Results 181 to 190 of about 57,852 (256)

Flexoelectrically Induced Polar Topology in Twisted SrTiO3 Membranes

Advanced Materials, EarlyView.
Twisted SrTiO3 bilayers host polar vortices of flexoelectric origin, revealed through combined experiment and theory. By reconstructing polarization from the toroidal moment of strain gradients, the work establishes a 3D chiral state with broken inversion and mirror symmetries.
Isabel Tenreiro, Hugo Aramberri, Víctor Rouco, Gabriel Sánchez‐Santolino, Mariona Cabero, Fernando Gallego, David Sánchez‐Manzano, José M. González‐Calbet, Federico Mompeán, Mar García‐Hernández, Alberto Rivera‐Calzada, Jorge Íñiguez‐González, Carlos León, Jacobo Santamaría   +13 more
wiley   +1 more source

Development and external validation of an interpretable machine-learning model for HFpEF comorbidity risk in COPD patients. [PDF]

Respir Res
Cao J, Kang B, Li S, Lei Y, Liu D, Li C, Guo W, Zhang B, Xie X.   +8 more
europepmc   +1 more source

3D Anodic Alumina Nanoarchitectures: A Decade of Progress from Foundational Science to Functional Metamaterials

Advanced Materials, EarlyView.
Ordered three‐dimensional anodic aluminum oxide (3D‐AAO) nanoarchitectures with longitudinal and transverse pores enable architecture‐driven metamaterials. The review maps fabrication advances, including hybrid pulse anodization, and shows how 3D‐AAO templates tailor properties across magnetism, energy, catalysis, and sensing.
Marisol Martín‐González
wiley   +1 more source

Harnessing confinement effect and interpretable machine learning to predict alkane diffusion in zeolite catalysts. [PDF]

Nat Commun
Wang X, Qi J, Wan M, Li F, Yuan J, Liu Z, Zheng A.   +6 more
europepmc   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Predicting macrosomia and low birth weight with interpretable machine learning. [PDF]

BMC Pregnancy Childbirth
Cui M, Yang H, Wang B, Zhang J, Chu Q, Zhang C, Yao Z, Wang L.   +7 more
europepmc   +1 more source

Topology and Material Optimization in Ultra‐Soft Magneto‐Active Structures: Making Advantage of Residual Anisotropies

Advanced Materials, EarlyView.
Residual magnetization induces pronounced mechanical anisotropy in ultra‐soft magnetorheological elastomers, shaping deformation and actuation even without external magnetic fields. This study introduces a computational‐experimental framework integrating magneto‐mechanical coupling into topology optimization for designing soft magnetic actuators with ...
Carlos Perez‐Garcia, Rogelio Ortigosa, Jesús Martínez‐Frutos, Daniel Garcia‐Gonzalez   +3 more
wiley   +1 more source

Personalized sepsis mortality prediction: An interpretable machine learning nomogram. [PDF]

Clinics (Sao Paulo)
Weng L, Li H, Lv Y, Luo J, Wen Z, Shi J, Zhong L.   +6 more
europepmc   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Fast and Interpretable Machine Learning Modeling of Atmospheric Molecular Clusters. [PDF]

J Phys Chem A
Seppäläinen L, Kubečka J, Elm J, Puolamäki KR.   +3 more
europepmc   +1 more source