275 citations · 707 across the 19 of their papers we have counts for
9 papers · 1 filter
Accelerating Plasmonic Hydrogen Sensors for Inert Gas Environments by Transformer-Based Deep Learning
Viktor Martvall, Henrik Klein Moberg, Athanasios Theodoridis +6
The ability to rapidly detect hydrogen gas upon occurrence of a leak is critical for the safe large-scale implementation of hydrogen (energy) technologies. However, to date, no tec…
Phonon-bottleneck enhanced exciton emission in 2D perovskites
Joshua J. P. Thompson, Mateusz Dyksik, Paulina Peksa +8
Layered halide perovskites exhibit remarkable optoelectronic properties and technological promise, driven by strongly bound excitons. The interplay of spin-orbit and exchange coupl…
Tensorial properties via the neuroevolution potential framework: Fast simulation of infrared and Raman spectra
Nan Xu, Petter Rosander, Christian Schäfer +7
Infrared and Raman spectroscopy are widely used for the characterization of gases, liquids, and solids, as the spectra contain a wealth of information concerning in particular the…
Tailoring hot-carrier distributions of plasmonic nanostructures through surface alloying
Jakub Fojt, Tuomas P. Rossi, Priyank V. Kumar +1
Alloyed metal nanoparticles are a promising platform for plasmonically enabled hot-carrier generation, which can be used to drive photochemical reactions. Although the non-plasmoni…
Machine Learning for Polaritonic Chemistry: Accessing chemical kinetics
Christian Schäfer, Jakub Fojt, Eric Lindgren +1
Altering chemical reactivity and material structure in confined optical environments is on the rise, and yet, a conclusive understanding of the microscopic mechanisms remains elusi…
General-purpose machine-learned potential for 16 elemental metals and their alloys
Keke Song, Rui Zhao, Jiahui Liu +25
Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicabil…
Quantitative predictions of the thermal conductivity in transition metal dichalcogenides: The impact of point defects in MoS and WS monolayers
Srinivisan Mahendran, Jesús Carrete, Andreas Isacsson +2
Transition metal dichalcogenides are investigated for various applications at the nanoscale thanks to their unique combination of properties and dimensionality. For many of the ant…
Understanding correlations in BaZrO3:Structure and dynamics on the nano-scale
Erik Fransson, Petter Rosander, Paul Erhart +1
Barium zirconate BaZrO3 is one of few perovskites that is claimed to retain an average cubic structure down to 0K at ambient pressure, while being energetically very close to a tet…
GPAW: An open Python package for electronic-structure calculations
Jens Jørgen Mortensen, Ask Hjorth Larsen, Mikael Kuisma +44
We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density…