SP-LCC — a dataset on the structure and properties of lignin-carbohydrate complexes from hardwood

M. Alopaeus; M. Stosiek; D. Diment; J. Löfgren; M. Cho; J. Hemming; T. Tirri; A. Pranovich; P.C. Eklund; D. Rigo; M. Balakshin; C. Xu; P. Rinke

doi:10.1038/s41597-025-05327-8

SP-LCC — a dataset on the structure and properties of lignin-carbohydrate complexes from hardwood

M. Alopaeus
, M. Stosiek
, D. Diment
, J. Löfgren
, M. Cho
, J. Hemming
, T. Tirri
, A. Pranovich
, P.C. Eklund
, D. Rigo
, M. Balakshin
, C. Xu^*
, P. Rinke

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Lehtiartikkeli › Artikkeli › Tieteellinen › vertaisarvioitu

4 Sitaatiot (Scopus)

41 Lataukset (Pure)

Abstrakti

Lignin-carbohydrate complexes (LCCs) are bioproducts with high potential as alternatives for petrochemicals. However, the complex structure and the lack of protocols for high-yield production limit their usage. Herein, we present data collected from a comprehensive artificial intelligence (AI)-guided optimization of the AquaSolv Omni (AqSO) biorefinery process targeting high-yield production of LCCs. The resulting database, termed SP-LCC, includes structural information extracted from nuclear magnetic resonance measurements (NMR) and data on the molar mass distribution, antioxidant activity, glass transition temperature, thermal degradation, and surface tension. In total, we collected data for 95 LCC-containing samples isolated for different AqSO process conditions. SP-LCC provides a holistic dataset for LCC development, materials understanding, and exploiting the LCC valorization potential. Furthermore, SP-LCC provides valuable data for training machine learning models for further optimization of biorefineries outside the scope of AqSO.

Alkuperäiskieli	Englanti
Artikkeli	996
Julkaisu	Scientific Data
Vuosikerta	12
Numero	1
DOI - pysyväislinkit	https://doi.org/10.1038/s41597-025-05327-8
Tila	Julkaistu - 13 kesäk. 2025
OKM-julkaisutyyppi	A1 Julkaistu artikkeli, soviteltu

Rahoitus

The authors gratefully acknowledge the Research Council of Finland for the support through the project No. 316601, 341589, and 341596/2021, the FinnCEREs BioEconomy flagship, and the Finnish Center for Artificial Intelligence (FCAI). Parts of this work were conducted within the Research Council of Finland Research Infrastructure “Printed Intelligence Infrastructure” (PII-FIRI). In addition, we acknowledge the Aalto Science-IT project and the Aalto Materials Digitalization (AMAD) platform.

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SDG 9 – Teollisuus, innovaatiot ja infrastruktuuri

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10.1038/s41597-025-05327-8Lisenssi: CC BY

s41597-025-05327-8Lopullinen julkaistu versio, 2,66 MBLisenssi: CC BY

https://urn.fi/URN:NBN:fi-fe2025090894806

Muut tiedostot ja linkit

https://www.scopus.com/pages/publications/105008220617

Åbo Akademi Functional Printing Center
Toivakka, M. (PI), Rosenholm, J. (PI), Anttu, N. (PI), Bobacka, J. (PI), Huynh, T. P. (PI), Peltonen, J. (PI), Wang, X. (PI), Wilen, C.-E. (PI), Xu, C. (PI), Zhang, H. (PI) & Österbacka, R. (PI)
Luonnontieteiden ja tekniikan tiedekunta
Laitteistot/tilat: Laitos

