In celebration of National Nanotechnology Day in October, the RTNN and the National Nanotechnology Coordinated Infrastructure (NNCI) are hosting the Plenty of Beauty at the Bottom image contest. Referencing Richard Feynman’s 1959 lecture, There’s Plenty of Room at the Bottom, this image contest celebrates the beauty of the micro and nanoscale.
Submissions will be accepted from individuals or teams of two in a variety of categories. Images must have been acquired using instruments in RTNN facilities or be a result of data acquired using instruments in RTNN facilities within the past two years. The winning submissions for each category will be featured on the RTNN website, invited to attend an awards dinner (meal provided by RTNN!), and entered into the wider NNCI Image Competition. One image will also be selected as RTNN’s overall winner and receive a $50 Amazon gift card. Winners of the NNCI competition will have their images printed and framed and receive an award for conference travel!
Submissions will be accepted in the categories listed below. Each person/team may submit one image to each category. Image should be submitted in JPEG, PNG, or TIFF format at the highest resolution possible. All images must include a scale bar in or below the image.
- Most Stunning – beautiful images can use false color but the original image details should not be altered. Colorization of the image is not required for submission.
- Most Unique Capability – show off something that makes RTNN facilities stand out.
- Most Whimsical – visual illusion in art; for example, adding a boat to an SEM image that looks like the ocean
The submission deadline is September 10, 2024. If you have difficulty submitting through the linked form, please contact the RTNN at rtnanonetwork@ncsu.edu.
Note: Submitted images may be used by the RTNN and/or NNCI for promotional purposes. Your submission implies you have full author rights to submitted images and agree to give consent to the RTNN and NNCI for use of images.
If you have questions, please contact the RTNN at rtnanonetwork@ncsu.edu.
