Results 151 to 160 of about 20,616 (262)

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
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

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

open access: yesAdvanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan   +8 more
wiley   +1 more source

Superatom Distortion Induces Triferroicity and Spin Splitting in Two‐Dimensional Antiferromagnets

open access: yesAdvanced Science, EarlyView.
The incorporation of superatoms into a 2D square lattice induces symmetry breaking, thereby enabling concurrent coupling among magnetism, ferroelectricity, and ferroelasticity. This strategy achieves triferroic behavior—characterized by spin‐split antiferromagnetic ground states—and offers a viable pathway toward energy‐efficient spintronic devices ...
Zhen Gao   +6 more
wiley   +1 more source

Fibrous nonlinear elasticity enables positive mechanical feedback between cells and ECMs. [PDF]

open access: yesProc Natl Acad Sci U S A, 2016
Hall MS   +6 more
europepmc   +1 more source

Engineering Microbial Particles for Next‐Generation Biomedical Platforms

open access: yesAdvanced Science, EarlyView.
Microbe‐derived particles (MDPs), which include extracellular vesicles, outer membrane vesicles, inclusion bodies, polysaccharide particles, and virus‐like particles, represent a rapidly expanding category of bioinspired nanomaterials. With their natural origin, intrinsic biocompatibility, and highly programmable functionality, MDPs serve as a ...
Yuting Li   +7 more
wiley   +1 more source

Strain-enhanced stress relaxation impacts nonlinear elasticity in collagen gels. [PDF]

open access: yesProc Natl Acad Sci U S A, 2016
Nam S, Hu KH, Butte MJ, Chaudhuri O.
europepmc   +1 more source

Ultrasound‐Responsive Piezoelectric Fibrous Membrane Promotes Neurological Recovery After TBI by Modulating Microglial Polarization via Restoring Mitochondrial Dynamic Homeostasis

open access: yesAdvanced Science, EarlyView.
We demonstrate a novel therapy for traumatic brain injury TBI using a LIPUS‐responsive Piezoelectric fibrous membrane. It targets microglial mitochondria via in situ electrical signals, restoring homeostasis and reducing oxidative stress to promote an anti‐inflammatory M2 phenotype.
Wei Li   +9 more
wiley   +1 more source

Organoid Brain‐Machine‐Interface Devices for Central Nervous System Repair

open access: yesAdvanced Science, EarlyView.
We envision organoid brain‐machine‐interface (Organoid‐BMI) devices as new biohybrid bidirectional communication pathways to connect the human CNS and the external world for personalized CNS repair and regeneration. ABSTRACT Central nervous system (CNS) repair and regeneration suffer from tremendous clinical challenges due to current limitations in ...
Yantao Xing   +10 more
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

open access: yesAdvanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung   +7 more
wiley   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

open access: yesAdvanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen   +7 more
wiley   +1 more source

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