Four constitutive models are evaluated for FeCoNiCr and Al0.6FeCoNiCr HEAs under wide temperature and strain‐rate conditions. The predictive capabilities and limitations of each model are then critically assessed, with particular emphasis on strain rate sensitivity, temperature dependence, and physically unrealistic responses at extreme loading ...
Yooseob Song +3 more
wiley +1 more source
Incidental crossed fused renal ectopia in a low-resource setting: Lessons from Ghana on diagnostic accuracy and imaging practice. [PDF]
Allorsey G +7 more
europepmc +1 more source
The 100% recycling of optimal polycarbonate/acrylonitrile–butadiene–styrene/poly(methyl methacrylate) (PC/ABS/PMMA) blends, identified through the mixture design, over multiple successive cycles provides valuable insights into their life cycle. Subsequently, chemical, rheological, thermal and mechanical characterizations will be carried out to evaluate
Rahma Ezzeddine +3 more
wiley +1 more source
Machine learning-based prediction of well performance parameters for wellhead choke flow optimization. [PDF]
Akbari A, Ghazi F, Kazemzadeh Y.
europepmc +1 more source
Conjugated Polymers Engineered for Flexible/Stretchable Electronics
This review highlights glass transition temperature (Tg) as the central parameter linking molecular structure to device performance in conjugated polymers. By tuning backbone rigidity, side‐chain architecture, and dynamic bonding, Tg governs the balance between π–π stacking–enabled charge transport and mechanical compliance.
Yunchong Yang +5 more
wiley +1 more source
Static Mixers for High-Viscosity Systems: From Classical Helices to Machine-Learning-Optimized Geometries. [PDF]
Luo S, Wang C.
europepmc +1 more source
Physics‐Aware Recurrent Convolutional Neural Networks (PARC) can reliably learn the thermomechanics of energetic materials as a function of morphology. This work introduces LatentPARC, which accelerates PARC by modeling the dynamics in a low‐dimensional latent space.
Zoë J. Gray +5 more
wiley +1 more source
Multiphase dynamic contrast-enhanced magnetic resonance imaging radiomics nomogram for predicting axillary lymph node metastasis in breast cancer. [PDF]
Wang M +5 more
europepmc +1 more source
Optimal design for real-time quantitative monitoring of sand in gas flowline using computational intelligence assisted design framework [PDF]
Aminu, Kuda Tijjani +2 more
core +1 more source
Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim +3 more
wiley +1 more source

