Results 211 to 220 of about 4,069,375 (260)
ABSTRACT Extreme heat has become a recurring operational challenge that disrupts production, raises energy and maintenance needs, and makes it harder for firms to sustain environmental performance. However, it remains less clear whether AI‐related capability is associated with firms' ability to maintain environmental performance under recurring extreme‐
Shangze Dai, Xinde James Ji, Kai Huang
wiley +1 more source
This work explores generative AI for automated revision of Piping and Instrumentation Diagrams (P&IDs). We frame P&ID correction as a translation problem, converting attributed P&ID graphs into sequences and learning revisions with a transformer‐based model.
Lukas Schulze Balhorn +5 more
wiley +1 more source
Experimental methods in chemical engineering: Cyclic voltammetry—CV
Abstract Cyclic voltammetry (CV) is a foundational electroanalytical technique for investigating redox behaviour and evaluating material performance across fields such as molecular electrochemistry, electrocatalysis, sensing, and energy storage. Despite its widespread use, a gap remains between formal electrochemical theory and the practical data ...
Yasser Matos‐Peralta +4 more
wiley +1 more source
Conventional clinical trials remain the benchmark for evaluating therapeutic safety and efficacy, yet they are constrained by escalating costs, withdrawal over the extended follow‐up periods, recruitment difficulties, ethical limits, and a restricted ability to characterize heterogeneous populations.
Maximilian Balmus +7 more
wiley +1 more source
Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality
ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
wiley +1 more source
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li +4 more
wiley +1 more source
An overview of grain boundary engineering in the field of electrocatalysis. ABSTRACT Key electrocatalytic reactions such as HER, OER, ORR, CO2RR, and NRR offer promising routes for storing renewable energy as chemical fuels. However, their widespread application is constrained due to the lack of highly active and stable catalysts. Grain boundaries (GBs)
Jingyu Gao +8 more
wiley +1 more source
Dynamic reconstruction transforms atomically dispersed Cu catalysts into authentic working‐state active phases during CO2 electroreduction. By integrating operando characterization, multiscale simulations, and AI‐assisted predictive modeling, this review establishes a framework for understanding, predicting, and rationally engineering catalyst ...
Jin Liu, Yue‐Wen Fang
wiley +1 more source
Generative Models in Inorganic Crystals Discovery and Inverse Design
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li +5 more
wiley +1 more source

