Machine learning for electrocatalyst and photocatalyst design and discovery
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …
reducing the impact of global warming, and providing solutions to environmental pollution …
Developing sustainable, high-performance perovskites in photocatalysis: design strategies and applications
Solar energy is attractive because it is free, renewable, abundant and sustainable.
Photocatalysis is one of the feasible routes to utilize solar energy for the degradation of …
Photocatalysis is one of the feasible routes to utilize solar energy for the degradation of …
Machine learning for perovskite solar cells and component materials: key technologies and prospects
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 …
design is an irreversible trend. Its ability and efficiency to handle nonlinear and game …
Converting nanotoxicity data to information using artificial intelligence and simulation
Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …
However, data is not equal to information. The question is how to extract critical information …
Enhanced visible light photocatalytic performance of Sr0. 3 (Ba, Mn) 0.7 ZrO3 perovskites anchored on graphene oxide
In search of better materials for visible light photocatalytic performance, perovskite Sr 0.3
(Ba/Mn) 0.7 ZrO 3 nanopowders anchored on graphene oxide were synthesized for the …
(Ba/Mn) 0.7 ZrO 3 nanopowders anchored on graphene oxide were synthesized for the …
Recent development of organic–inorganic hybrid photocatalysts for biomass conversion into hydrogen production
Over the last few years, photocatalysis using solar radiation has been explored extensively
to investigate the possibilities of producing fuels. The production and systematic usage of …
to investigate the possibilities of producing fuels. The production and systematic usage of …
Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development
With the projected global surge in hydrogen demand, driven by increasing applications and
the imperative for low-emission hydrogen, the integration of machine learning (ML) across …
the imperative for low-emission hydrogen, the integration of machine learning (ML) across …
Machine learning in the development of adsorbents for clean energy application and greenhouse gas capture
Addressing climate change challenges by reducing greenhouse gas levels requires
innovative adsorbent materials for clean energy applications. Recent progress in machine …
innovative adsorbent materials for clean energy applications. Recent progress in machine …
One-pot microwave-assisted synthesis of In2S3/In2O3 nanosheets as highly active visible light photocatalysts for seawater splitting
YR Lin, YC Chang, FH Ko - International Journal of Hydrogen Energy, 2024 - Elsevier
A facile one-pot microwave-assisted synthesis prepared a new noble metal-free
heterostructure of In 2 S 3/In 2 O 3 nanosheets for blue LED-light-induced photocatalytic …
heterostructure of In 2 S 3/In 2 O 3 nanosheets for blue LED-light-induced photocatalytic …
Enhancing prediction accuracy of physical band gaps in semiconductor materials
Accurate band-gap prediction is essential for designing and discovering new materials with
desired properties. However, current methods for calculating band gaps based on local and …
desired properties. However, current methods for calculating band gaps based on local and …