Viittausmuodot

@article{8fe55b1af3434e5f94766eeba9354679,

title = "SP-LCC {\textemdash} a dataset on the structure and properties of lignin-carbohydrate complexes from hardwood",

abstract = "Lignin-carbohydrate complexes (LCCs) are bioproducts with high potential as alternatives for petrochemicals. However, the complex structure and the lack of protocols for high-yield production limit their usage. Herein, we present data collected from a comprehensive artificial intelligence (AI)-guided optimization of the AquaSolv Omni (AqSO) biorefinery process targeting high-yield production of LCCs. The resulting database, termed SP-LCC, includes structural information extracted from nuclear magnetic resonance measurements (NMR) and data on the molar mass distribution, antioxidant activity, glass transition temperature, thermal degradation, and surface tension. In total, we collected data for 95 LCC-containing samples isolated for different AqSO process conditions. SP-LCC provides a holistic dataset for LCC development, materials understanding, and exploiting the LCC valorization potential. Furthermore, SP-LCC provides valuable data for training machine learning models for further optimization of biorefineries outside the scope of AqSO.",

author = "M. Alopaeus and M. Stosiek and D. Diment and J. L{\"o}fgren and M. Cho and J. Hemming and T. Tirri and A. Pranovich and P.C. Eklund and D. Rigo and M. Balakshin and C. Xu and P. Rinke",

year = "2025",

month = jun,

day = "13",

doi = "10.1038/s41597-025-05327-8",

language = "English",

volume = "12",

journal = "Scientific Data",

issn = "2052-4463",

publisher = "Nature Research",

number = "1",

}

TY - JOUR

T1 - SP-LCC — a dataset on the structure and properties of lignin-carbohydrate complexes from hardwood

AU - Alopaeus, M.

AU - Stosiek, M.

AU - Diment, D.

AU - Löfgren, J.

AU - Cho, M.

AU - Hemming, J.

AU - Tirri, T.

AU - Pranovich, A.

AU - Eklund, P.C.

AU - Rigo, D.

AU - Balakshin, M.

AU - Xu, C.

AU - Rinke, P.

PY - 2025/6/13

Y1 - 2025/6/13

N2 - Lignin-carbohydrate complexes (LCCs) are bioproducts with high potential as alternatives for petrochemicals. However, the complex structure and the lack of protocols for high-yield production limit their usage. Herein, we present data collected from a comprehensive artificial intelligence (AI)-guided optimization of the AquaSolv Omni (AqSO) biorefinery process targeting high-yield production of LCCs. The resulting database, termed SP-LCC, includes structural information extracted from nuclear magnetic resonance measurements (NMR) and data on the molar mass distribution, antioxidant activity, glass transition temperature, thermal degradation, and surface tension. In total, we collected data for 95 LCC-containing samples isolated for different AqSO process conditions. SP-LCC provides a holistic dataset for LCC development, materials understanding, and exploiting the LCC valorization potential. Furthermore, SP-LCC provides valuable data for training machine learning models for further optimization of biorefineries outside the scope of AqSO.

AB - Lignin-carbohydrate complexes (LCCs) are bioproducts with high potential as alternatives for petrochemicals. However, the complex structure and the lack of protocols for high-yield production limit their usage. Herein, we present data collected from a comprehensive artificial intelligence (AI)-guided optimization of the AquaSolv Omni (AqSO) biorefinery process targeting high-yield production of LCCs. The resulting database, termed SP-LCC, includes structural information extracted from nuclear magnetic resonance measurements (NMR) and data on the molar mass distribution, antioxidant activity, glass transition temperature, thermal degradation, and surface tension. In total, we collected data for 95 LCC-containing samples isolated for different AqSO process conditions. SP-LCC provides a holistic dataset for LCC development, materials understanding, and exploiting the LCC valorization potential. Furthermore, SP-LCC provides valuable data for training machine learning models for further optimization of biorefineries outside the scope of AqSO.

UR - https://www.scopus.com/pages/publications/105008220617

U2 - 10.1038/s41597-025-05327-8

DO - 10.1038/s41597-025-05327-8

M3 - Article

SN - 2052-4463

VL - 12

JO - Scientific Data

JF - Scientific Data

IS - 1

M1 - 996

ER -

SP-LCC — a dataset on the structure and properties of lignin-carbohydrate complexes from hardwood

Abstrakti

Rahoitus

YK:n kestävän kehityksen tavoitteet

Pääsy asiakirjaan

Muut tiedostot ja linkit

Sormenjälki

Laitteet

Åbo Akademi Functional Printing Center

Viittausmuodot