| A pH-driven transition of the cytoplasm from a fluid-to a solid-like state promotes entry into dormancy MC Munder, D Midtvedt, T Franzmann, E Nuske, O Otto, M Herbig, ... elife 5, e09347, 2016 | 465 | 2016 |
| Determination of the bending rigidity of graphene via electrostatic actuation of buckled membranes N Lindahl, D Midtvedt, J Svensson, OA Nerushev, N Lindvall, A Isacsson, ... Nano letters 12 (7), 3526-3531, 2012 | 255 | 2012 |
| Quantitative digital microscopy with deep learning B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe Applied Physics Reviews 8 (1), 2021 | 123 | 2021 |
| Nonlinear damping in graphene resonators A Croy, D Midtvedt, A Isacsson, JM Kinaret Physical Review B—Condensed Matter and Materials Physics 86 (23), 235435, 2012 | 119 | 2012 |
| Frequency tuning, nonlinearities and mode coupling in circular mechanical graphene resonators AM Eriksson, D Midtvedt, A Croy, A Isacsson Nanotechnology 24 (39), 395702, 2013 | 76 | 2013 |
| Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles B Špačková, H Klein Moberg, J Fritzsche, J Tenghamn, G Sjösten, ... Nature Methods 19 (6), 751-758, 2022 | 61 | 2022 |
| Geometric deep learning reveals the spatiotemporal features of microscopic motion J Pineda, B Midtvedt, H Bachimanchi, S Noé, D Midtvedt, G Volpe, ... Nature Machine Intelligence 5 (1), 71-82, 2023 | 53 | 2023 |
| Fermi-pasta-ulam physics with nanomechanical graphene resonators: intrinsic relaxation and thermalization from flexural mode coupling D Midtvedt, A Croy, A Isacsson, Z Qi, HS Park Physical review letters 112 (14), 145503, 2014 | 53 | 2014 |
| Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography B Midtvedt, E Olsén, F Eklund, F Höök, CB Adiels, G Volpe, D Midtvedt ACS nano, 0 | 52 | |
| Size and refractive index determination of subwavelength particles and air bubbles by holographic nanoparticle tracking analysis D Midtvedt, F Eklund, E Olsén, B Midtvedt, J Swenson, F Höök Analytical chemistry 92 (2), 1908-1915, 2019 | 48 | 2019 |
| Strain–displacement relations for strain engineering in single-layer 2d materials D Midtvedt, CH Lewenkopf, A Croy 2D Materials 3 (1), 011005, 2016 | 48 | 2016 |
| Single-shot self-supervised object detection in microscopy B Midtvedt, J Pineda, F Skärberg, E Olsén, H Bachimanchi, E Wesén, ... Nature communications 13 (1), 7492, 2022 | 46 | 2022 |
| Extracting quantitative biological information from bright-field cell images using deep learning S Helgadottir, B Midtvedt, J Pineda, A Sabirsh, C B Adiels, S Romeo, ... Biophysics Reviews 2 (3), 2021 | 39 | 2021 |
| Label-free spatio-temporal monitoring of cytosolic mass, osmolarity, and volume in living cells D Midtvedt, E Olsén, F Höök, GDM Jeffries Nature Communications 10 (1), 340, 2019 | 36 | 2019 |
| Intracellular mass density increase is accompanying but not sufficient for stiffening and growth arrest of yeast cells S Abuhattum, K Kim, TM Franzmann, A Eßlinger, D Midtvedt, R Schlüßler, ... Frontiers in Physics 6, 131, 2018 | 31 | 2018 |
| Nonlinear phononics using atomically thin membranes D Midtvedt, A Isacsson, A Croy Nature Communications 5 (1), 4838, 2014 | 31 | 2014 |
| Carbon nanotube field effect transistors with suspended graphene gates J Svensson, N Lindahl, H Yun, M Seo, D Midtvedt, Y Tarakanov, ... Nano Letters 11 (9), 3569-3575, 2011 | 29 | 2011 |
| Simulation of Complex Systems A Argun, A Callegari, G Volpe IOP Publishing, 2021 | 25 | 2021 |
| The Matrix protein M1 from influenza C virus induces tubular membrane invaginations in an in vitro cell membrane model D Saletti, J Radzimanowski, G Effantin, D Midtvedt, S Mangenot, ... Scientific reports 7 (1), 40801, 2017 | 25 | 2017 |
| Roadmap on deep learning for microscopy G Volpe, C Wählby, L Tian, M Hecht, A Yakimovich, K Monakhova, ... ArXiv, 2023 | 21 | 2023 |
Giovanni VolpePhysics Department, University of Gothenburg, Sweden在 physics.gu.se 的电子邮件经过验证