Results 91 to 100 of about 25,726 (266)

Self‐Assembled Inorganic Nanomembrane Tubes: Rolled‐Up Piezoelectrics for Microacoustic Wave‐Based Actuators and Sensors

Advanced Materials, EarlyView.
This study demonstrates a self‐assembly process to generate free‐standing piezoelectric nanomembranes, forming ultracompact microtubular acoustic wave sensors and actuators. The miniaturized 3D piezoelectric platform reported in this work can be applied in telecommunication, energy harvesting, and acoustofluidics. Moreover, the 3D self‐assembly can add
Raphaël C. L‐M. Doineau, Christian N. Saggau, Stefan Baunack, Thomas Gemming, Yara Abdelaal, Robert Weser, Oliver G. Schmidt, Hagen Schmidt, Andreas Winkler, Mariana Medina‐Sánchez   +9 more
wiley   +1 more source

Wear Prediction Algorithm for Feedback Ball Head of Servo Valve

Lubricants
Wear of the feedback ball head–ball seat interface changes the contact state and reduces the feedback force in electro-hydraulic servo valves, resulting in output nonlinearity and performance degradation. Existing wear models usually assume fixed surface
Xiaonan Pan, Jianrui Zhang, Jian Kang
doaj   +1 more source

Tough, Ductile, and Strong Hard‐Soft Cementitious Composite Enabled by Multi‐Material Additive Manufacturing

Advanced Materials, EarlyView.
Drawing inspiration from the layered hard‐soft architecture found in sea sponges, this work establishes a new framework for architected cementitious composites (ACC) through multi‐material additive manufacturing (MMAM) process. The integration of mortar and elastomer phases into layered architectures enables synergistic toughening mechanisms, including
Aimane Najmeddine, Shashank Gupta, William Makinen, Zayvinn Lin, Krystal Delnoce, Reza Moini   +5 more
wiley   +1 more source

Enhancing Tool Wear Prediction Accuracy Using Walsh-Hadamard Transform, DCGAN and Dragonfly Algorithm-Based Feature Selection. [PDF]

Sensors (Basel), 2023
Shah M, Borade H, Sanghavi V, Purohit A, Wankhede V, Vakharia V.   +5 more
europepmc   +1 more source

Flexible Ag2Se‐Based Thermoelectrics: Fundamentals, Processing, and Device Applications

Advanced Materials, EarlyView.
Ag2Se‐based thermoelectrics are reviewed from fundamental transport mechanisms to flexible device integration. Crystal structure, defect chemistry, and band features are correlated with performance optimization strategies and scalable fabrication routes.
Jie Qin, Yuchen Yang, Huangshui Ma, Yong Du, Min Hong, Qinfei Ke   +5 more
wiley   +1 more source

A framework for wheel profile wear prediction of high-speed trains considering tread modification

Friction
Tread modification has gained significant attention in recent years as a means to address the issue of wheel hollow wear. The wear resulting from tread modification can alter the wheel profile, thereby impacting the wheel–rail contact relationship and ...
Yuchen Xie, Maoru Chi, Wubin Cai, Shulin Liang, Yixiao Li, Yabo Zhou, Peng Wang   +6 more
doaj   +1 more source

Tool Wear Prediction When Machining with Self-Propelled Rotary Tools. [PDF]

Materials (Basel), 2022
Umer U, Mian SH, Mohammed MK, Abidi MH, Moiduddin K, Kishawy H.   +5 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

An Advanced Tool Wear Forecasting Technique with Uncertainty Quantification Using Bayesian Inference and Support Vector Regression

Sensors
Tool wear prediction is of great significance in industrial production. Current tool wear prediction methods mainly rely on the indirect estimation of machine learning, which focuses more on estimating the current tool wear state and lacks effective ...
Zhiming Rong, Yuxiong Li, Li Wu, Chong Zhang, Jialin Li   +4 more
doaj   +1 more source

Local-feature and global-dependency based tool wear prediction using deep learning. [PDF]

Sci Rep, 2022
Yang C, Zhou J, Li E, Wang M, Jin T.
europepmc   +1 more source