Surfaces and Interfaces at the Nanoscale (SIN)

Currently at bat:

• Captain (at tea) - Prof. Adam Foster
• Leg slip - Dr. Orlando Silveira Júnior
• Gully - Lauri Kurki
• Extra cover - Dr. Joakim Jestilä
• First slip - Dr. Nian Wu
• Mid off - Farzin Irandoost
• Third slip - Jie Huang
• Long off - Dr. Nan Cao
• Deep mid on - Azin Alesafar

Affiliated:

• Wicket keeper - Dr. Filippo Leonida Federici Canova (Nanolayers Ltd.)
• Third man - Dr. Niko Oinonen (Nanolayers Ltd.)

Previous innings:

• Janne Viertävä - stumped 31
• Petri Lehtinen - caught at slip 56
• Yuchen Ma - bowled middle and leg 39
• Timo Ahlberg - run out 13
• Pilvi Saaristo - caught at long on 32
• Toma Susi - played on 21 (University of Vienna)
• Gustav Bårdsen - caught at second slip 9 (Helsinki University of Technology)
• Olli Pakarinen - bowled off 84 (Helsinki University)
• Arkady Krasheninnikov - not out 111 (Helmholtz-Zentrum Dresden-Rossendorf)
• Henri Pinto - run out 49 (Yachay Tech University, Ecuador)
• Jozsef Hegedus - caught at midwicket 26 (Helsinki University of Technology)
• Iina Vainio - leg before wicket 19 (Tampere University)
• Mikko Hakala - bowled off and middle 63 (Aalto University)
• Sampsa Riikonen - caught at silly mid off 24 (University of Helsinki)
• Ariane Raschke - stumped 17 (Tampere University of Technology)
• Janak Sapkota - caught Wicketkeeper 21
• Martin Zeleny - caught at second slip 26 (Brno University of Technology)
• Eeva Niemi - leg before wicket 31 (Tampere University of Technology)
• Ville Raappana - bowled middle 16 (Aalto University)
• Filippo Leonida Federici Canova - handled the ball 69 (Nanolayers Ltd)
• Oski Kervinen - caught at first slip 23 (Tampere University of Technology)
• Bernhard Reischl - timed out after lunch 99 (University of Helsinki)
• Niniko Samadashvili - caught at long on 37 (in a bar somewhere)
• Teemu Hynninen - bowled middle and leg 273 (Turku University)
• Sampo Kulju - caught at second slip 41 (Tampere University of Technology)
• Jiang-Cheng Chen - run out 37 (The Shop, Helsinki)
• Olli Keisanen - bowled off 32 (Aalto University)
• Mustafa Lokhandwala - stumped 22 (Indian Institute of Technology, Bombay)
• Marissa Abreu - caught at square leg 13
• Hugo Pinto - run out 53 (Nordic Investment Bank)
• Peter Spijker - caught at cow corner 119 (Foundation for Fundamental Research on Matter)
• Prakhar Agrawal - bowled middle and leg 19 (Indian Institute of Technology Delhi, India)
• Naveen Sundar - leg before wicket 27 (Indian Institute of Technology Delhi, India)
• Kajetan Stanski - caught at midoff 23 (University of Glasgow, UK)
• Sami Kivistö - caught at first slip 21 (Aalto University)
• Simiam Ghan - bowled off 26 (Technical University of Munich, Germany)
• Tiziana Musso - leg before wicket 54 (Zurich University, Switzerland)
• Juha Ritala - caught at third man 41 (Futusome Oy)
• Eero Holmström - run out 87 (Natural Resources Institute Finland)
• Dhananjay Varma - caught at cover 19 (Indian Institute of Technology Delhi, India)
• Aniket Ninawe - stumped 15 (Indian Institute of Technology Dhanbad, India)
• Martha Arbayani - leg before wicket 43 (Helsinki University)
• Tobias Reisch - bowled off 23 (Technische Universität Wien, Austria)
• Jayesh Mahapatra - caught at long on 17 (Veer Surendra Sai University of Technology, Burla, India)
• John Tracey - retired hurt (sunburn) 57 (Aurora Computer Services)
• Ville Haapasilta - bowled leg 71 (YLE)
• Lidija Zivanovic - caught at midoff 43 (Fortum)
• Antti Autio - caught at fourth slip 19 (Helsinki University)
• Amara McCune - leg before wicket 14 (Stanford University)
• Fabio Priante - stumped 18 (Università dell'Aquila)
• Petri Määttä - bowled off 24 (Aalto University)
• Eiaki Morooka - handled the ball 33 (Helsinki)
• Prokop Hapala - caught at long on 43 (Czech Academy of Sciences)
• Lauri Kurki - caught at gully 27 (Helsinki University)
• Lauri Himanen - leg before wicket 79 (Software Consultancy)
• Stavrina Dimosthenous - bowled middle 27
• Lei Yang - caught wicket-keeper 53 (Shenzhen HUASUAN Technology)
• Marc Jäger - caught at first slip 61 (SellForte)
• Nico Toikka - bowled leg 15 (Helsinki University)
• Atte Martikainen - caught at long off 14 (Helsinki University)
• Rebekka Kirchgässner - leg before wicket 21 (Karlsruhe Institute of Technology)
• Fedor Urtiev - caught at leg slip 77 (Nokia)
• Ishan Phansalkar - bowled off 11 (Aalto University)
• Ondrej Krejci - hit the ball twice 68 (Aalto University)
• Ygor Jaques - run out 43 (Aalto University)
• Darina Andriychenko - caught at first slip 14 (Cambridge University)
• Lorenzo Piersante - leg before wicket 12 (Oxford University)
• Henri Willems - caught at long on 21 (Technische Universität Berlin)
• Eric Kramer - bowled leg 17 (University of Barcelona)
• I-Ju Chen - caught at square leg 44 (IMEC)
• Yashasvi Ranawat - caught at first slip 74 (IPRally)
• Panu Korpela - timed out 33 (Helsinki University)
• Leonel Cabrera - caught at second slip 21 (Yachay Tech University)
• Gregor Lauter - caught at point 19 (Heidelberg University)
• Fabio Priante - caught at long on 83 (Aalto University)
• Markus Junttila - leg before wicket 27 (Aalto University)

