Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Artificial Intelligence speeds up photodynamics simulations

12.09.2019

Scientists use deep neural networks to achieve simulations on long time scales

The prediction of molecular reactions triggered by light is to date extremely time-consuming and therefore costly. A team led by Philipp Marquetand from the Faculty of Chemistry at the University of Vienna has now presented a method using artificial neural networks that drastically accelerates the simulation of light-induced processes.


Illustration to the study, which appeared on one of the covers of "Chemical Science": Artificial neural networks help to drastically accelerate simulations of photoinduced processes.

Credit: © Julia Westermayr, Philipp Marquetand

The method provides new possibilities for a better understanding of biological processes such as the first steps of carcinogenesis or ageing processes of matter. The study appeared in the current issue of the journal "Chemical Science", also including an accompanying illustration on one of its covers.

Machine learning plays an increasingly important role in chemical research, e.g. in the discovery and development of new molecules and materials. In this study, researchers from Vienna and Berlin show how artificial intelligence enables efficient photodynamics simulations.

To understand photo-induced processes, such as photosynthesis, human visual perception or skin cancer, "we need to understand the motion of molecules under the influence of UV light. In addition to classical mechanical calculations, we also need quantum mechanics that is computationally extremely demanding and therefore cost-intensive," says Philipp Marquetand, author of the study and scientist at the Institute of Theoretical Chemistry.

With previous methods, researchers were only able to predict the fastest photo-induced processes in the picosecond range (1 picosecond = 0.000 000 000 001 seconds) - with computation times of several months. The new method uses artificial intelligence to simulate over longer periods, in the range of one nanosecond (1,000 picoseconds), with considerably less computation time.

Learning neural networks

In their approach, the researchers use artificial neural networks, i.e. mathematical models that imitate the functioning of our brain. "We teach our neuronal network the complex quantum-mechanical relationships by performing a few calculations beforehand and passing the knowledge on to the neural network," says first study author and uni:docs fellow, Julia Westermayr from the Institute of Theoretical Chemistry. Based on its knowledge, the self-learning neural networks will then be able to predict what will happen more quickly.

As part of the study, the researchers carried out photodynamics simulations of a test molecule called methylenimmonium cation - a building block of the molecule retinal that enables our visual processes. "After two months of computing, we were able to reproduce the reaction for one nanosecond; based on previous methods, the simulation would have taken about 19 years," says PhD student Julia Westermayr.

A Proof of Concept

In the nanosecond range, the majority of photochemical processes take place: "With our strategy, we are entering a new dimension of prediction. In principle, the approach we are presenting can be applied to a wide range of smaller molecules, including DNA building blocks and amino acids," says Philipp Marquetand.

In the next step, the researchers want to use their method to describe the amino acid tyrosine. Tyrosine occurs in most proteins, and it is suspected to promote blindness and skin ageing after being damaged under the influence of light. According to the study authors, the presented strategy in general could foster better predictions of light-controlled processes in all respects, including material ageing and photosensitive drugs.

###

Publication in "Chemical Science"

Machine learning enables long time scale molecular photodynamics simulations, Michael Gastegger, Maximilian F. S. J. Menger, Sebastian Mai, Leticia González and Philipp Marquetand

Chemical Science, 2019.

https://doi.org/10.1039/C9SC01742A

Media Contact

Philipp Marquetand
philipp.marquetand@univie.ac.at
43-142-775-2764

 @univienna

http://www.univie.ac.at/en/ 

Philipp Marquetand | EurekAlert!
Further information:
https://medienportal.univie.ac.at/presse/aktuelle-pressemeldungen/detailansicht/artikel/from-years-to-days-artificial-intelligence-speeds-up-photodynamics-simulations/
http://dx.doi.org/10.1039/C9SC01742A

More articles from Information Technology:

nachricht Automated assembly system manufactures solid-state LIDAR systems for autonomous vehicles
12.09.2019 | Fraunhofer-Institut für Produktionstechnologie IPT

nachricht Important step towards European warning system: European Commission launches warning app
12.09.2019 | FOKUS - Fraunhofer-Institut für Offene Kommunikationssysteme

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Milestones on the Way to the Nuclear Clock

Two research teams have succeeded simultaneously in measuring the long-sought Thorium nuclear transition, which enables extremely precise nuclear clocks. TU Wien (Vienna) is part of both teams.

If you want to build the most accurate clock in the world, you need something that "ticks" very fast and extremely precise. In an atomic clock, electrons are...

Im Focus: Graphene sets the stage for the next generation of THz astronomy detectors

Researchers from Chalmers University of Technology have demonstrated a detector made from graphene that could revolutionize the sensors used in next-generation space telescopes. The findings were recently published in the scientific journal Nature Astronomy.

Beyond superconductors, there are few materials that can fulfill the requirements needed for making ultra-sensitive and fast terahertz (THz) detectors for...

Im Focus: Physicists from Stuttgart prove the existence of a supersolid state of matte

A supersolid is a state of matter that can be described in simplified terms as being solid and liquid at the same time. In recent years, extensive efforts have been devoted to the detection of this exotic quantum matter. A research team led by Tilman Pfau and Tim Langen at the 5th Institute of Physics of the University of Stuttgart has succeeded in proving experimentally that the long-sought supersolid state of matter exists. The researchers report their results in Nature magazine.

In our everyday lives, we are familiar with matter existing in three different states: solid, liquid, or gas. However, if matter is cooled down to extremely...

Im Focus: World record for tandem perovskite-CIGS solar cell

A team headed by Prof. Steve Albrecht from the HZB will present a new world-record tandem solar cell at EU PVSEC, the world's largest international photovoltaic and solar energy conference and exhibition, in Marseille, France on September 11, 2019. This tandem solar cell combines the semiconducting materials perovskite and CIGS and achieves a certified efficiency of 23.26 per cent. One reason for this success lies in the cell’s intermediate layer of organic molecules: they self-organise to cover even rough semiconductor surfaces. Two patents have been filed for these layers.

Perovskite-based solar cells have experienced an incredibly rapid increase in efficiency over the last ten years. The combination of perovskites with classical...

Im Focus: A molecular 'atlas' of animal development

Researchers from the University of Pennsylvania provide a molecular map of every cell in a developing animal embryo

In a paper in Science this week, Penn researchers report the first detailed molecular characterization of how every cell changes during animal embryonic...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

Society 5.0: putting humans at the heart of digitalisation

10.09.2019 | Event News

Interspeech 2019 conference: Alexa and Siri in Graz

04.09.2019 | Event News

AI for Laser Technology Conference: optimizing the use of lasers with artificial intelligence

29.08.2019 | Event News

 
Latest News

Artificial Intelligence speeds up photodynamics simulations

12.09.2019 | Information Technology

Automated assembly system manufactures solid-state LIDAR systems for autonomous vehicles

12.09.2019 | Information Technology

Important step towards European warning system: European Commission launches warning app

12.09.2019 | Information Technology

VideoLinks
Science & Research
Overview of more VideoLinks >>>