The winning entries from the University of Cambridge department of engineering show that engineering beauty is all around us.

For some engineering inspiration, see the top three winners as well as winners in the contest’s subcategories, including micrograph captures with electron microscopes and the photo or video with the most innovative engineering story.

Shot in the Dark

1st Prize - Shot in the Dark. (Image courtsey of Rachel Garsed.)

Rachel Garsed’s striking photo of a bullet-hole pattern in liquid crystal took first place. The photo shows the effect of a strong electric field destroying the liquid crystal that it normally controls.

Titanium Comet Diaspora

2nd Prize - Titanium Comet Diaspora. (Image courtesy of Andrew Payne.)

Second place was awarded to Andrew Payne’s photo, taken from his attempts to join sapphire and steel to increase wear resistance. Payne used a laser as an energy source and a layer of titanium between the two materials to aid in bonding. The photo shows the edge of the irradiation zone, with flecks of titanium exploding off of the edge of the steel.

Vertically-Aligned Multi-Walled Carbon Nanotubes

3rd Prize - Vertically Aligned Multi-Walled Carbon Nanotubes. (Image courtesy of Dilek Ozgit and Andrea De Luca.)

The third-place winners, Dilek Ozgit and Andrea De Luca, submitted a micrograph of a “forest” of nanotubes grown on top of electrodes on a standard silicon platform. This allowed them to monitor the electrical properties of the forest as it developed.

Under the Covers

SEM Prize - Under the Covers. (Image courtesy of Kenichi Nakanishi.)

Kenichi Nakanishi won the scanning electron microscope (SEM) prize for a composite of four separate false-color electron micrographs depicting a three-dimensional shell of ceramic encapsulating layers of graphene.

How a Robot Tourist Would View Cambridge Landmarks

Head of Department's Prize - How a robot tourist would view Cambridge landmarks. (Image courtesy of Alex Kendall.)

Alex Kendall won the Head of Department’s prize for a demonstration of his system for taking single color images and reconstructing them in 3D. Kendall used this system to train an AI to localize its position and orientation around Cambridge using deep learning.

To see the other entries in the competition, visit the department of engineering’s website.