  Confused...education is at hand, explore the beautiful game.

Many technological applications depend crucially on surface rather than bulk material properties, and the study of surfaces has become an important field within condensed matter physics. A few prominent examples are immediately evident – the environmental degradation of high-Tc superconductors; bonding between grains of alumina in sintered ceramics; passivation of metal surfaces against corrosion; biomedical substrates; improving and designing new solid-state gas sensors for pollution monitoring and control; studying electrode/electrolyte interfaces in fuel cells.

In microelectronics, the ability to produce and control almost atomically perfect silicon surfaces has allowed the interface engineering crucial in fabricating transistors at the nanoscale – and this control of surface properties remains a crucial element in the development of the next generation of microelectronic devices. More recently, increased confidence in manipulation and fabrication of atomic structures on surfaces has opened the field of nano or molecular electronics and magnetism, with great technological potential. In each of these cases, and in many other applications where surface properties are important, understanding and controlling surface and interface physics at the atomic scale is the fundamental developmental goal required for optimization and, in cases like nanoelectronics, realization.

We are very active in the simulation of Scanning Probe Microscopy (SPM), particularly Atomic Force Microscopy (AFM), Scanning Tunneling Microscopy (STM) and Kelvin Probe Force Microscopy (KPFM). In general, experimental studies of surfaces with atomic resolution are often difficult to interpret and simulations provide a link between measured images and surface topography and electronic structure. SPM techniques can be applied to the study of a wide variety of systems, including ideal and defective surfaces, molecular adsorbates, organic films, DNA, proteins, and the corresponding theoretical toolbox is equally wide.

Surface science techniques, and particularly high-resolution Scanning Probe Microscopy (SPM) approaches, now offer unprecedented levels of understanding and control of solid/vacuum interfaces. By contrast, the physics of liquid/solid interfaces is less developed, although it is often more relevant for real-world applications. It is important in such diverse fields as heterogeneous catalysis, next generation battery technology and corrosion. The solid/liquid interface is also particularly relevant to biological systems, where measurements are made in physiological conditions. In this work we apply a combination of first principles and atomistic simulation approaches to study how liquids interact with a variety of insulating and organic surfaces, providing atomic-scale insight into hydration structures, dissolution, friction and high-resolution imaging.

“Big data” and “Machine Learning” have become buzz words in information technology. Big data refers to data sets that are so large that traditional ways of human information processing can no longer process them. Instead, machine learning techniques are being developed for computer-aided data processing, and they now permeate ever growing parts of society, industry and market economies. In collaboration with computational science groups and international data repositories, we are developing the infrastructure to gather, analyse and mine data produced by entire materials science communities – building up the technology to analyze large data sets (big data) and create the tools that add value (materials informatics and machine learning). We are developing these tools to support all of our research focus areas.

As the scaling of the CMOS devices approaches its technological and fundamental limits, the replacement of silicon and its native oxide becomes one of the key challenges to sustain the continuous improvement of the IC performance. New semiconductors and dielectrics are at the heart of development of new and emerging high performance nanoelectronic devices. We use multiscale atomistic modelling to study the structure of interfaces and probable defects in next-generation materials, including devices based on 2D materials and molecular assemblies. This work also involves the development of methods for simulating thousands of atoms with high accuracy.

