Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Mechanistic anode engineering for aqueous aluminium‐ion batteries is discussed through alloying and microstructure control, surface/interface engineering, and electrolyte modification to regulate ion transport, suppress dendrites, passivation, hydrogen evolution, and side reactions, highlighting standardisation, computational acceleration, and ...
Hong Zhao +3 more
wiley +1 more source
Comparative Analysis of AWJM Performance in FFF-Printed PLA and PLA-CF: Influence of Process Parameters and Cutting Regions. [PDF]
Mayuet Ares PF +3 more
europepmc +1 more source
Challenges and enablers in fluidization technology
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley +1 more source
Lapping of Soft-Brittle Lithium Niobate Crystal with Fixed Abrasive Pad. [PDF]
Zhu N, Gao X, Tang C, Chen J, Zhu Y.
europepmc +1 more source
Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son +4 more
wiley +1 more source
Towards Ultra-Precision Manufacturing: Advancements and Future Trends in Energy Field-Assisted Jet Machining. [PDF]
He Y, Chen T, Man X, Su T.
europepmc +1 more source
Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley +1 more source
Editorial for the Special Issue on Advanced Abrasive Processing Technology and Applications. [PDF]
Gao Y.
europepmc +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source

