Development of a Thermal Conductivity Prediction Simulators Based on the Effects of Electron Conduction and Lattice Vibration

Kabasawa

Ouchi

et al. 2008

MSF

Self Cite

The main electronic characteristics of silicon carbide (SiC) are its wide energy gap, high thermal conductivity, and high break down electric field which make of it of one of the most appropriate materials for power electronic devices. Previously we reported on a new electrical conductivity evaluation method for nano-scale complex systems based on our original tight-binding quantum chemical molecular dynamics method. In this work, we report on the application of our methodology to various SiC polytypes. The electrical conductivity obtained for perfect crystal models of 3C-, 6H- and 4H-SiC, were equal to 10-20-10-25 S/cm. For the defect including model an extremely large electrical conductivity (of the order of 102 S/cm) was obtained. Consequently these results lead to the conclusion that the 3C-, 6H-, and 4H-SiC polytypes with perfect crystals have insulator properties while the electrical conductivity of the crystal with defect, increases significantly. This result infers that crystals containing defects easily undergo electric breakdown.

Section: Computational Methodologymentioning

confidence: 99%

Computational Evaluation of Electrical Conductivity on SiC and the Influence of Crystal Defects

Kabasawa

Ouchi

et al. 2008

MSF

Self Cite

“…Preliminary relaxation calculation was performed at 273 K by classical molecular dynamics as described in a previous report. 12) To compute the Seebeck coefficient by means of eq. ( 3), the density of states was firstly calculated using the tightbinding quantum chemical molecular dynamics program Colors.…”

Section: Resultsmentioning

confidence: 99%

“…This methodology enables us to perform fast and accurate quantum chemical molecular dynamics simulations. 11,12) This underscores the importance of the Colors systems in calculations for largescale complex systems and thermoelectric materials as compared with other systems.…”

Section: Methodsmentioning

confidence: 93%

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Development of A Seebeck Coefficient Prediction Simulator Using Tight-Binding Quantum Chemical Molecular Dynamics

Ogiya

Chutia

et al. 2008

jjap

Self Cite

Technologies oriented to the development of thermoelectric materials are of great interest because they can assist in directly tapping the vast reserves of currently underused thermal energy. To improve the rational design of high-performance thermoelectric materials, a new numerical procedure for prediction of Seebeck coefficient based on the electronic information from tight-binding quantum chemical molecular dynamics method, has been developed. The newly developed simulator can evaluate Seebeck coefficient theoretically. The simulator is used for the prediction of the Seebeck coefficients for Pt and Si that are the representative materials for metals and semiconductors, respectively. The results show that both coefficients are in quantitative agreement with experimental data, i.e. in the case of Pt metal the predicted value is 5.62 mV/K while the experimental is À4:45 mV/K. Similarly, in the case of Si semiconductor the predicted value is À324:48 mV/K while the experimental is 300 -400 mV/K. This new developed simulator can be used to guide the rational design of high performance thermoelectric materials.

“…The classical MD calculation was performed using the ''New-Ryudo'' system, developed in our laboratories. 23,24) The system can solve the motion equation for large sets of atoms; furthermore in this MD simulation system the Verlet algorithm 25) is adopted to integrate the equation of motion. Moreover, the temperature scaling method implemented in the system is similar to the Woodcock algorithm.…”

Section: Methodsmentioning

confidence: 99%

Development of a Multi-Scale Electromigration Simulator Based on a Combination of Ultra Accelerated Quantum Chemical Molecular Dynamics and Kinetic Monte Carlo Methods Application to Cu Interconnects Lifetime Simulation

Kato

Sato

et al. 2009

jjap

Self Cite

We present a novel study on electromigration (EM) phenomena in Cu interconnects using a newly developed multi-scale simulator that consists on a combination of a device scale simulator based on a kinetic Monte Carlo (KMC) method and an atomic scale simulator based on ultra accelerated quantum chemical molecular dynamics (UA-QCMD). We have firstly demonstrated the simulation of the lifetime of Cu interconnects using the newly developed device scale simulator setting some suitable KMC probabilities for the void movement according to the regions in which it can be divided, i.e., the crystal grain and the grain boundary. The simulated values are shown to be in good agreement with experimental values. In an attempt to connect the device scale studies to quantum chemical instances of the system -since the correlation of probability of the void movement with, for example, activation energies or diffusion coefficients is important -we have developed an atomic scale simulator based on our original UA-QCMD method. In this atomic scale simulation, the electron wind force was evaluated using our original electrical conductivity prediction simulator based on KMC method which uses the electronic states from tight-binding quantum chemical (TBQC) calculation. Using this atomic scale simulator under the conditions of 475 K of temperature and 2:5 Â 10 10 A/m 2 of current density, we were able to successfully simulate the migration of a Cu atom from a lattice site to a vacant site by evaluating the electron wind force.