Results 181 to 190 of about 335,451 (304)
Machine learning driven optimization of biomedical waste ash concrete for sustainable construction. [PDF]
George C +5 more
europepmc +1 more source
This review outlines how understanding bone's biology, hierarchical architecture, and mechanical anisotropy informs the design of lattice structures that replicate bone morphology and mechanical behavior. Additive manufacturing enables the fabrication of orthopedic implants that incorporate such structures using a range of engineering materials ...
Stylianos Kechagias +4 more
wiley +1 more source
Performance Analysis of Boosting-Based Machine Learning Models for Predicting the Compressive Strength of Biochar-Cementitious Composites. [PDF]
Kim J, Ryu D, Hwan H, Lee H.
europepmc +1 more source
In this Perspective, we highlight the processing science and scale‐up capabilities of the Materials Engineering Research Facility (MERF) at the U.S. Department of Energy's Argonne National Laboratory, with an emphasis on practical solutions for sustainable water and critical resource recovery. We demonstrate how national laboratories bridge fundamental
Yuepeng Zhang +9 more
wiley +1 more source
This study presents a new biodegradable coating for titanium implants using a natural antimicrobial peptide, caerin 1.9. Applied via solvent casting, the coating offers sustained antibacterial protection and promotes healing. Tested on 3D‐printed porous titanium scaffolds, it effectively prevented infection—including against resistant bacteria—while ...
Hejie Li +7 more
wiley +1 more source
Modeling the mechanical properties of lightweight high-strength concrete incorporating supplementary cementitious materials using multi-expression programming and random forest. [PDF]
Sheraz M +7 more
europepmc +1 more source
Predicting concrete compressive strength using Machine Learning Algorithms
This thesis explores the application of Artificial Neural Networks (ANNs) for predicting the compressive strength of concrete, a critical parameter in construction engineering. Given the complexity of concrete's composition and the various factors influencing its strength, traditional methods for predicting compressive strength often fall short.
Hussein, Ali Kassim, Hussein, Nuur Ali
openaire +1 more source
Ductility Tuning via Cluster Network Characteristics of Porous Components
Network optimization via cluster characteristics induced by interaction of stress concentration is proposed, demonstrating increased cluster size and dispersion in non‐uniform porous components. The optimized structures exhibit, for the first time, that enhanced ductility and damage progression is controllable through zigzag cluster network designed by
Ryota Toyoba +4 more
wiley +1 more source
Advances in Solid‐Phase Processing Techniques: Innovations, Applications, and Future Perspectives
Based on practical manufacturing challenges, this review examines advanced solid‐phase processing techniques that overcome the inherent limitations of conventional melting‐based and traditional solid‐phase manufacturing, enabling the production of higher‐performance components at reduced cost through process innovation and improved supply‐chain ...
Tianhao Wang
wiley +1 more source
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu +8 more
wiley +1 more source

