Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Identity-Based Efficient Secure Data Communication Protocol for Hierarchical Sensor Groups in Smart Grid. [PDF]
Feng Y, Sun Y, Cao Y, Xu B, Li Y.
europepmc +1 more source
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu +12 more
wiley +1 more source
Evolutionary adaptation of CCD4 enzymes in <i>Buddleja alternifolia</i> for crocetin biosynthesis. [PDF]
Parreño E +6 more
europepmc +1 more source
Ray Transform of Symmetric Tensor Fields on Riemannian Manifolds with Conjugate Points. [PDF]
Holman S, Krishnan VP.
europepmc +1 more source
Ventricular Topology in Congenital Heart Defects Associated with Heterotaxy: Can We Find Patterns Reflecting the Syndrome-Specific Tendency for Visceral Symmetry? [PDF]
Othman T +4 more
europepmc +1 more source
Covariant Approach to the Geometric Dilution of Precision. [PDF]
Montesinos RS +2 more
europepmc +1 more source
MOT-Assisted Object-Level Point Cloud Extraction from Multi-View Observations. [PDF]
Ju C, Zhao Z, Shen C, Li X, Namiki A.
europepmc +1 more source
A Certificateless Encryption-Based Authentication Protocol for Low Earth Orbit Satellite Network. [PDF]
Lv Z +5 more
europepmc +1 more source

