A film just 250 nanometers or 0.00025 mm thick has given scientists a glimpse of the superfast world (A super-fast world captured with ultra-thin films).
The film is made from transparent conductive oxides, a material commonly used for touchscreens and smartphone photovoltaic systems.
Nanophotoacoustics experts from the Heriot-Watt Institute of Quantum and Photonic Sciences have demonstrated that these materials can capture and measure ultrafast events much better than current systems.
This could (A super-fast world captured with ultra-thin films) lead to breakthroughs in many areas of science, including cell biology and chemistry, where reactions occur and must be recorded in a millionth of a billionth of a second. The results are reported in Nature Communications. Dr. Marcello Ferrera, assistant professor of nanophotoacoustics at Heriot-Watt University, led the work along with colleagues from the University of Glasgow and Purdue University in the United States.
“The ultrathin films we use are zero-index materials. Light behaves quite differently in these materials because the index of refraction, which is how we describe the interaction between light and matter, approaches zero. This is a condition that is very difficult to achieve with conventional materials. “This opens up a world of possibilities because when the index is very small, the material starts to be very sensitive to extremely fast light excitations.
“We have used this enhanced optical sensitivity in a frequency-resolved optical measurement system or a FROG system, which is one of the most fundamental tools for measuring the evolution of optical events. learn very fast.
“The end result is a significant improvement in all key metrics, including bandwidth, speed and power efficiency.”
Ferrera emphasizes that their new system is based on readily available and ready-to-use materials. This means that the technology can quickly move from the laboratory to the commercial application.
He points to another advantage of the system. “This new zero-index FROG reduces baseline power requirements and also provides a broader set of optical information that can be used in machine learning to improve power and accuracy when describing super fast events”.
