911

News

CSC and 911 team up to create a physicist AI

Published:
The Aalto research group Computational Electronic Structure Theory CEST granted 8M core hours from CSC – IT Center for Science
The incoming laser beam represents the spectroscopy process as it would proceed in an experiment in which the molecule in the center is excited by the beam. In the CSC Grand Challenge project the group calculated these excitation spectra with quantum mechanical methods. The resulting spectral data is symbolized by the 1s and 0s and is stored in a large molecular database for further processing with machine learning.

The  will construct an AI that learns from the plethora of
spectroscopic data already available in databases. Once trained, the
AI can make predictions of spectra instantly and at no further cost.
The CSC Grand Challenge award of 8M computer hours will allow the group to
create test spectroscopy datasets for developing, training and
testing the AI before it is ready for large-scale applications.

Spectroscopy probes the interaction between radiation and matter. It
is the primary method to scientifically study the laws of nature,
discover new phenomena and characterize the properties of substances
or materials.

Conventional spectroscopies are slow and expensive, often requiring
large facilities such as synchrotrons or supercomputers. In the
Department of Applied Physics, CEST run the "Artificial Intelligence
for Spectroscopy” project that employs deep learning neural
network-based artificial intelligence (AI) methods to harvest the
wealth of spectroscopic data that has already been recorded.

When deployed, AI spectroscopy would complement conventional
spectroscopy to greatly accelerate the analysis of materials, and
suggest better candidate materials to boost existing technologies
based around light absorption. For example, it could help design
more effective optical coatings or increase the power conversion
rates in solar cells.

More information:

Patrick Rinke, professor

patrick.rinke@aalto.fi

  • Updated:
  • Published:
Share
URL copied!

Read more news

See all
The 3 members from the Kenno team smiling at the camera in a picture selfie style
Campus, Research & Art, University Published:

The company established by three anthropologists relied on strong research expertise

Etnografinen tutkimustoimisto Kenno Oy was established in 2014 when its three founders were finalising their master's degree studies at the University of Helsinki and wanted to create an interesting job for themselves.
Four people in a meeting room watch a large screen showing charts and photos, with laptops on a long table.
Research & Art Published:

Bachelor's Students Successfully Complete Research Internship

Three bachelor's students have successfully completed their research internships.
Scientist in white coat and gloves examining wooden samples at a lab bench with shelves and equipment
Research & Art Published:

From Materials to Smart Textiles: Benjamin Begins a New Chapter at Aalto

Ping-Chun Chen is a researcher from National Tsing Hua University, Taiwan.
A group of people cheering with branded black cups. 4 people sitting, 2 on each side, and one in the middle standing up. 3 men and two women
Campus, Research & Art, University Published:

The idea of three researchers generated a deep tech company

Sim Analytics Oy relies on strong research expertise. Its story began when three researcher colleagues working in different laboratories at LUT University began to consider how to provide and analyse data in a way that would support industrial companies in making business decisions.
See all