Hybridinanopartikkelien rakenteiden ennustaminen tekoälyä hyväksi käyttäen (HNP-AI)
Päärahoittaja
Rahoittajan antama koodi/diaarinumero: 315549
Päärahoittajan myöntämä tuki (€)
- 458 214,00
Rahoitusohjelma
Hankkeen aikataulu
Hankkeen aloituspäivämäärä: 01.01.2018
Hankkeen päättymispäivämäärä: 31.12.2021
Tiivistelmä
This project aims at new scientific breakthroughs in the area of computational research of nanomaterials, specifically developing newopen-source AI-based algorithms and software for reliable structural predictions of ambiently stable hybrid metal nanoparticles in the size range up to a few nanometers in diameter, and analyzing correlations in the experimental and computational nanoparticles'structure-property data. The improved understanding of nanoparticles' structure-property relationships and of the initial structures that dominate their nucleation mechanisms in solution helps to design more stable, functional nanoparticles for various applications. The new software can be used in other areas of nanomaterials research for improved structure prediction and structure-property research.The project is a collaboration between Academy Prof. Hannu Häkkinen at the Jyväskylä University (JYU) Nanoscience Center and
Prof. Tommi Kärkkäinen at the IT Faculty of JYU.
Prof. Tommi Kärkkäinen at the IT Faculty of JYU.
Vastuullinen johtaja
Muut hankkeeseen liittyvät henkilöt (JYU)
Päävastuullinen yksikkö
Liittyvät julkaisut
- Cubic aromaticity in ligand-stabilized doped Au superatoms (2021) López-Estrada, Omar; et al.; A1; OA
- Magnetically induced currents and aromaticity in ligand-stabilized Au and AuPt superatoms (2021) López-Estrada, Omar; et al.; A1; OA
- Prospects and challenges for computer simulations of monolayer-protected metal clusters (2021) Malola, Sami; et al.; B1; OA
- [Pt2Cu34(PET)22Cl4]2–: An Atomically Precise, 10-Electron PtCu Bimetal Nanocluster with a Direct Pt–Pt Bond (2021) Lee, Sanghwa; et al.; A1
- Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods (2020) Pihlajamäki, Antti; et al.; A1; OA
- Solubility‐Driven Isolation of a Metastable Nonagold Cluster with Body‐Centered Cubic Structure (2020) Shen, Hui; et al.; A1; OA
- A method for structure prediction of metal-ligand interfaces of hybrid nanoparticles (2019) Malola, Sami; et al.; A1; OA
- Chiral Inversion of Thiolate-Protected Gold Nanoclusters via Core Reconstruction without Breaking an Au-S Bond (2019) Malola, Sami; et al.; A1; OA
- Real-space imaging with pattern recognition of a ligand-protected Ag374 nanocluster at sub-molecular resolution (2018) Zhou, Qin; et al.; A1; OA
