柠檬导航

News

A Flexible Biorefinery using Machine Learning

Biorefineries convert biomass, such as wood, annual plants or agricultural into products and energy. Research teams in Finland and Germany aim to maximize such product output for a more holistic valorization of our natural resources. The development of these new processes is often slow because they require optimization of many factors. The integration of artificial intelligence (AI) can help us accelerate such a development drastically.
A hand in a blue glove holding a spherical glass flask with a cork, containing a brown, grainy substance.
Isolated lignin-carbohydrate complexes to be tested for new applications. Photo: Aalto University

A multidisciplinary consortium of researchers at Aalto University and 脜bo Akademi in Finland, and at Technical University Munich in Germany, are developing a flexible biorefinery concept to exploit the unique synergism of lignin-carbohydrate complexes (LCCs), which are naturally found in wood, to produce fully bio-based antioxidants, effective surfactants and polymer additives. LCCs are indispensable components of the wood cell wall, providing wood its rigidity and structure. In classical pulping processes, LCCs are disintegrated to isolate cellulose, hemicellulose and lignin. Within the consortium project 鈥淎I-4-LCC: Exploiting Lignin-Carbohydrate Complex through Artificial Intelligence鈥 funded by the Research Council of Finland, the teams of late Professor of Practice Mikhail Balakshin (鈥2022, Aalto University), Prof. Patrick Rinke (Aalto University, Technical University of Munich) and Prof. Chunlin Xu (脜bo Akademi) have developed a process to produce LCCs with tailored properties and high yield.

The new process is based on a modified hydrothermal treatment of wood followed by solvent extraction of the resulting solids, named AquaSolv Omni (AqSO) by Balakshin. The properties of the LCCs can be adjusted precisely by tuning the process conditions. Researchers from Rinke鈥檚 group employed Bayesian Optimization to iteratively collect data points of interest and evaluate the impact of the process conditions (P-factor, temperature, and liquid-to-solid ratio) on yield and carbohydrate content. Incorporation of Pareto front analysis allowed the team to maximize both yield and carbohydrate content. To evaluate LCC鈥檚 potential for high-value applications, the antioxidant potential, surface tension and glass transition temperature were measured in close collaboration with experts from Xu鈥檚 group of biomass chemists. The joint effort was recently published in the prestigious journal ChemSusChem: . 

Doctoral candidate Daryna Diment explains: 鈥淗igh carbohydrate content of LCCs was found beneficial for reducing the glass transition temperature and surface tension of aqueous solutions, implying its potential use in thermoplastic formulations and as bio-based surfactants.LCCs produced in severe processing conditions (high temperature and extensive time) demonstrated a remarkable antioxidant activity.鈥

Overall, the developed idea represents an unparalleled advantage over traditional biorefineries for LCC isolation because it involves only water, temperature, and acetone extraction. On top of that, Bayesian Optimization provided flexibility to produce LCCs with targeted properties in high yield. This work demonstrates the potential of LCCs as a novel biorefinery product and showcases how machine learning can be used to accelerate the development of new technologies to valorize local and natural resources.

More information:

Enhancing Lignin-Carbohydrate Complexes Production and Properties with Machine Learning in ChemSusChem by Diment et al.  

  • Updated:
  • Published:
Share
URL copied!

Read more news

A person in black touches a large stone sculpture outside a brick building under a blue sky.
Campus, Research & Art, University Published:

Glitch artwork challenges to see art in a different light

Laura K枚n枚nen's sculpture was unveiled on 14 October at the Otaniemi campus.
Book cover of 'Nanoparticles Integrated Functional Textiles' edited by Md. Reazuddin Repon, Daiva Miku膷ioniene, and Aminoddin Haji.
Research & Art Published:

Nanoparticles in Functional Textiles

Dr. Md. Reazuddin Repon, Postdoctoral Researcher at the Textile Chemistry Group, Department of Bioproducts and Biosystems, Aalto University, has contributed as an editor to a newly published academic volume titled 鈥淣anoparticles Integrated Functional Textiles鈥.
Person standing outdoors in autumn, wearing a grey hoodie and green jacket. Trees in the background with orange leaves.
Appointments Published:

Introducing Qi Chen: Trustworthy AI requires algorithms that can handle unexpected situations

AI developers must focus on safer and fairer AI methods, as the trust and equality of societies are at stake, says new ELLIS Institute Finland principal investigator Qi Chen
A person wearing a light grey hoodie stands indoors with a brick wall and green plants in the background.
Appointments, University Published:

The research puzzle of when humans and AI don鈥檛 see eye to eye

Francesco Croce works on robustness in multi-modal foundation models