Department of Applied Physics

Computational Electronic Structure Theory (CEST)

The Computational Electronic Structure Theory Group is developing electronic structure and machine learning methods and applies them to pertinent problems in material science, surface science, physics, chemistry and the nano sciences.
CEST researchers standing in a group
Back row from left: P. Henkel, J. Löfgren, M. Stosiek, J. Järvi, O. Krejci; middle: A. Tiihonen, E. Lehto, M. Marques, V. Havu, H. Sandström, M. Iannacchero, J. Laakso; front: L. Fang, F. Delesma, P. Pisal, N. Bhatia, P. Rinke, K. Ghosh


Latest Publications

Ferrofluidic Manipulator : Theoretical Model for Single-Particle Velocity

Zoran M. Cenev, Ville Havu, Jaakko V.I. Timonen, Quan Zhou 2023 IEEE/ASME Transactions on Mechatronics

Core-Selective Silver-Doping of Gold Nanoclusters by Surface-Bound Sulphates on Colloidal Templates: From Synthetic Mechanism to Relaxation Dynamics

Sourov Chandra, Alice Sciortino, Shruti Shandilya, Lincan Fang, Xi Chen, Hua Jiang, Leena Sisko Johansson, Marco Cannas, Janne Ruokolainen, Robin H.A. Ras, Fabrizio Messina, Bo Peng, Olli Ikkala 2023 ADVANCED OPTICAL MATERIALS

Gold Au(I)6 Clusters with Ligand-Derived Atomic Steric Locking: Multifunctional Optoelectrical Properties and Quantum Coherence

Sourov Chandra, Alice Sciortino, Susobhan Das, Faisal Ahmed, Arijit Jana, Jayoti Roy, Diao Li, Ville Liljeström, Hua Jiang, Leena Sisko Johansson, Xi Chen, Marco Cannas, Thalappil Pradeep, Bo Peng, Robin H.A. Ras, Zhipei Sun, Olli Ikkala, Fabrizio Messina 2023 ADVANCED OPTICAL MATERIALS

An Alternative to the Born Rule : Spectral Quantization

Marc Dvorak 2023 Foundations of Physics

Exploring the Conformers of an Organic Molecule on a Metal Cluster with Bayesian Optimization

Lincan Fang, Xiaomi Guo, Milica Todorovic, Patrick Rinke, Xi Chen 2023 JOURNAL OF CHEMICAL INFORMATION AND MODELING

Differences in Molecular Adsorption Emanating from the (2 × 1) Reconstruction of Calcite(104)

Jonas Heggemann, Yashasvi S. Ranawat, Ondřej Krejčí, Adam S. Foster, Philipp Rahe 2023 Journal of Physical Chemistry Letters

Role of CsMnCl3 Nanocrystal Structure on Its Luminescence Properties

Anastasia Matuhina, G. Krishnamurthy Grandhi, Fang Pan, Maning Liu, Harri Ali-Löytty, Hussein M. Ayedh, Antti Tukiainen, Jan-Henrik Smått, Ville Vähänissi, Hele Savin, Jingrui Li, Patrick Rinke, Paola Vivo 2023 ACS Applied Nano Materials

Single-Atom Dopants in Plasmonic Nanocatalysts

Daniel Sorvisto, Patrick Rinke, Tuomas P. Rossi 2023 Journal of Physical Chemistry C

On-surface synthesis of disilabenzene-bridged covalent organic frameworks

Kewei Sun, Orlando J. Silveira, Yujing Ma, Yuri Hasegawa, Michio Matsumoto, Satoshi Kera, Ondřej Krejčí, Adam S. Foster, Shigeki Kawai 2023 NATURE CHEMISTRY
More information on our research in the Research database.
Research database

Research Group Members

Group Leader


 Ville Havu

Ville Havu

Senior University Lecturer

Postdoctoral Researchers

Doctoral, Master Students and Research Assistants

 Lincan Fang

Lincan Fang

Doctoral Candidate

Henrietta Homm

Research Assistant

Emma Lehto

Research Assistant

Visiting Researchers

 Xi Chen

Xi Chen

Visiting Researcher
 Marc Dvorak

Marc Dvorak

Visiting Researcher (HRL Laboratories)
 Dorothea Golze

Dorothea Golze

Visiting Researcher (TU Dresden)

Marcelo Marques

Visiting Professor (Instituto Tecnológico de Aeronáutica, Brazil)
 Tuomas Rossi

Tuomas Rossi

Visiting Researcher
 Milica Todorovic

Milica Todorovic

Visiting Researcher (Turku University)


Graphic illustration of materials science, AI and physics with equations, B&W photos and a photo of prof. Rinke.
Research & Art Published:

Prof. Patrick Rinke: making sustainable materials with AI

Professor Patrick Rinke’s pioneering expertise in finding sustainable and climate-friendly materials with machine learning methodology has arguably never been more in demand
Research & Art Published:

Matteo Iannacchero, a developer of bio-based yarns: ‘I value the freedom of science’

In his doctoral research conducted at Aalto University’s Bioinnovation Center, Iannacchero uses machine learning to develop ecologically sustainable electronic yarns. This is an opportunity to come up with something completely new.
A solar panel with blue sky and a graphic showing perovskite material
Research & Art Published:

Machine learning boosts the discovery of new perovskite solar cell materials

Researchers from CEST group apply machine learning to help identifying suitable solar cell materials
Image of neuromorphic circuits
Research & Art Published:

Prof. Patrick Rinke Awarded Academy Grant for Developing Biologically Inspired Computing Systems

Prof. Rinke’s three-year joint project with VTT aims to make demanding AI computing tasks use less power while maintaining performance.

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