The <i>dilemma</i> of cancer biomechanics assessment: Living soft matter from a rheological perspective. [PDF]
Ferraro R, Guido S, Caserta S.
europepmc +1 more source
Diffusion–Model–Driven Discovery of Ferroelectrics for Photocurrent Applications
We developed a diffusion model–based generative AI and high‐throughput screening framework that accelerates the discovery of photovoltaic ferroelectrics. By coupling AI driven crystal generation with machine learning and DFT screening, we identified Ca3P2 and LiCdP as new ferroelectric materials exhibiting strong polarization, feasible switching ...
Byung Chul Yeo +3 more
wiley +1 more source
A numerical simulation approach for inflatable asymmetric geometries of orthotropic fabrics. [PDF]
Abdelmaseeh ASA +2 more
europepmc +1 more source
A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng +8 more
wiley +1 more source
A multiscale topology optimization design framework with data driven surrogate model. [PDF]
Zhou H, Zhou C.
europepmc +1 more source
This manuscript presents the WDMS platform, an AI‐assisted, self‐powered wearable dual‐mode sensor for tele‐neurology. It integrates a contact–separation TENG insole with stretchable polyurethane optical‐fiber strain sensors to synchronously track plantar pressure and lower‐limb muscle deformation.
Tianliang Li +12 more
wiley +1 more source
How does carbon pricing leverage emission reductions in the power sector? Evidence from China's national carbon market. [PDF]
Song Y, Li Y, Peng K.
europepmc +1 more source
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
Rheological analysis in food processing: factors, applications, and future outlooks with machine learning integration. [PDF]
Chen Y +6 more
europepmc +1 more source
A Finite Element Study of Bimodulus Materials with 2D Constitutive Relations in Non-Principal Stress Directions. [PDF]
Dong C +7 more
europepmc +1 more source

