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News, Computational Electronic Structure Theory (CEST), Computational Electronic Structure Theory (CEST)
New Academy projects will investigate drug development, superconductivity and emotional game experience
There are altogether 12 new Academy of Finland projects at the Aalto School of Science. Funding was received from all the three Academy of Finland Research Councils: Biosciences, Health and the Environment, Culture and Society and Natural Sciences and Engineering.
Novel cross-disciplinary approach for identifying complex molecular adsorbates
CEST researchers integrate Bayesian inference with scanning probe experiments to robustly detect surface adsorbate configurations.
CEST research acknowledged at the E-MRS Spring Meeting 2021
Jari Järvi wins the Best Poster Award at the annual Spring Meeting of the European Materials Research Society
Emil Aaltonen Foundation Grant Awarded to CEST researcher Jari Järvi
Jari Järvi receives PhD fellowship from the Emil Aaltonen Foundation
New machine learning approach speeds up search for molecular conformers
A new method based on machine learning facilitates search for molecular conformers
CEST researchers pave the way for calculating circular dichroism (CD) spectra more efficiently
New study by CEST group implements an efficient method for calculating CD spectra in open source GPAW code
A computational deep glance at 2-dimensional MXene materials reveals new insight about their surface properties
New computational study looks at surface functionalization of 2-dimensional materials class
Method yielding more accurate total energies could boost quantum chemistry calculations
CEST researchers publish new method calculating total energies efficiently and accurately
Finnish Cultural Foundation awards Kunal Ghosh with PhD grant
Kunal Ghosh (CEST group) was awarded a Finnish Cultural Foundation grant for his doctoral studies
Theoretical study elucidates deep surface structure of emerging perovskite material
Newly published work by doctoral candidate Azimatu Seidu (CEST group) reveals detailed electronic and atomistic structure of cesium lead triiodide (CsPbI3), an emerging perovskite material
Computational physics graduate Lauri Himanen selected for SCI Dissertation Award
Lauri Himanen (CEST & SIN groups) was one of two awardees at the Department of Applied Physics for a SCI Dissertation Award
Levi Keller wins Finnish Cultural Foundation award for doctoral studies
Levi Keller (CEST group) was awarded a grant from the Finnish Cultural Foundation to support his doctoral studies exploring computational methods for spectroscopy.
Computational physicist Dorothea Golze receives prestigious Emmy Noether Award
Dorothea Golze received funding from the German Research Foundation within the Emmy Noether Programme to establish her own junior research group at the Technical University of Dresden.
Discovering new materials in data
FCAI member Milica Todorović uses computational methods for material science, training AI on her field's vast databases to speed up the search for tomorrow's functional materials.
CEST group wins supercomputing Grand Challenge
The CEST group has won a CSC grand supercomputing challenge to run projects in 2021.
Azimatu Seidu has won a grant from the Finnish Academy of Science and Letters
Azimatu successfully applies Density Functional Theory (DFT) to screen vast combinations of different materials which find potential application in perovskite-based photovoltaic devices.
Artificial intelligence helps to identify correct atomic structures
Detecting adsorbate configurations with Bayesian inference.
Simple accuracy boost for core excitation calculations
Relativistic corrections that are important for core excitations in molecules and materials are incorporated in complex quantum mechanical calculations in an efficient manner.
Deciphering the structure of nanosystems with machine learning
The CEST group joins forces with a team in Austria to solve a long-standing puzzle in nanoscience.
Patrick Rinke awarded Academy of Finland funding
The LearnSolar project receives funding for machine-learning based discovery of new solar cell materials.
