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Results for “synthesis (scalable processing)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Thermoelectric power factor enhancement with gate-all-around silicon nanowires

The thermoelectric properties of gate-all-around silicon nanowires (Si NWs) are calculated to determine the potential for significant power factor enhancement. The Boltzmann transport equation and relaxation time approximation are employed to develop an electron transport model used to determine the field-effect mobility, electrical conductivity, Seebeck coefficient, and power factor for Si NWs with cross-sectional areas between 4 nm × 4 nm and 12 nm × 12 nm and a range of gate biases. Electrical conductivity for the gated Si NWs was much higher than that of doped Si due to the lack of ionized impurities and correspondingly greater carrier mobility. A significant increase in electrical conductivity with decreasing Si NW cross-sectional area was also observed due to a large increase in the average carrier density. For all Si NWs, the Seebeck coefficient was lower than that of doped bulk Si due to the different energy dependence between ionized impurity and phonon-mediated scattering processes. This decrease was also confirmed with Seebeck coefficient measurements of multigated Si NWs and n-type Si thin-films. Quantum confinement was also found to increase the Seebeck coefficient for <8 nm × 8 nm Si NWs and also at high charge densities. A maximum power factor of 6.8 × 10{sup −3} W m{sup −1} K{sup −2} was calculated for the 6 nm × 6 nm Si NWs with typical Si/SiO{sub 2} interface roughness, which is 2–3 × those obtained experimentally for bulk Si. The power factor was also found to greatly depend on surface roughness, with a root-mean-square roughness of <0.8 nm necessary for power factor enhancement. An increase in ZT may also be possible if a low thermal conductivity can be obtained with minimal surface roughness.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

First-principles study of vacancy-assisted impurity diffusion in ZnO

Group-III elements act as donors in ZnO when incorporated on the Zn site. Their incorporation and behavior upon annealing is governed by diffusion, which proceeds mainly through a vacancy-assisted process. We report first-principles calculations for the migration of Al, Ga, and In donors in ZnO, based on density functional theory using a hybrid functional. From the calculated migration barriers and formation energies, we determine diffusion activation energies and estimate annealing temperatures. Impurity-vacancy binding energies and migration barriers decrease from Al to In. Activation energies for vacancy-assisted diffusion are lowest for In and highest for Al.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Modeling Mesoscale Processes of Scalable Synthesis (Final Report)

The main objective of the center is to develop tools that can help for the understanding of equilibrium and non-equilibrium properties of nanoparticles in aqueous electrolytes. To achieve this goal, we need to develop new computational methodologies that can integrate molecular level description such as the electronic structure analysis to mesoscale description such as generalized hydrodynamics. The challenge is to develop systematic coarse graining techniques that can adaptively choose the level of description needed for the particular task. For example, if bonding breaking is involved, then one should use appropriate models from quantum mechanics to accurately model the time scale and molecular mechanism for the breaking process. However, to model transport process or the process of self-assembly, much less detailed models can be used. There are two main components to this task. One is to develop accurate models that bridge different levels of description. The classical example is the QM/MM model that bridges quantum mechanics and molecular mechanics for studying chemical reactions of large molecules. This work was awarded the Nobel prize this year. For our purpose, we also need to develop methods that bridge molecular and continuum levels of description. Another main task is to develop systematic coarse-graining methods that can give rise to accurate mesoscale and macroscale models, starting from more detailed models at the atomic or molecular scale. None of these ideas are new. By now they have been fashionable topics for quite some time. But neither problem is satisfactorily resolved. The main problem is that uncontrolled approximations are used. As a result, we have very little idea about the validity and accuracy of these models. The main purpose of the center is to exploit the Mori-Zwanzig formalism to achieve the goals stated above. The Mori-Zwanzig formalism is a general tool for eliminating degrees of freedom from existing models. What is attractive about this formalism is its generality. The flip side is that it is also somewhat of a tautology. In order to make it a practical tool, one has to make approximations and this is where the trouble comes. Instead of focusing on Mori-Zwanzig formalism, the PI proposes to study the closely related renormalization group formalism (RG). Like Mori-Zwanzig, RG is a general strategy for eliminating small scale degrees of freedom in a model. Unlike Mori-Zwanzig, RG has the advantage that at least for some problems, one can write a PDE (partial differential equation) type of model for the exact RG flow, without any approximation. This gives us a solid starting point for discussing and analyzing approximations. The PI studied approximate RG flows for turbulent diffusion and related problems. However, extending it to more practical problems proved to be hard. The second line that the PI has pursued is to develop special numerical algorithms for studying particularly important events for dynamics processes in meso-scale systems. The PI succeeded in doing so for the problem of understanding phase transition in metallic systems.

97 MATHEMATICS AND COMPUTING↗