activity
20002026
most citedAccurate and efficient band gap predictions of metal halide perovskites using the DFT-1/2 method: GW accuracy with DFT expense

188 citations · 270 across the 9 of their papers we have counts for

collaborators

11 papers

cond-mat.other2026

Space-Charge-Driven Nonlinear Charge Transport in Silicon Reconfigurable Nonlinear-Processing Units

Jonas Kareem, Lorenzo Cassola, Reinier J. C. Cool +4

Reconfigurable nonlinear-processing units (RNPUs) are multi-terminal electronic devices that act as computational primitives, exploiting intrinsic nonlinear charge transport combin…

physics.atm-clus2025★ 4 cited

Dipole-quadrupole coupling in triplet exciton-polaron quenching in a phosphorescent OLED emission layer

Clint van Hoesel, Reinder Coehoorn, Peter A. Bobbert

Improving the efficiency and stability of organic light-emitting diodes (OLEDs) will further expand their present success in display applications. Triplet exciton-polaron quenching…

cs.ET2023

Critical nonlinear aspects of hopping transport for reconfigurable logic in disordered dopant networks

Henri Tertilt, Jonas Mensing, Marlon Becker +3

Nonlinear behavior in the hopping transport of interacting charges enables reconfigurable logic in disordered dopant network devices, where voltages applied at control electrodes t…

cond-mat.mtrl-sci2022★ 2 cited

Light-tunable three-phase coexistence in mixed halide perovskites

Zehua Chen, Geert Brocks, Shuxia Tao +1

Mixed iodine-bromine perovskites used in solar cells undergo below a critical temperature an intrinsic demixing into phases with different iodine-bromine compositions. In addition,…

cs.NE2021★ 2 cited

Gradient descent in materia through homodyne gradient extraction

Marcus N. Boon, Lorenzo Cassola, Hans-Christian Ruiz Euler +5

Deep learning, a multi-layered neural network approach inspired by the brain, has revolutionized machine learning. One of its key enablers has been backpropagation, an algorithm th…

cs.LG2020

Dopant Network Processing Units: Towards Efficient Neural-network Emulators with High-capacity Nanoelectronic Nodes

Hans-Christian Ruiz-Euler, Unai Alegre-Ibarra, Bram van de Ven +3

The rapidly growing computational demands of deep neural networks require novel hardware designs. Recently, tunable nanoelectronic devices were developed based on hopping electrons…