Data‐driven epoch, the development of machine learning (ML) in materials and device
design is an irreversible trend. Its ability and efficiency to handle nonlinear and game …

Amid the global call for decarbonization efforts, uranium and lithium are two important metal
resources critical for securing a sustainable energy future. Extraction of uranium and lithium …

Real-time and personalized lithium-ion battery health management is conducive to safety
improvement for end-users. However, personalized prognostic of the battery health status is …

Halide perovskite quantum dots have recently attracted increasing research interest in
photocatalytic CO2 reduction due to their high light absorption coefficient, tunable bandgap …

Grain boundaries (GBs) play an important role in determining the optoelectronic properties
of perovskites, requiring an atomistic understanding of the underlying mechanisms. Strain …

Photoelectrochemical cells (PEC) use solar energy to generate green hydrogen by water
splitting and have an integrated device structure. Achieving high solar‐to‐hydrogen …

Color centers in host semiconductors are prime candidates as spin-photon interfaces for
quantum applications. Finding an optimal spin-photon interface in silicon would move …

Thin-film photovoltaics (PV) offers a path to decarbonize global energy production.
Unfortunately, existing thin-film solar absorbers have major issues associated with either …

Two-dimensional Janus III–VI monolayers and corresponding van der Waals (vdW)
heterostructures present immense application potential in the solar energy conversion …

Over the last few years there has been an increasing number of papers using machine
learning (ML) as a tool to aid research directed towards perovskite solar cells. This review …