Publications

3 Results
Skip to search filters

Thermal Infrared Detectors: expanding performance limits using ultrafast electron microscopy

Talin, A.A.; Ellis, Scott R.; Bartelt, Norman C.; Leonard, Francois L.; Perez, Christopher P.; Celio, Km C.; Fuller, Elliot J.; Hughart, David R.; Garland, Diana; Marinella, Matthew J.; Michael, Joseph R.; Chandler, D.W.; Young, Steve M.; Smith, Sean M.; Kumar, Suhas K.

This project aimed to identify the performance-limiting mechanisms in mid- to far infrared (IR) sensors by probing photogenerated free carrier dynamics in model detector materials using scanning ultrafast electron microscopy (SUEM). SUEM is a recently developed method based on using ultrafast electron pulses in combination with optical excitations in a pump- probe configuration to examine charge dynamics with high spatial and temporal resolution and without the need for microfabrication. Five material systems were examined using SUEM in this project: polycrystalline lead zirconium titanate (a pyroelectric), polycrystalline vanadium dioxide (a bolometric material), GaAs (near IR), InAs (mid IR), and Si/SiO 2 system as a prototypical system for interface charge dynamics. The report provides detailed results for the Si/SiO 2 and the lead zirconium titanate systems.

More Details

Quantum mechanical studies of carbon structures

Ward, Donald K.; Zhou, Xiaowang Z.; Bartelt, Norman C.; Foster, Michael E.; Schultz, Peter A.; Wang, Bryan M.; McCarty, Kevin F.

Carbon nanostructures, such as nanotubes and graphene, are of considerable interest due to their unique mechanical and electrical properties. The materials exhibit extremely high strength and conductivity when defects created during synthesis are minimized. Atomistic modeling is one technique for high resolution studies of defect formation and mitigation. To enable simulations of the mechanical behavior and growth mechanisms of C nanostructures, a high-fidelity analytical bond-order potential for the C is needed. To generate inputs for developing such a potential, we performed quantum mechanical calculations of various C structures.

More Details

Predicting growth of graphene nanostructures using high-fidelity atomistic simulations

Bartelt, Norman C.; McCarty, Keven F.; Foster, Michael E.; Schultz, Peter A.; Zhou, Xiaowang Z.; Ward, Donald K.

In this project we developed t he atomistic models needed to predict how graphene grows when carbon is deposited on metal and semiconductor surfaces. We first calculated energies of many carbon configurations using first principles electronic structure calculations and then used these energies to construct an empirical bond order potentials that enable s comprehensive molecular dynamics simulation of growth. We validated our approach by comparing our predictions to experiments of graphene growth on Ir, Cu and Ge. The robustness of ou r understanding of graphene growth will enable high quality graphene to be grown on novel substrates which will expand the number of potential types of graphene electronic devices.

More Details
3 Results
3 Results