Scanning Probe Microscopy (SPM) has become a dominant tool for the design and activation of nanodevices. SPM direct mechanical manipulation can be used to build nanosystems piece by piece. It relies on locally changing the migration barriers by close-approach with the SPM tip pushing or pulling the molecule. This offers local control of molecular properties, and is in principle viable for any system. More importantly, SPM provides in situ high-resolution characterization, allowing direct observation of the dynamics even at the atomic scale. As well as being a tool for nanomanipulation, SPM provides a direct measure of the energy dissipated at the nanocontact between tip and cluster, and offers insight into the energy loss due to friction during manipulation. 

You can get our most useful software from GitHub.

Some movies based on our research:

• Kelvin Probe Force Microscopy (Ondrej Krecji)
• Nanoparticle manipulation (Teemu Hynninen)

Part of the SIN group went on tour in Japan from 12th to 27th November 2011. They visited six universities, covering over 2500 Km by train and presented over 20 seminars. See the tour site for details.

SIN was involved in the organization of the following meetings:

• Progress in anisotropic wet chemical etching
• Towards Reality in Nanoscale Materials 2007
• Towards Reality in Nanoscale Materials 2008
• Computational Nanoscience for Renewable Energy Solutions
• Towards Reality in Nanoscale Materials 2009
• 1st European Nanomanipulation Workshop 2010
• Spring College on Computational Nanoscience 2010
• Towards Reality in Nanoscale Materials 2010
• Towards Reality in Nanoscale Materials V
• 2nd European Nanomanipulation Workshop 2011
• Physics Boat Workshop 2012
• Towards Reality in Nanoscale Materials VI
• Physics Boat Workshop 2013
• Towards Reality in Nanoscale Materials VII
• Physics Boat Workshop 2014
• Physics Boat Workshop 2015
• Towards Reality in Nanoscale Materials VIII
• Autumn School in Computational Physics: From Electrons to Large Blobs of Matter
• Physics Boat Workshop 2016
• Autumn School in Computational Physics: Why Free Energy Matters and How to Compute It
• Towards Reality in Nanoscale Materials IX
• International Workshop on Machine Learning for Materials Science 2018
• Non-contact Atomic Force Microscopy 2018
• MAINZ Summer School "Investigating Solid-Liquid Interfaces – Complementary Theoretical and Experimental Approaches"
• Towards Reality in Nanoscale Materials X
• Physics Boat Workshop 2019
• The 1st International Conference on Big Data and Machine Learning in Microscopy
• Winter School 2020 "Investigating Solid-Liquid Interfaces: The Calcite-Water Interface at the Molecular Level" 
• Big Data and Machine Learning in Microscopy 2024 (MLMII)
• Towards Rationality in Two-Dimensional Nanomaterials 2025 (TRNM XI)

SIN has been involved in the following large international projects:

• Modelling of the reliability and degradation of next generation nanoelectronic devices (MORDRED) – coordinator (2011-2015) - Final reports
• Planar Atomic and Molec­u­lar Scale devices (PAMS) – work package leader (2013 – 2017)
• The Novel Materials Discovery Laboratory (NOMAD) – partner (2015 – 2018)
• Rational design of future catalyst materials (CritCat) - work package leader (2016 - 2019)
• Nano Life Science Institute (NanoLSI), Kanazawa, Japan - PI (2017 - 2027)

PhD theses produced in the group:

• Magnetic nature of intrinsic carbon defects – Petri Lehtinen
• Scanning force microscopy simulations of nanoparticles on insulating surfaces – Olli Pakarinen
• Simulating atomic processes in Non-contact Atomic Force Microscopy of ionic surfaces – Filippo Federici Canova
• Atomistic Simulations of Solid-Liquid Interfaces – Bernhard Reischl
• Atomic and electronic transport on surfaces and interfaces – Mikko Hakala
• Nanoscale Friction of Ice – Nino Samadashvili
• Simulation of functional interfaces - Tiziana Musso
• Simulating atomic force microscopy at the solid- liquid interface - John Tracey
• Structural and dynamic properties of the solid-liquid interfaces studied by Molecular Dynamics simulations - Lidija Zivanovic
• Materials Informatics - Augmenting Materials Research with Data-driven Design and Machine Learning - Lauri Himanen
• Efficient screening of nanoclusters as catalysts for the hydrogen evolution reaction - Marc Jäger
• Simulating molecular adsorption on dielectric surfaces with classical MD, DFT and machine learning - Yashasvi Ranawat
• Automating high-resolution atomic force microscopy image interpretation - Niko Oinonen