222 citations · 834 across the 21 of their papers we have counts for
21 papers
Deep learning-enhanced Lagrangian 3D Tracking of motile microorganisms
Thierry Darnige, Daniel Midtvedt, Renaud Baillou +5
How microorganisms respond to and interact with their environment can vary significantly from individual to individual, which can have important microbiological and ecological impl…
Latent Space-Driven Quantification of Biofilm Formation using Time Resolved Droplet Microfluidics
Daniela Pérez Guerrero, Jesús Manuel Antúnez Domínguez, Aurélie Vigne +5
Bacterial biofilms play a significant role in various fields that impact our daily lives, from detrimental public health hazards to beneficial applications in bioremediation, biode…
Optical Label-Free Microscopy Characterization of Dielectric Nanoparticles
Berenice Garcia Rodriguez, Erik Olsén, Fredrik Skärberg +3
In order to relate nanoparticle properties to function, fast and detailed particle characterization, is needed. The ability to characterize nanoparticle samples using optical micro…
Deep-learning-powered data analysis in plankton ecology
Harshith Bachimanchi, Matthew I. M. Pinder, Chloé Robert +6
The implementation of deep learning algorithms has brought new perspectives to plankton ecology. Emerging as an alternative approach to established methods, deep learning offers ob…
Label-free optical quantification of material composition of suspended virus-gold nanoparticle complexes
Erik Olsén, Benjamin Midtvedt, Adrián González +7
The interaction between metallic and biological nanoparticles (NPs) is widely used in various biotechnology and biomedical applications. However, detailed characterization of this…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Single-shot self-supervised particle tracking
Benjamin Midtvedt, Jesús Pineda, Fredrik Skärberg +8
Particle tracking is a fundamental task in digital microscopy. Recently, machine-learning approaches have made great strides in overcoming the limitations of more classical approac…
Microplankton life histories revealed by holographic microscopy and deep learning
Harshith Bachimanchi, Benjamin Midtvedt, Daniel Midtvedt +2
The marine microbial food web plays a central role in the global carbon cycle. Our mechanistic understanding of the ocean, however, is biased towards its larger constituents, while…
Geometric deep learning reveals the spatiotemporal fingerprint of microscopic motion
Jesús Pineda, Benjamin Midtvedt, Harshith Bachimanchi +4
The characterization of dynamical processes in living systems provides important clues for their mechanistic interpretation and link to biological functions. Thanks to recent advan…
Extracting quantitative biological information from brightfield cell images using deep learning
Saga Helgadottir, Benjamin Midtvedt, Jesús Pineda +5
Quantitative analysis of cell structures is essential for biomedical and pharmaceutical research. The standard imaging approach relies on fluorescence microscopy, where cell struct…
Quantitative Digital Microscopy with Deep Learning
Benjamin Midtvedt, Saga Helgadottir, Aykut Argun +3
Video microscopy has a long history of providing insights and breakthroughs for a broad range of disciplines, from physics to biology. Image analysis to extract quantitative inform…
Holographic characterisation of subwavelength particles enhanced by deep learning
Benjamin Midtvedt, Erik Olsén, Fredrik Eklund +4
The characterisation of the physical properties of nanoparticles in their native environment plays a central role in a wide range of fields, from nanoparticle-enhanced drug deliver…
Multi-scale approach for strain-engineering of phosphorene
Daniel Midtvedt, Caio H. Lewenkopf, Alexander Croy
A multi-scale approach for the theoretical description of deformed phosphorene is presented. This approach combines a valence-force model to relate macroscopic strain to microscopi…
Valence force model and nanomechanics of single-layer phosphorene
Daniel Midtvedt, Alexander Croy
In order to understand the relation of strain and material properties, both a microscopic model connecting a given strain to the displacement of atoms, and a macroscopic model rela…
Strain-displacement relations and strain engineering in 2d materials
Daniel Midtvedt, Caio H. Lewenkopf, Alexander Croy
We investigate the electromechanical coupling in 2d materials. For non-Bravais lattices, we find important corrections to the standard macroscopic strain - microscopic atomic-displ…
Strain-tuning of vacancy-induced magnetism in graphene nanoribbons
Daniel Midtvedt, Alexander Croy
Vacancies in graphene lead to the appearance of localized electronic states with non-vanishing spin moments. Using a mean-field Hubbard model and an effective double-quantum dot de…
Nonlinear phononics using atomically thin membranes
Daniel Midtvedt, Andreas Isacsson, Alexander Croy
Phononic crystals and acoustic meta-materials are used to tailor phonon and sound propagation properties by facilitating artificial, periodic structures. Analogous to photonic crys…
FPU physics with nanomechanical graphene resonators: intrinsic relaxation and thermalization from flexural mode coupling
Daniel Midtvedt, Zenan Qi, Alexander Croy +2
Thermalization in nonlinear systems is a central concept in statistical mechanics and has been extensively studied theoretically since the seminal work of Fermi, Pasta and Ulam (FP…
Frequency tuning, nonlinearities and mode coupling in circular graphene resonators
A. M. Eriksson, D. Midtvedt, A. Croy +1
We study circular nanomechanical graphene resonators by means of continuum elasticity theory, treating them as membranes. We derive dynamic equations for the flexural mode amplitud…
Nonlinear Damping in Graphene Resonators
Alexander Croy, Daniel Midtvedt, Andreas Isacsson +1
Based on a continuum mechanical model for single-layer graphene we propose and analyze a microscopic mechanism for dissipation in nanoelectromechanical graphene resonators. We find…
Determination of the Bending Rigidity of Graphene via Electrostatic Actuation of Buckled Membranes
Niklas Lindahl, Daniel Midtvedt, Johannes Svensson +4
The small mass and atomic-scale thickness of graphene membranes make them highly suitable for nanoelectromechanical devices such as e.g. mass sensors, high frequency resonators or…