University College London
Browse

Research data for "Learning Radical Excited States from Sparse Data"

Download (665.26 kB)
dataset
posted on 2025-07-23, 10:29 authored by Jingkun ShenJingkun Shen, Lucy E. Walker, Kevin Ma, James D. Green, Hugo Bronstein, Keith T. ButlerKeith T. Butler, Timothy J. H. HeleTimothy J. H. Hele
<p dir="ltr">In this study we have demonstrated a computational model for the simulation of excited electronic states of radicals whose parameters are learned from experimental excited-state data using derivative-free optimisation. This model allows for the rapid-screening of the UV-Visible absorption spectra of organic radicals, including those with potentially useful properties such as in OLEDs and radical qubits. We believe this to be the first rapid-screening method for the excited electronic states of radicals with zero spin-contamination.</p>

Funding

URF\R1\201502

Harnessing vibration-induced enhancement of transport in functional materials with soft structural dynamics

Engineering and Physical Sciences Research Council

Find out more...

Spin Control in Radical Semiconductors

European Research Council

Find out more...

EP/Y000552/1

Designing and optimizing polar photovoltaics with physics informed machine learning

Engineering and Physical Sciences Research Council

Find out more...

History

Related Materials