Results 101 to 110 of about 75,077 (201)
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Disentangling Brillouin's Negentropy Law of Information and Landauer's Law on Data Erasure. [PDF]
Lairez D.
europepmc +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
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 +5 more
wiley +1 more source
Entropy Production and Irreversibility in the Linearized Stochastic Amari Neural Model. [PDF]
Lucente D, Gradenigo G, Salasnich L.
europepmc +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
π‐Enlargement in Porphyrin Macrocycles at Interfaces
On‐surface synthesis of a 20‐π free‐base expanded porphyrin, by depositing onto a hot Ag(111) substrate an 18‐π free‐base precursor equipped with ‐CF3 functional groups ABSTRACT Porphyrins are essential heteroatomic macrocycles, fundamental to both biological systems and advanced technology.
Ana Barragán +11 more
wiley +2 more sources
Membrane-Mediated Force Transduction Drives Stick-Slip Motion of Lipid Vesicles. [PDF]
Magrinya P +3 more
europepmc +1 more source
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
Current interest in artificial cell research underscores its potential to deepen our understanding of life's fundamental processes. This review highlights advances in bottom‐up coacervate‐based artificial cell engineering via combined integration of cellular hallmarks.
Arjan Hazegh Nikroo +3 more
wiley +2 more sources

