Results 161 to 170 of about 8,346 (256)
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
Asking the 5 W's for designing next‐generation bioprocessing
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook +4 more
wiley +1 more source
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +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
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
Review and Integrated Framework for Deep-Sea Mineral Resources, Ecological Influence, and Future Development. [PDF]
Liu J +8 more
europepmc +1 more source
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Genome Mining of Deep-Sea Cold Seep-Derived Fungus Reveals a Laccase-Fasciclin System Modulating Regioselective Naphthopyranone Dimerization. [PDF]
Li H +7 more
europepmc +1 more source
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source

