Results 151 to 160 of about 3,113,242 (314)
Advanced Functional Materials, EarlyView.AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu +5 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Wrinkling of soft materials, such as polydimethylsiloxane (PDMS), underpins a myriad of technologies. Plasma‐oxidation of PDMS induces spontaneous wrinkling, which is canonically attributed to thermal expansion‐contraction of bilayers. Employing experiments and modelling, it is demonstrated that sorption of water vapor is instead responsible for ...
Zain Ahmad +8 more
wiley +1 more source
Recycling of Thermoplastics with Machine Learning: A Review
Advanced Functional Materials, EarlyView.This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque +5 more
wiley +1 more source
Applications of sensitivity analysis to uncertainty quantification in variably saturated flow
, 2002 Carol S. Woodward +2 more
openalex +2 more sources
Advanced Functional Materials, EarlyView.The ionic conductivity of a solid electrolyte is just the “tip of the iceberg”. There are many parameters to consider to quantify it reliably in powdered solid electrolyte samples. Abstract All‐solid‐state batteries (ASSBs) are taking the lead as the next‐generation energy storage systems, mainly to the development of new solid electrolytes with high ...
Fariza Kalyk +3 more
wiley +1 more source
Quantification of Uncertainty in Mineral Prospectivity Prediction Using Neural Network Ensembles and Interval Neutrosophic Sets [PDF]
, 2006 Pawalai Krai peerapun +3 more
openalex +1 more source
The Hierarchical Structure of Sheep Wool and Its Impact on Physical Properties
Advanced Functional Materials, EarlyView.Sheep wool, a prevalent α‐keratinous fiber, is an essential model for studying protein‐based fibers. Its genetic diversity across breeds enables the establishment of multiscale structure‐property relationships, uncovering previously elusive insights into wool's hierarchical structure.
Serafina R. France Tribe +9 more
wiley +1 more source
Quantifying Vadose Zone Flow and Transport Uncertainties Using a Unified, Hierarchical Approach
, 2002 Philip D. Meyer +3 more
openalex +2 more sources