Results 181 to 190 of about 1,414,259 (269)

From Word2Vec to Transformers: Text‐Derived Composition Embeddings for Filtering Combinatorial Electrocatalysts

Advanced Intelligent Discovery, EarlyView.
With the downstream filter held fixed, text‐derived composition representations produce distinct screening outcomes across 14 electrocatalyst libraries. Embedding model and composition encoding control the trade‐off between candidate reduction and preservation of the best measured current.
Lei Zhang, Markus Stricker
wiley   +1 more source

A 3D Multitask Graph Neural Network Framework for Ames Mutagenicity Prediction

Advanced Intelligent Discovery, EarlyView.
Our proposed multitask graph neural network model has a high predictive accuracy for Ames mutagenicity. By operating directly on molecular graph representations instead of traditional molecular descriptors, and predicting strain‐specific results, the model outperforms most existing benchmarks.
Abigail E. Teitgen, Eugenia Ulzurrun, Nuria E. Campillo, Eduardo R. Hernández   +3 more
wiley   +1 more source

Indole based multicomponent reactions towards functionalized heterocycles

ARKIVOC, 2004
Janos Sapi, Jean-Yves Laronze
doaj   +1 more source

Characterization of Novel Sigma Receptor Ligands Derived from Multicomponent Reactions as Efficacious Treatments for Neuropathic Pain. [PDF]

Pharmaceuticals (Basel)
Shinouchi R, Turgutalp B, Ople RS, Eans SO, Williams AK, Hammond HR, Varadi A, Dardashti RN, Majumdar S, McLaughlin JP.   +9 more
europepmc   +1 more source

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

Synthesis of furochromene derivatives employing multicomponent reactions and SiO₂/Fe₃O₄ as a nanomagnetic catalyst: study of biological activity and reduction of organic pollutants. [PDF]

RSC Adv
Iravani N, Keshavarz M, Taib LA, Hossaini Z.   +3 more
europepmc   +1 more source

Integration of Liquid Handling Robotics, Turbidimetry, and Machine Learning Toward Inverse Design of Lower Critical Solution Temperature Polymer Formulations

Advanced Intelligent Systems, EarlyView.
An integrated OT‐2/plate reader platform automates LCST cloud point measurement of NIPAM‐co‐DMAEMA copolymers across high‐dimensional formulation spaces. Machine learning trained on the resulting high‐throughput datasets achieves R2 up to 0.96 and enables inverse design of polymer formulations to target transition temperatures with <1% error.
Lachlan Alexander, Vianna F. Jafari, Tanja Junkers   +2 more
wiley   +1 more source

Beyond Formate Trapping: A Mechanistic Framework for Homogeneous CO2‐to‐Methanol Conversion With First‐Row Transition Metals

Angewandte Chemie, EarlyView.
This review shows that converting CO2 into methanol with catalysts based on abundant first‐row metals requires more than overcoming formate formation. Success depends on balancing hydrogen activation, intermediate reactivity, product release, and catalyst stability.
Elise Boudry, Christophe M. Thomas
wiley   +2 more sources

Estimation of multicomponent reactions' yields from networks of mechanistic steps. [PDF]

Nat Commun
Szymkuć S, Wołos A, Roszak R, Grzybowski BA.   +3 more
europepmc   +1 more source

Physics‐Informed Machine Learning for Predicting Phases and Density of Al2O3–TiB2 Composites Synthesized via Laser Ignition From the Al–TiO2–B2O3–H3BO3 Reactive System

Advanced Intelligent Systems, EarlyView.
This interactive physics‐informed machine learning model predicts the composition and density of advanced ceramic materials produced by self‐propagating high‐temperature synthesis. The model requires user input processing parameters and demonstrates high accuracy.
Evangelos Daskalakis, Geeta Sharma, Sarathkumar Loganathan, Andrew Scott, Animesh Jha   +4 more
wiley   +1 more source