A5066257421- Force Microscopy Techniques and Applications
- Machine Learning in Materials Science
- Graphene research and applications
- Advanced Materials Characterization Techniques
- Surface and Thin Film Phenomena
- Surface Chemistry and Catalysis
- Topological Materials and Phenomena
- Electron and X-Ray Spectroscopy Techniques
- 2D Materials and Applications
- Molecular Junctions and Nanostructures
- Integrated Circuits and Semiconductor Failure Analysis
- Carbon Nanotubes in Composites
- Mechanical and Optical Resonators
- Neural Networks and Applications
- Ion-surface interactions and analysis
- Quantum many-body systems
- Advanced Electron Microscopy Techniques and Applications
- Metal-Organic Frameworks: Synthesis and Applications
Aalto University
2019-2022
Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing atomic structure of organic molecules on surfaces. Most experiments have been limited to nearly planar aromatic due difficulties interpretation highly distorted AFM images originating from nonplanar molecules. Here, we develop a deep learning infrastructure that matches set unique descriptor characterizing molecular configuration, allowing us predict directly. We...
Abstract Achieving large‐area uniform 2D metal‐organic frameworks (MOFs) and controlling their electronic properties on inert surfaces is a big step toward future applications in devices. Here monolayer Cu‐dicyanoanthracene MOF with long‐range order successfully fabricated an epitaxial graphene surface. Its structural are studied by low‐temperature scanning tunneling microscopy spectroscopy complemented density‐functional theory calculations. Access to multiple molecular charge states the...
The combination of two-dimensional (2D) materials into vertical heterostructures has emerged as a promising path to designer quantum with exotic properties. Here, we extend this concept from inorganic 2D metal-organic frameworks (MOFs) that offer additional flexibility in realizing heterostructures. We successfully fabricate monolayer Cu-dicyanoanthracene MOF on van der Waals NbSe2 superconducting substrate. structural and electronic properties two different phases the are characterized by...
Auto-CO-AFM is an open-source software package for scanning probe microscopes that enables the automatic functionalization of tips with carbon monoxide molecules. This machine operators to specify quality tip needed utilizing a pre-trained library off-the-shelf software. From single image, can determine which molecules on surface are monoxide, perform necessary procedures, interface microscope control position, and determines centeredness after successful functionalization. particular...
While offering unprecedented resolution of atomic and electronic structure, Scanning Probe Microscopy techniques have found greater challenges in providing reliable electrostatic characterization at the same scale. In this work, we introduce Electrostatic Discovery Atomic Force Microscopy, a machine learning based method which provides immediate quantitative maps potential directly from images with functionalized tips. We apply to characterize properties variety molecular systems compare...
Controlling the properties of organic/inorganic materials requires detailed knowledge their molecular adsorption geometries. This is often unattainable, even with current state-of-the-art tools. Visualizing structure complex non-planar adsorbates atomic force microscopy (AFM) challenging, and identifying it computationally intractable conventional search. In this fresh approach, cross-disciplinary tools are integrated for a robust automated identification 3D adsorbate configurations....
On-surface metal-organic coordination provides a promising way for synthesizing different two-dimensional lattice structures that have been predicted to possess exotic electronic properties. Using scanning tunneling microscopy (STM) and spectroscopy (STS), we studied the supramolecular self-assembly of 9,10-dicyanoanthracene (DCA) molecules on Au(111) surface. Close-packed islands DCA Au-DCA coexist Ordered DCA$_{3}$Au$_{2}$ networks structure combining honeycomb Au atoms with kagome...
Abstract Controlling the properties of organic/inorganic materials requires detailed knowledge their molecular adsorption geometries. This is often unattainable, even with current state-of-the-art tools. Visualizing structure complex non-planar adsorbates atomic force microscopy (AFM) challenging, and identifying it computationally intractable conventional search. In a fresh approach, we propose to integrate cross-disciplinary tools for robust automated identification 3D adsorbate...
Bayesian Inference In article number 2010853, Patrick Rinke and co-workers combine artificial intelligence enhanced ab-initio structure search with atomic force microscopy simulations (SIM) experiments (EXP) to detect configurations of bulky 3D adsorbates. inference is employed identify distinct stable adsorption (1S)-camphor on the Cu(111) surface, followed by SIM-EXP image feature matching fingerprint multiple experimental structures.
Abstract Controlling the properties of organic/inorganic materials requires detailed knowledge their molecular adsorption geometries. This is often unattainable, even with current state-of-the-art tools. Visualizing structure complex non-planar adsorbates atomic force microscopy (AFM) challenging, and identifying it computationally intractable conventional search. In a fresh approach, we propose to integrate cross-disciplinary tools for robust automated identification 3D adsorbate...