Results 211 to 220 of about 22,737,984 (250)

Hybrid Steel Fiber Design in Ultra-High-Performance Concrete Containing Coarse Aggregate Using Pore Size Distribution Within Coarse Aggregate Skeleton. [PDF]

Materials (Basel)
Tang R, Du Y, Zhang J, Kong L.
europepmc   +1 more source

Hydration Behavior of Tricalcium Silicate in Seawater Relevant Salt Systems: A Hybrid Study with the Aid of Machine Learning

Advanced Intelligent Discovery, EarlyView.
The hydration behavior of C3S in seawater‐relevant solutions is studied based on experiments, boundary nucleation and growth (BNG) modeling, and machine learning. The main ions included in seawater modify hydration mechanisms, with MgCl2 showing the strongest acceleration effect at the same concentration.
Yanjie Sun, Chen Zhang, Ting Zhang, Mengze Hong, Peiliang Shen, Chi Sun Poon, Gang Li   +6 more
wiley   +1 more source

Dataset on compressive strength, ultrasonic pulse velocity, and rebound hammer properties of ultra-high performance concrete with maturing age. [PDF]

Data Brief
Durrani O, Haroon 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

Predicting carbonation depth in fiber-reinforced ultra-high performance concrete (FR-UHPC) using state-of-the-art machine learning techniques. [PDF]

Sci Rep
Mahmoodzadeh A, Hassan R, Ghazouani N, Alghamdi A, Alanazi A, Alsubai S, Alqahtani A, Palani S.   +7 more
europepmc   +1 more source

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

Performance Research of Ultra-High Performance Concrete Incorporating Municipal Solid Waste Incineration Fly Ash. [PDF]

Materials (Basel)
Liu F, He Y, Liu J, Zhang F, Hao X, Liu C.   +5 more
europepmc   +1 more source

Prediction‐Guided Two‐Step Solid‐State Exploration of Unknown Pseudo‐Ternary Oxides

Advanced Intelligent Discovery, EarlyView.
Prediction‐guided selection combined with two‐step solid‐state exploration enables efficient search of unknown pseudo‐ternary oxides. Broad robotic slurry screening followed by manual single‐phase isolation leads to the discovery of a new oxide, Ba5SnV6O22, showing how data‐guided experiments connect unexplored composition regions to new materials ...
Hiroyuki Hayashi
wiley   +1 more source

Probabilistic calculation formula for the compressive strength of ultra-high-performance concrete with coarse aggregate based on feature engineering and genetic programming. [PDF]

Sci Rep
Guo R, Niu J, Li D, Jin Y, Li H, Shi J, Wu X, Wang Z, Yuan Y.   +8 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