Optimizing blended cement concrete strength using the Box-Behnken design technique. [PDF]
Oyebisi S +3 more
europepmc +1 more source
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 +2 more
wiley +1 more source
Investigating the Causes of Substandard Concrete Strength: A Macro- and Microanalysis. [PDF]
Du X +7 more
europepmc +1 more source
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 +2 more
wiley +1 more source
Enhancing concrete strength for sustainability using a machine learning approach to improve mechanical performance. [PDF]
Khan A +5 more
europepmc +1 more source
MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design
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 +2 more
wiley +1 more source
A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength. [PDF]
Zhang K, Li X, Zhang S, Zhang S.
europepmc +1 more source
Programmable Flocks: Hierarchical Swarm Control via Dynamic Parameter Injection
We present a method for the control of robot swarms which allows the shaping and the translation of patterns of simple robots (“smart particles”), using two types of devices. These two types represent a hierarchy: a larger group of simple, oblivious robots (which we call the workers) that is governed by simple local attraction forces and a smaller ...
Vivek Shankar Varadharajan +1 more
wiley +1 more source
Soft computing models for prediction of bentonite plastic concrete strength. [PDF]
Inqiad WB +6 more
europepmc +1 more source
A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti +6 more
wiley +1 more source

