معرفی
Joakim Jestilä serves as a Postdoctoral Researcher at Aalto University within the Department of Chemistry and Materials, actively contributing to the Inorganic Materials Modelling research group. His work integrates computational and experimental approaches to investigate atomic-scale material behaviors, with emphasis on surface phenomena and molecular interactions.
Research interests span computational chemistry, quantum physics, and machine learning applications in materials characterization. Key focus areas include carbohydrate self-assembly mechanisms, quantum spin systems in molecular rings, and lignocellulosic biomass adsorption. His methodologies combine scanning probe microscopy with deep learning for precise surface analysis, bridging theoretical modeling and experimental validation in nanoscale science.
Recent publications demonstrate interdisciplinary impact across chemistry, physics, and computer science domains. Work on chirality transfer in carbohydrates reveals stereochemical principles governing self-assembly, while quantum ring studies uncover many-body degeneracy phenomena. Machine learning applications enable accelerated adsorption structure determination and precise chemical transformations, highlighting convergence of AI with experimental surface science.
As part of Aalto University's Inorganic Materials Modelling group, Jestilä collaborates extensively with international researchers including Adam Foster and Peter Liljeroth. His work supports advanced materials design through fundamental insights into molecular interactions and surface processes, with implications for renewable energy and nanotechnology applications.