Renewed prospects for organic photovoltaics

G Zhang, FR Lin, F Qi, T Heumüller, A Distler… - Chemical …, 2022 - ACS Publications
Organic photovoltaics (OPVs) have progressed steadily through three stages of photoactive
materials development:(i) use of poly (3-hexylthiophene) and fullerene-based acceptors …

Machine learning for a sustainable energy future

Z Yao, Y Lum, A Johnston, LM Mejia-Mendoza… - Nature Reviews …, 2023 - nature.com
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …

An autonomous laboratory for the accelerated synthesis of novel materials

NJ Szymanski, B Rendy, Y Fei, RE Kumar, T He… - Nature, 2023 - nature.com
To close the gap between the rates of computational screening and experimental realization
of novel materials,, we introduce the A-Lab, an autonomous laboratory for the solid-state …

The rise of self-driving labs in chemical and materials sciences

M Abolhasani, E Kumacheva - Nature Synthesis, 2023 - nature.com
Accelerating the discovery of new molecules and materials, as well as developing green
and sustainable ways to synthesize them, will help to address global challenges in energy …

Recent advances and applications of deep learning methods in materials science

K Choudhary, B DeCost, C Chen, A Jain… - npj Computational …, 2022 - nature.com
Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Advantages, challenges and molecular design of different material types used in organic solar cells

J Yi, G Zhang, H Yu, H Yan - Nature Reviews Materials, 2024 - nature.com
The performance of organic solar cells (OSCs) has increased substantially over the past 10
years, owing to the development of various high-performance organic electron–acceptor …

Autonomous chemical experiments: Challenges and perspectives on establishing a self-driving lab

M Seifrid, R Pollice, A Aguilar-Granda… - Accounts of Chemical …, 2022 - ACS Publications
Conspectus We must accelerate the pace at which we make technological advancements to
address climate change and disease risks worldwide. This swifter pace of discovery requires …

Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics

K Hippalgaonkar, Q Li, X Wang, JW Fisher III… - Nature Reviews …, 2023 - nature.com
As materials researchers increasingly embrace machine-learning (ML) methods, it is natural
to wonder what lessons can be learned from other fields undergoing similar developments …

Nanoparticle synthesis assisted by machine learning

H Tao, T Wu, M Aldeghi, TC Wu… - Nature reviews …, 2021 - nature.com
Many properties of nanoparticles are governed by their shape, size, polydispersity and
surface chemistry. To apply nanoparticles in chemical sensing, medical diagnostics …

A mobile robotic chemist

B Burger, PM Maffettone, VV Gusev, CM Aitchison… - Nature, 2020 - nature.com
Technologies such as batteries, biomaterials and heterogeneous catalysts have functions
that are defined by mixtures of molecular and mesoscale components. As yet, this multi …