Results 231 to 240 of about 4,063,184 (303)

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1−x−yScxGdyN Heterostructural Alloys

Advanced Science, EarlyView.
This study demonstrates ferroelectricity and piezoelectric properties improvement of quaternary wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films, guided by density functional theory calculations. Wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films have a high optical bandgap, enhanced piezoelectric ...
Julia L. Martin, Cheng‐Wei Lee, Nate S.P. Bernstein, Thi Nguyen, Ande Bryan, Eli Cooper, John S. Mangum, Sage R. Bauers, Andriy Zakutayev, Keisuke Yazawa, Prashun Gorai, Rebecca W. Smaha   +11 more
wiley   +1 more source

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source

Estimation of Underlying Normal Distribution Parameters From Dichotomized Data. [PDF]

Biom J
Liu Z, Shang L, Lesperance M, Zhou S, Zhang X.   +4 more
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Beat Frequency Estimation in a Square He-Ne Ring Laser Gyroscope: Joint I/Q Channel Calibration and Kalman Filtering. [PDF]

Sensors (Basel)
Shi L, Luo Z, Hu J, Lu J, Chen D, Xie Z, Wu S, Tan Z.   +7 more
europepmc   +1 more source

Remote Magnetomechanical Neuromodulation Uncovers Therapeutic Mechanisms for Alleviating Parkinsonian Symptoms in Freely Moving Mice

Advanced Science, EarlyView.
Magnetomechanical neuromodulation using magnetic nanodiscs enables remote activation of neurons. In a hemiparkinsonian mouse model, alternating magnetic fields actuate the nanodiscs to generate torque that opens mechanosensitive ion channels within the subthalamic nucleus, thereby modulating basal ganglia motor circuitry.
Anouk Wolters, Lorenzo Signorelli, Christian Herff, Sophia Gimple, Renzo Riemens, Gunter Kenis, Kim Rijkers, Hamed Shabani, Jyh‐Jang Sun, Yasin Temel, Hans Clusmann, Danijela Gregurec, Sarah‐Anna Hescham   +12 more
wiley   +1 more source

An Imaging System with Robust Spot Detection for Space Laser Communication ATP Systems. [PDF]

Sensors (Basel)
Liu Z, Yan Q, Li Z, An J.
europepmc   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Identification and Enhancement of Kink Soliton Motions in a van der Waals Layer. [PDF]

ACS Nano
Li B, Park JW, Yeom HW.
europepmc   +1 more source

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

Advanced 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, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source