Results 181 to 190 of about 117,918 (260)
RF-SVR-based prediction methodology for metal tube-bending rebound: Handling non-uniformity and limited sample challenges. [PDF]
Fang Z, Zhang P, Li L, Zhang Q.
europepmc +1 more source
Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source
Elucidating formability limits in warm incremental sheet forming of AZ61 magnesium alloy using integrated grey relational and data-driven analysis. [PDF]
Magdum AR +5 more
europepmc +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Isoscape of Oxygen Stable Isotopes in Woods of the Amazon. [PDF]
Batista ACG +16 more
europepmc +1 more source
Light‐Imprinted Chirality in Nanomaterials: From Principles to Applications
Light‐induced chirality represents a transformative paradigm for fabricating chiral nanostructures. This review provides a comprehensive framework encompassing light‐based strategies for imprinting and tuning chirality in nanomaterials, which guides researchers in harnessing light to create next‐generation functional materials.
Xinru Jin +3 more
wiley +1 more source
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Development of an exploratory prediction model for preoperative CK19 expression in esophageal cancer driven by radiomics and machine learning. [PDF]
Yang J, Wang S, Chen X, Liu L, Li Y.
europepmc +1 more source
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu +3 more
wiley +1 more source

