Henrik Klein Moberg

Doctoral Student at Chemical Physics

I am a PhD student with a Bachelor's degree in Physics and a Master's degree in Complex Adaptive Systems, with a focus of combining deep learning with physics.

My PhD project is in developing deep learning models for nanoplasmonic spectroscopy and nanofluidic microscopy analysis. I utilize deep learning-based computer vision in nanofluidic scattering microscopy, a scattering-based optical microscopy method, to study the properties of nano-sized biological molecules and nanoparticles. Further, I use deep learning to study the response of nanoplasmonic sensors in a catalytic nanoreactor to correlate the effect of complex catalytic nanoparticle surface effects on said particles' catalytic activity, as well as improve the speed and limits of detection of hydrogen gas sensors in the framework of the TechForH2 competence center for hydrogen energy technologies at Chalmers.

Source: chalmers.se
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Showing 3 publications

2024

Neural network enabled nanoplasmonic hydrogen sensors with 100 ppm limit of detection in humid air

David Tomecek, Henrik Klein Moberg, Sara Nilsson et al
Nature Communications. Vol. 15 (1)
Journal article
2022

Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles

Barbora Spackova, Henrik Klein Moberg, Joachim Fritzsche et al
Nature Methods. Vol. 19 (6), p. 751-758
Journal article

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