Model ◽  
Conversion Process ◽  
Level Energy ◽  
Level Model ◽  
Two Level Model

AbstractWe use a two-level energy model to understand the conversion process that takes place in thermoradiative cells and to compare it with the conversion process that happens in photovoltaic cells. In this way, we show that in both kinds of converters the conversion process can be studied as the succession of a change in the populations of the levels that occur at constant chemical potential and a change in the value of the chemical potential of the two levels that happens while keeping their populations constant. As an application of the model, we will discuss why in thermoradiative cells the open-circuit voltage is negative while it is positive in photovoltaic cells. We also show that the expression for the open-circuit voltage is the same in both kinds of cells but that due to the values of the temperatures it is negative in thermoradiative cells and positive in photovoltaic ones.

scholarly journals System-level energy model for data transmission in wireless biomedical implantable systems

2018 ◽  
Vol 2018 (3) ◽  
pp. 147-154
Author(s):  
Mojtaba Daliri ◽  
Mohammad Maymandi-Nejad
Keyword(s):  
Data Transmission ◽  
Energy Model ◽  
System Level ◽  
Level Energy

scholarly journals Towards an Accurate High-Level Energy Model for LDPC Decoders

2021 ◽  
Author(s):  
Jeremy Nadal ◽  
Simon Brown ◽  
Elsa Dupraz ◽  
Francois Leduc-Primeau
Keyword(s):  
Energy Model ◽  
Level Energy ◽  
High Level

Hydrogen Atom Transfer Reaction Free Energy as a Predictor of Abiotic Nitroaromatic Reduction Rate Constants: A Comprehensive Analysis

2019 ◽  
Author(s):  
Dominic Di Toro ◽  
Kevin P. Hickey ◽  
Herbert E. Allen ◽  
Richard F. Carbonaro ◽  
Pei C. Chiu
Keyword(s):  
Free Energy ◽  
Hydrogen Atom ◽  
Hydrogen Atom Transfer ◽  
Energy Model ◽  
Second Order ◽  
Transfer Model ◽  
Atom Transfer ◽  
Order Rate ◽  
Linear Free Energy ◽  
Free Energy Model

<div>A linear free energy model is presented that predicts the second order rate constant for the abiotic reduction of nitroaromatic compounds (NACs). For this situation previously presented models use the one electron reduction potential of the NAC reaction. If such value is not available, it has been has been proposed that it could be computed directly or estimated from the electron affinity (EA). The model proposed herein uses the Gibbs free energy of the hydrogen atom transfer (HAT) as the parameter in the linear free energy model. Both models employ quantum chemical computations for the required thermodynamic parameters. The available and proposed models are compared using second order rate constants obtained from five investigations reported in the literature in which a variety of NACs were exposed to a variety of reductants. A comprehensive analysis utilizing all the NACs and reductants demonstrate that the computed hydrogen atom transfer model and the experimental one electron reduction potential model have similar root mean square errors and residual error probability distributions. In contrast, the model using the computed electron affinity has a more variable residual error distribution with a significant number of outliers. The results suggest that a linear free energy model utilizing computed hydrogen transfer reaction free energy produces a more reliable prediction of the NAC abiotic reduction second order rate constant than previously available methods. The advantages of the proposed hydrogen atom transfer model and its mechanistic implications are discussed as well.</div>

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