Results 151 to 160 of about 5,371,789 (237)

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Numerical Simulation and Experimental Validation of the Resistance of Recycled Aggregate Concrete to Chloride Penetration Under Freeze-Thaw Cycles. [PDF]

Materials (Basel)
Li Y, Zhao J, Liu Q, Chen X, Zhang H, Jin K, Wang W, Yin P, Zhang T.   +8 more
europepmc   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source

Improved random hierarchical capillary bundle model for simulating the gas permeability evolution of alkali-activated concretes under thermal damage. [PDF]

Sci Rep
A N Omrani I, Koniorczyk M, Colombel MC, Duży P, Hager I, Amiri O, Leklou N, Habiera-Waśniewska E.   +7 more
europepmc   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

Degradation of Hydrophobic Recycled Fine Aggregate Concrete Under Chloride Salt Dry-Wet Cycling Environment. [PDF]

Materials (Basel)
Lu Y, Chen C, Zhang X, Liang J, Guo X.
europepmc   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Effects of the artificial solidified crust on ground settlement during full scaffold construction in a coastal region. [PDF]

Sci Rep
Shang K, Chen L, Zhu Y, Xie C, Li B, Chen XA.   +5 more
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

Raw Marine Sediments in Concrete: Mechanical Performance, Durability, Environmental Release, and End-of-Life Behavior. [PDF]

Materials (Basel)
Alassaad F, Haddad B, Affan H, Ennahal I, Maherzi W, Yaghi A, Issa A.   +6 more
europepmc   +1 more source