Flexible Memory: Progress, Challenges, and Opportunities
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan +5 more
wiley +1 more source
Data-driven design guide for vibrotactile display layouts by continuous mapping. [PDF]
Vom Stein M, Hoppe M, Rieger N, Wolf KD.
europepmc +1 more source
On the Dynamically Unstable Vibrations of the Shaft Carrying an Unsymmetrical Rotating Body
Toshio YAMAMOTO, Hiroshi OTA
openaire +2 more sources
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Analysis of hydraulic mechanism of dynamics flow visualization in an axial pump with impeller blades based on novel transient characteristics conditions and vibration techniques. [PDF]
Al-Obaidi AR, Alwatban A.
europepmc +1 more source
Evolution of Physical Intelligence Across Scales
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Research on the characteristics of spatial 6-degree-of-freedom linear inclined vibrating screen. [PDF]
Huang LX +5 more
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Vehicle Aerodynamic Noise: A Systematic Review of Mechanisms, Simulation Methods, and Bio-Inspired Mitigation Strategies. [PDF]
Zou T, Fu Y, Cao P.
europepmc +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source

