Results 171 to 180 of about 16,685,753 (277)

Effect of Aggregate Type on Properties of Ultra-High-Strength Concrete. [PDF]

Materials (Basel), 2022
Szcześniak A, Siwiński J, Stolarski A.
europepmc   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Author Correction: Experimental and numerical study on flexural behavior of steel fiber reinforced high-strength concrete (SFRHC) beams. [PDF]

Sci Rep
Shi K, Gao Z.
europepmc   +1 more source

Analysis of Shear Model for Steel-Fiber-Reinforced High-Strength Concrete Corbels with Welded-Anchorage Longitudinal Reinforcement. [PDF]

Materials (Basel), 2023
Li SS, Peng D, Wang H, Zhang FJ, Li HM, Xie YJ, Chen AJ, Xie W.   +7 more
europepmc   +1 more source

On the Aggregates for High Strength Concrete

Concrete Journal, 1990
Kokubu, Katsuro, Hisaka, Motoo
openaire   +2 more sources

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Experimental Study on Mechanical Properties and Mix Design Optimization of Nano-SiO₂-Double-Doped Fiber High-Strength Concrete. [PDF]

Materials (Basel)
Zhu Y, Zhang Y, Tao Y, Wang Q, Zhang R, Fang Y.   +5 more
europepmc   +1 more source

The Influence of Fly Ash on the Tensile Creep Prediction of High-Strength Concrete at Early Ages. [PDF]

Materials (Basel), 2023
Yao J, Yao S, Huang S, Ni T, Jiang C, Yang Y, Kong D.   +6 more
europepmc   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

Influence of Training-Testing Data Variation on ML-Based Deflection Prediction of GFRP-Reinforced High-Strength Concrete Beams. [PDF]

Polymers (Basel)
Karabulut M.
europepmc   +1 more source