Results 161 to 170 of about 14,931 (256)

Surface Diffusion in SnTe‐PbTe Monolayer Lateral Heterostructures

Advanced Functional Materials, EarlyView.
The lateral heterostructures between 2D materials often suffer from the interdiffusion at the interfaces. Here, a surface diffusion mechanism is found to be dominating at the interfaces between semiconducting SnTe and PbTe monolayers. Atomically sharp interfaces can be achieved by suppressing this diffusion process. ABSTRACT The construction of complex
Jing‐Rong Ji, Zi'Ang Gao, Shiva Prasad Poudel, Rui‐Qi Cao, Tianzhe Chen, Luxin Li, Chong Liu, Salvador Barraza‐Lopez, Stuart S. P. Parkin, Kai Chang   +9 more
wiley   +1 more source

Improving the Accuracy of Direction of Arrival Estimation with Multiple Signal Inputs Using Deep Learning. [PDF]

Sensors (Basel)
Lu Y, Guan H, Yang K, Peng T, Wen C, Li X.   +5 more
europepmc   +1 more source

Cardiac‐Derived ECM Microspheres for Enhanced hiPSC‐CMs Maturation

Advanced Functional Materials, EarlyView.
Cardiac extracellular matrix microspheres derived from decellularized porcine heart provide a biomimetic 3D microenvironment for human induced pluripotent stem cell–derived cardiomyocytes (hiPSC‐CMs). This platform supports short‐ and long‐term culture, enhances structural organization, and promotes electrophysiological and functional maturation of ...
Jiazhu Xu, Joel Aboagye, Marcella Edwards, Nick Rogozinski, Yufeng Wen, Angello Huerta Gomez, Zui Pan, Ge Zhang, Huaxiao Yang, Yi Hong   +9 more
wiley   +1 more source

Super-resolution diffractive neural network for all-optical direction of arrival estimation beyond diffraction limits. [PDF]

Light Sci Appl
Gao S, Chen H, Wang Y, Duan Z, Zhang H, Sun Z, Shen Y, Lin X.   +7 more
europepmc   +1 more source

Three‐Dimensional Hierarchical Nanowire‐Networks with Deep‐Focus Tolerance and Adhesion Robustness for Harsh‐Environment SERS Sensing

Advanced Functional Materials, EarlyView.
A 3D nanowire‐network SERS substrate with robust adhesion is developed, featuring pronounced z‐direction optical activity, ultralow detection limit (1.5 × 10−13 M), and excellent signal uniformity (RSD < 10%). Enabled by enhanced light scattering, increased optical density of states, and structural reinforcement, the substrate demonstrates stable, high‐
Jinglai Duan, Wentao Wang, Xiu Liang, Yongliang Zhang, Jie Liu, Yu Bai, Dangyuan Lei   +6 more
wiley   +1 more source

Off-Grid Underwater Acoustic Source Direction-of-Arrival Estimation Method Based on Iterative Empirical Mode Decomposition Interval Threshold. [PDF]

Sensors (Basel)
Xing C, Tan G, Dong S.
europepmc   +1 more source

Counterion Dependent Side‐Chain Relaxation Stiffens a Chemically Doped Thienothiophene Copolymer

Advanced Functional Materials, EarlyView.
Oxidation of a thienothiophene copolymer, p(g3TT‐T2), via different doping strategies and dopant molecules resulted in materials with similar oxidation levels and a high electrical conductivity of ≈100 S cm−1. However, mechanical properties varied significantly, with sub‐glass transition temperatures and elastic moduli spanning from –44°C to –3°C and ...
Mariavittoria Craighero, Meghna Jha, Elsa Veronica Flores‐Vela, Joost Kimpel, Andreas Schaefer, Jiali Guo, Jesika Asatryan, Alberto Peinador Veiga, Shuichi Haraguchi, Per‐Anders Carlsson, Jaime Martín, Mariano Campoy‐Quiles, Christian Müller   +12 more
wiley   +1 more source

Direction-of-Arrival Estimation for Unmanned Aerial Vehicles and Aircraft Transponders Using a Multi-Mode Multi-Port Antenna. [PDF]

Sensors (Basel)
Almasri SA, Johannsen NL, Hoeher PA.
europepmc   +1 more source

Meta‐Rod Mechanical Metamaterials With Programmable Reconfiguration

Advanced Functional Materials, EarlyView.
Existing mechanical metamaterials achieve programmable large deformations in planar square or cubic configurations, restricted by required complex boundary conditions. This research proposes a 1D metamaterial, Meta‐rod, with linear, bending, twisting, area, and volume deformation modes.
Atharva Pande, Lyes Kadem, Hang Xu
wiley   +1 more source

Direction-of-Arrival Estimation via Sparse Bayesian Learning Exploiting Hierarchical Priors with Low Complexity. [PDF]

Sensors (Basel)
Li N, Zhang X, Lv F, Zong B.
europepmc   +1 more source