Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Implications of the new US AI framework in medicine. [PDF]
Armoundas AA.
europepmc +1 more source
Polymorphic Superparaelectric Engineering Boosting Energy Storage Capacity in BaTiO3‐Based Ceramics
Herein, Ca2+ incorporation promotes the coexistence of CaTiO3‐/BaTiO3‐derived paraferroelectric states, stabilizing cubic‐orthorhombic‐tetragonal polymorphic superparaelectric phases. This minimizes polarization energy barriers, facilitating full polarization saturation without compromising efficiency.
Pan Liu +9 more
wiley +1 more source
Toward fairness in digital consumer protection: a comparative legal and socio-regulatory perspective on digital platform governance. [PDF]
Akkhateerathitiphum R.
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
Unpacking non-transparency: Most physical trading card game and collectible sports card packs failed to disclose probabilities for winning rare prizes. [PDF]
Lo CY, Xiong KX, Xiao LY.
europepmc +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
Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
wiley +1 more source
Promoting Voices of People With Dementia: Examining Barriers to Participation in Residential Aged Care Consultation. [PDF]
Chelberg K +3 more
europepmc +1 more source

