Assessment of tribological performance and thermal stability of metakaolin-based geopolymer composites reinforced with high TiO<sub>2</sub> concentration. [PDF]
Hassan MA +2 more
europepmc +1 more source
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
Integration and mechanical and water absorption characteristics of treated natural fiber-titanium nanoparticles embedded polyester composites. [PDF]
Aruna M +9 more
europepmc +1 more source
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley +1 more source
Exploring the synergistic effects of titanium dioxide reinforcements on microstructural and tribological behaviour of hybrid Al6061/5ZrO<sub>2</sub> composite. [PDF]
Shekhawat D, Aherwar A, Pathak VK.
europepmc +1 more source
We present a novel AI‐integrated implantation‐on‐chip platform that enables mimicking and monitoring the maternal–fetal interactions at the early phases of human embryo implantation with high spatiotemporal resolution. The complexity of the trophoblast invasion process was addressed by conducting the analysis at global (rate of invasion) and local ...
Joanna Filippi +12 more
wiley +1 more source
Enhanced crystallinity, hardness and thermal stability of PEEK/TC4 composites for biomedical applications. [PDF]
Sariyev B +3 more
europepmc +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source
Effects of different whitening toothpastes on the color and surface properties of resin composites after staining. [PDF]
Yıldızoğlu E, Manir M, Karadas M.
europepmc +1 more source
Stable Neural Signal Recording Processed by Memristor‐Based Reservoir Computing System
This work introduces a memristor‐based reservoir computing (RC) system for real‐time, energy‐efficient processing of neural signals in brain‐machine interface (BMI). Combined with flexible mesh neural probes with tissue‐like flexibility and subcellular‐scale features that enable consistent, long‐term tracking of single‐cell neural activities, the ...
Soohyeon Kim +10 more
wiley +1 more source

