Fr. 57.50

Generation and manipulation of terahertz waves in carbon derivatives - DE

English · Paperback / Softback

Shipping usually within 2 to 3 weeks (title will be printed to order)

Description

Read more

Carbon-based nanomaterials are fascinating newcomers for generation, modulation, and detection of terahertz (THz) electromagnetic waves. The anticipated amplified emission in this spectral range from the graphene is yet to be observed while the linear energetic dispersion of monoatomic graphene restricts the electronic accelerations. On the other hand, in the case of graphite, the Fermi-level engineering is turned out to be useful in modifying the electrical transports via doping and interfacial work function offsets. In particular, the work function engineering among air, graphite, and metals allowed a viable route to tuning the graphitic energy profiles and manipulating the THz radiation features. The novel functionalized graphene structures have been synthesized e.g. holey graphene with nitrogen atoms being added into otherwise conventional graphene and can possibly be useful in controlling the transport properties.

About the author










Muhammad Irfan is an assistant professor of department of electrical engineering. Prior to joining KFUEIT, he was an assistant professor at UET, Lahore in the department of electrical engineering since 2008. He received his MS and Ph.D. in electrical engineering from GIST, South Korea in 2011 and 2016.

Product details

Authors Muhammad Irfan
Publisher LAP Lambert Academic Publishing
 
Languages English
Product format Paperback / Softback
Released 17.12.2024
 
EAN 9786208417536
ISBN 9786208417536
No. of pages 80
Subject Natural sciences, medicine, IT, technology > Physics, astronomy > Miscellaneous

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.