Department of Chemistry and Materials Science

AI-yarn project (Bioinnovation)

AI-guided biohybrid assembly platform for e-textiles (Aalto University Bioinnovation Center project)
AIyarn project main image. Photo by Aalto University / Matteo Iannacchero, Maija Vaara

Full title of the project: AI-guided biohybrid assembly platform for e-textiles (Aalto University Bioinnovation Center project)



Matteo Iannacchero, a developer of bio-based yarns: ‘I value the freedom of science’

In his doctoral research conducted at Aalto University’s Bioinnovation Center, Iannacchero uses machine learning to develop ecologically sustainable electronic yarns. This is an opportunity to come up with something completely new.

Biomaterial in water


Bioinnovation Center's research focuses on sustainable textiles and packaging. Currently we have eight research projects ongoing. Read more about the research projects here.

Aalto University Bioinnovation Center

More about the project:

Electronic textiles, e-textiles or smart textiles are terms that are interchangeably used for digitally enhanced fabrics. The electronic components in e-textiles augment their aesthetic appeal or enable new functionality, like wearable electronics. Common problems hindering the commercialization of current e-textiles are durability (e.g., brittleness), user discomfort due to integrated bulky electronics, and sustainability. In AIyarn, we address these challenges by developing novel biomaterial-based yarns for e-textiles. This will be done by combining nanocellulose and flexuous plant-virus nanoparticles (VNPs) into a fully bio-based assembly line for conductive and piezoelectric yarns. 

AIyarn creates a highly-controllable biohybrid assembly line for functional e-textile yarns. Monofilaments – combining nanocellulose and flexuous virus nanoparticles that can independently act as a co-assembly platform for other functionalities – are drawn, and multifunctional textile yarns are fabricated by spinning specifically selected monofilaments. With machine learning, we optimize the mechanical and functional properties (e.g., conductivity, piezoelectricity). We also devise a machine-learning-based materials discovery approach to find optimal carbon compounds for co-assembly. AIyarn will produce novel biomaterial yarns and deliver a first use-case of AI for bioinnovations. 

Interdisciplinary collaboration 

In AIyarn, two young PIs combine their complementary expertise in biomaterials and computer science for the first time in a funded project. In this interdisciplinary project, machine learning techniques facilitate and accelerate biomaterials synthesis. Machine learning unlocks unprecedented opportunities for materials and process optimization, unveils previously unseen correlations between materials characteristics and functional properties, and aids in the discovery of new compounds. 

Scientific or societal impact 

To the best of our knowledge, AIyarn would deliver the first functional biohybrid material for e-textiles and provide sustainable options of smart textiles. Scientifically, AIyarn establishes a new paradigm of AI-guided biomaterials research and accelerated materials development. 

Bioinnovation aspect and application potential 

As a fundamental interdisciplinary project, AIyarn enables completely bio-based functional conductive and piezoelectric yarns. We will also create an alternative for Ag-coated conductive yarns commonly applied in current e-textiles. We believe that our biohybrid platform will significantly improve the flexibility and durability of Ag nanowire-based conductive yarns. This opens new opportunities for the ever-growing application areas of e-textiles. 

Project team

Fiber structure formation exploiting interfacial complexation. Photo by Aalto University, Matteo Iannacchero
Fiber structure formation exploiting interfacial complexation / Photo: Aalto University, Matteo Iannacchero

Matteo Iannacchero, Doctoral Candidate

"I am currently working on the production of functionalised fibres suitable for the creation of e-textiles, but in general on the use of AI for the production of optimal materials. 

The goal of this project is precisely the combination of laboratory work (data acquisition) and machine learning (data processing) that allows artificial intelligence to predict the optimal reaction conditions to obtain the best desired properties.

The complexity of the use of AI depends on the number of variables involved, but it has an enormous advantage in the study of any reaction or process since it can discover the position, in an n-dimensional space of variables, of the points of greatest interest, i.e. those that can guarantee an optimised functional product."

Contact information

Project team: 
Doctoral Candidate Matteo Iannacchero (CHEM MMD) ([email protected])
Professor Jaana Vapaavuori (CHEM MMD) ([email protected])
Professor Patrick Rinke (SCI CEST) ([email protected])

Project intern: Azin Alesafar ([email protected])

This project is a project of the Aalto University Bioinnovation Center which focuses on innovations in sustainable bio-based materials, especially on textiles and packaging. Its target is to accelerate the transition to a circular economy and bioeconomy, and to create opportunities for sustainable economic growth in Finland. 

More about Bioinnovation Center's research

Related content:

Multifunctional Materials Design

Group led by Professor Jaana Vapaavuori

MMD webpage main image. GIF image by Aalto University, Giulnara Launonen

Computational Electronic Structure Theory (CEST)

CEST is developing electronic structure and machine learning methods and applying them to computational materials science problems.

CEST researchers standing in a group

Aalto University Bioinnovation Center

To achieve human wellbeing in planetary boundaries, we need new sustainable solutions to wisely use our natural resources. The Bioinnovation Center especially focuses on innovations in sustainable bio-based materials, with special focus on textiles and packaging.

Photo: Artistic paper sample

ModelCom project

Autonomously adapting and communicating modular textiles

ModelCom webpage, main image, nylon yarn helix. Photo by Aalto University, Maija Vaara

Beyond e-Textiles project

Nordic network on smart light-conversion textiles beyond electric circuits

Beyond e-Textiles webpage, main image. Image by Aalto University, Giulnara Launonen, Maija Vaara, Mithila Mohan
  • Published:
  • Updated: