Physicist Matthias Kling studies photons and the things science can do with ultrafast pulses of X-rays. These pulses last just attoseconds – a billionth of a billionth of a second, Kling says. He uses them to create slo-mo “movies” of electrons moving through materials like those used in batteries and solar cells. The gained knowledge could reshape fields like materials science, ultrafast and quantum computers, AI, and medical diagnostics, Kling tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to thefutureofeverything@stanford.edu.

Episode Reference Links:

• SStanford Profile: Matthias Kling
• Matthias’ Lab: SLAC National Accelerator Laboratory

Connect With Us:

• Episode Transcripts >>> The Future of Everything Website
• Connect with Russ >>> Threads or Twitter/X
• Connect with School of Engineering >>> Twitter/X

Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Matthias Kling, a professor of photon science and applied physics at Stanford University.

(00:02:52) Ultrafast Electronics Overview

The technologies enabling ultrafast photonics and electronic advancements.

(00:05:32) Attosecond Science Applications

Capturing electron and molecular movements with attosecond pulses.

(00:09:31) Photoelectric Effect Insights

Attosecond science’s impact on understanding the photoelectric effect and quantum mechanics.

(00:13:27) Real-Time Molecular Measurements

Using light waves to capture images of molecules at room temperature.

(00:19:32) Future of Ultrafast Electronics

How attosecond light pulses could revolutionize computing with petahertz speed.

(00:23:28) Energy-Efficient Quantum Computing

Potential for room-temperature quantum computers using light wave electronics.

(00:26:33) AI and Machine Learning in Science

AI's role in optimizing research and data collection in ultrafast electronics.

(00:28:51) Real-Time AI Data Analysis

Machine learning enables real-time analysis of massive experimental data.

(00:32:15) Conclusion

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>> Twitter/X