Results 161 to 170 of about 571,152 (309)
Tool Wear State Identification Based on SVM Optimized by the Improved Northern Goshawk Optimization. [PDF]
Wang J, Xiang Z, Cheng X, Zhou J, Li W.
europepmc +1 more source
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
Cutting parameter-tool material interaction on PcBN tool wear behaviour in ductile iron machining. [PDF]
Wang P, Li X, Jiu Y, Yin H, Zhang Y.
europepmc +1 more source
Multivariate time series data of milling processes with varying tool wear and machine tools. [PDF]
Denkena B, Klemme H, Stiehl TH.
europepmc +1 more source
This review systematically summarizes recent advances in porosity engineering of MXenes, with a focused discussion on their structure‐governed energy storage properties. A critical analysis of structure–property relationships is presented across alkali‐ion batteries, multivalent‐ion batteries, and supercapacitors.
Shude Liu +8 more
wiley +1 more source
The Effects of Lubricooling Ecosustainable Techniques on Tool Wear in Carbon Steel Milling. [PDF]
Villarrazo N +4 more
europepmc +1 more source
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 +5 more
wiley +1 more source
Tool Wear Condition Monitoring Method Based on Deep Learning with Force Signals. [PDF]
Zhang Y, Qi X, Wang T, He Y.
europepmc +1 more source
This review provides an overview of triboelectric nanogenerator (TENG)–based biomedical applications by classifying studies into electronic and ionic systems across attachable and implantable platforms. It summarizes key material choices, device structures, and working mechanisms that characterize current TENG‐based research, and outlines six future ...
Kyongtae Choi +12 more
wiley +1 more source
CBN cutting tool's surface roughness and tool wear prediction using JOA-optimized CNN-LSTM. [PDF]
Khetre S, Bongale A, Kumar S.
europepmc +1 more source

