{"id":736,"date":"2011-06-09T23:07:00","date_gmt":"2011-06-10T04:07:00","guid":{"rendered":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/?post_type=wm_projects&p=736"},"modified":"2018-03-09T23:24:16","modified_gmt":"2018-03-10T04:24:16","slug":"dislocation-engineering-of-led-nanostructures","status":"publish","type":"wm_projects","link":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/project\/dislocation-engineering-of-led-nanostructures\/","title":{"rendered":"Dislocation Engineering of LED Nanostructures"},"content":{"rendered":"

\"\"<\/p>\n

Dislocation filtering in GaN by selective area growth through a nanoporous template is examined both by numerical modeling. These nanorods grow epitaxially from the (0001)-oriented GaN underlayer through the ~100 nm thick template and naturally terminate with hexagonal pyramid-shaped caps. It is demonstrated that, for a certain window of geometric parameters, a threading dislocation growing within a GaN nanorod is likely to be excluded by the strong image forces of the nearby free surfaces. A finite element-based implementation of the eigenstrain model was<\/p>\n

\"\"<\/p>\n

employed to corroborate the experimentally observed data and examine a larger range of potential nanorod geometries, providing a simple map of the different regimes of dislocation filtering for this class of GaN nanorods. These results indicate that nanostructured semiconductor materials are effective at eliminating deleterious extended defects, as necessary to enhance the optoelectronic performance and device lifetimes compared to conventional planar heterostructures.<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Dislocation filtering in GaN by selective area growth through a nanoporous template…<\/p>\n","protected":false},"author":1,"featured_media":737,"template":"","meta":{"advanced_seo_description":""},"project_category":[72,28],"project_tag":[],"jetpack_sharing_enabled":true,"jetpack_likes_enabled":true,"_links":{"self":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/wm_projects\/736"}],"collection":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/wm_projects"}],"about":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/types\/wm_projects"}],"author":[{"embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/users\/1"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/media\/737"}],"wp:attachment":[{"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/media?parent=736"}],"wp:term":[{"taxonomy":"project_category","embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/project_category?post=736"},{"taxonomy":"project_tag","embeddable":true,"href":"https:\/\/engineering.purdue.edu\/ComputationalMaterials\/index.php\/wp-json\/wp\/v2\/project_tag?post=736"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}