Results 271 to 280 of about 1,429,068 (340)

Detection and Quantification of Over‐Humidification in Polymer Electrolyte Fuel Cells: Insights into Simulation, Imaging, and Sensors

open access: yesAdvanced Energy and Sustainability Research, EarlyView.
This review highlights advanced methods for detecting and managing over‐humidification in polymer electrolyte fuel cells (PEFCs), emphasizing innovative sensors, simulation techniques, and imaging methods. By addressing the impact of water management on fuel‐cell performance and durability, this study outlines practical and sustainable solutions for ...
Maximilian Käfer   +2 more
wiley   +1 more source

Taking a look at your speech: identifying diagnostic status and negative symptoms of psychosis using convolutional neural networks. [PDF]

open access: yesNPP Digit Psychiatry Neurosci
Melshin G   +5 more
europepmc   +1 more source

Machine Learning for Organic Fluorescent Materials

open access: yesAggregate, EarlyView.
Organic fluorescent materials (OFMs) have demonstrated significant potential in diverse applications. Conventional approaches for studying OFMs face significant limitations in fluorescence spectroscopy and computational methods. Machine learning (ML) has revolutionized materials chemistry, offering superior predictive accuracy and efficiency over ...
Jiamin Zhong   +7 more
wiley   +1 more source

Predicting both thermodynamic and kinetic properties of crystallizing molecules via transformer‐based language model

open access: yesAIChE Journal, EarlyView.
Abstract Crystallization is pivotal in the chemical and pharmaceutical industry, affecting particle stability, and drug release. Crystal size distribution (CSD), a critical attribute of the final dosage form, is determined by the molecular structure of the crystallizing entity.
Silabrata Pahari   +3 more
wiley   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

open access: yesAdvanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren   +6 more
wiley   +1 more source

Machine‐Learning‐Based, Feature‐Rich Prediction of Alumina Microstructure from Hardness

open access: yesAdvanced Intelligent Discovery, EarlyView.
Herein, high‐performance generative adversarial network (GAN), named ‘Microstructure‐GAN’, is demonstrated. After training, the high‐fidelity, feature‐rich micrographs can be predicted for an arbitrary target hardness. Microstructure details such as small pores and grain boundaries can be observed at the nanometer scale in the predicted 1000 ...
Xiao Geng   +10 more
wiley   +1 more source

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