Results 221 to 230 of about 1,212,320 (356)

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Elastomer-Based Sealing O-Rings and Their Compatibility with Methanol, Ethanol, and Hydrotreated Vegetable Oil for Fueling Internal Combustion Engines. [PDF]

Materials (Basel)
Müller M, Mishra RK, Šleger V, Pexa M, Čedík J.   +4 more
europepmc   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Flame‐Retardant Quasi‐Solid‐State Electrolytes From Self‐Assembled Azolate Hybrid Frameworks for Highly Safe Lithium Batteries

Angewandte Chemie, EarlyView.
This work develops a spray‐assisted in situ assembly technique to construct AHF materials with nitrogen/oxygen‐regulated one‐dimensional channels on glass fiber, providing abundant active sites and enabling rapid transport for lithium ions. Subsequently, phosphate flame retardants are encapsulated via in situ polymerization, resulting in a thermally ...
Shun Wang, Qimin Zhu, Yuanyuan Tian, Peiyu Cui, Qing Ji, Tian Xie, Hong Wang, Dong Zhou, Guoxiu Wang, Wenhuan Huang   +9 more
wiley   +2 more sources

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

Porous Organic Cages for CO2 Capture and Confined Reduction

Angewandte Chemie, EarlyView.
Porous organic cages (POCs) enable the coupling of CO2 capture and conversion through the interplay of molecular structure and solid‐state organization. Beyond intrinsic cavities, packing‐dependent pore accessibility and mass transport govern local CO2 concentration and catalytic performance, linking adsorption to reactivity in integrated capture ...
Valeria Amendola, Sonia La Cognata
wiley   +2 more sources

Ignition and Combustion of Rotary Engine

Review of Automotive Engineering, 2009
Okui, Nobunori, Takahashi, Yoshitomo, Kagawa, Ryoji, Tabata, Michihiko, Moriue, Osamu, Murase, Eiichi   +5 more
openaire   +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

Entropy‐Stabilized Aluminate Catalysts That Break the Activity–Stability Tradeoff in CF4 Hydrolysis

Angewandte Chemie, EarlyView.
Entropy‐stabilized aluminate breaks the activity–stability tradeoff in CF4 hydrolysis by combining a multication aluminate framework with an entropy‐stabilized lattice. An electron‐deficient Al–O environment is F‐philic but O‐phobic, enabling C–F activation while suppressing H2O poisoning. Under steam‐rich, strongly fluorinating conditions, the entropy‐
Seunghyuck Chi, Hyungmin Jeon, Yaejun Baik, DongHwan Oh, Jin Seok, Woosung Choi, Seungjun Lee, Minkee Choi   +7 more
wiley   +2 more sources