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A new version of Aaltodoc publication archive now available

Aaltodoc is updated to a new version, hence the appearance of the user interface has changed.
image of Aaltodoc main page

The purpose of is to ensure a long-term preservation of electronic theses and publications of Aalto University. In addition to theses and publications the self-archived versions of the articles published in the scientific journals as well as conference papers are also stored in Aaltodoc. 

Aaltodoc contains the metadata of theses and publication. Full-text file is available if the author has given a permission for the electronic publishing of the full-text. The publications stored in the archive have a permanent URN identifier. about the service.

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Modern exhibition room with mannequins in green and white clothes, bowls and a beige bathtub on white plinths
Research & Art Published:

Finnish wood-based innovations on display in London

The exhibition showcases Finnish bioeconomy solutions for both industry and everyday consumer life. Origami-based FOLD materials offer more sustainable solutions not only for packaging but also for many other applications.
White panel radiator on a light wall beside a wooden-framed glass door with city view
Research & Art Published:

Energy poverty is not recognized in Finland

According to a recent study by Aalto University and the Finnish Environment Institute, about 7–15 percent of Finnish households are energy poor, which at most means around 300,000 homes.
Person from behind in dark coat with large embroidered scene of kneeling figure on dramatic black background
Research & Art Published:

The exhibition "Our land, for all" explores personal and national identity

The 20th anniversary exhibition of the Association of Finnish Fine Arts Foundations, opened at Kunsthalle Helsinki, asks: whose stories is Finland built from? The exhibition has been curated by PhD, docent Annamari Vänskä.
Left: person wearing a black jacket and pearl necklace. Right: molecular structure illustration against a cosmic background.
Research & Art Published:

Decoding the chemistry of space with machine learning

Astronomers can detect complex chemical fingerprints in stardust – but many of them remain unidentified. The SpaceML project combines machine learning and computational chemistry to simulate how molecules form and evolve in space, helping researchers decode these signals.