scholarly journals Enhancing a Layout-Aware Synthesis Methodology for Analog ICs by Embedding Statistical Knowledge into the Evolutionary Optimization Kernel

Author(s):  
Frederico Rocha ◽  
Ricardo Martins ◽  
Nuno Lourenço ◽  
Nuno Horta

2007 ◽  
Author(s):  
Heather L. Silvio ◽  
Catherine Romero ◽  
Ray Hays


2020 ◽  
Author(s):  
Olivier Charles Gagné

The scarcity of nitrogen in Earth’s crust, combined with challenging synthesis, have made inorganic nitrides a relatively-unexplored class of compounds compared to their naturally-abundant oxide counterparts. To facilitate exploration of their compositional space via <i>a priori</i> modeling, and to help <i>a posteriori</i> structure verification not limited to inferring the oxidation state of redox-active cations, we derive a suite of bond-valence parameters and Lewis-acid strength values for 76 cations observed bonding to N<sup>3-</sup>, and further outline a baseline statistical knowledge of bond lengths for these compounds. We examine structural and electronic effects responsible for the functional properties and anomalous bonding behavior of inorganic nitrides, and identify promising venues for exploring uncharted compositional spaces beyond the reach of high-throughput computational methods. We find that many mechanisms of bond-length variation ubiquitous to oxide and oxysalt compounds (e.g., lone-pair stereoactivity, the Jahn-Teller and pseudo Jahn-Teller effects) are similarly pervasive in inorganic nitrides, and are occasionally observed to result in greater distortion magnitude than their oxide counterparts. We identify inorganic nitrides with multiply-bonded metal ions as a promising venue in heterogeneous catalysis, e.g. in the development of a post-Haber-Bosch process proceeding at milder reaction conditions, thus representing further opportunity in the thriving exploration of the functional properties of this emerging class of materials.<br>





Author(s):  
I. N. Belezyakov ◽  
K. G. Arakancev

At present time there is a need to develop a methodology for electric motors design which will ensure the optimality of their geometrical parameters according to one or a set of criterias. With the growth of computer calculating power it becomes possible to develop methods based on numerical methods for electric machines computing. The article describes method of a singlecriterion evolutionary optimization of synchronous electric machines with permanent magnets taking into account the given restrictions on the overall dimensions and characteristics of structural materials. The described approach is based on applying of a genetic algorithm for carrying out evolutionary optimization of geometric parameters of a given configuration of electric motor. Optimization criteria may be different, but in automatic control systems high requirements are imposed to electromagnetic torque electric machine produces. During genetic algorithm work it optimizes given geometric parameters of the electric motor according to the criterion of its torque value, which is being calculated using finite element method.



2021 ◽  
Author(s):  
Yaochu Jin ◽  
Handing Wang ◽  
Chaoli Sun


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