Results 131 to 140 of about 157,174 (281)

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Two‐Dimensional Infrared Spectroscopy Reveals the Presence of a Bridging CO Ligand in Two Catalytic Intermediates of [FeFe] Hydrogenase

Angewandte Chemie, EarlyView.
Two‐dimensional (2D) infrared (IR) spectroscopy provides vastly more structural and functional insight into chemical and biological systems than linear IR spectroscopy. Here, we apply 2D‐IR spectroscopy to two controversially discussed states of the [FeFe] hydrogenase active site, revealing the presence of a bridging carbonyl ligand, which is difficult
Cornelius C. M. Bernitzky, Mathesh Vaithiyanathan, Manon T. Lachmann, Igor V. Sazanovich, Gregory M. Greetham, Patricia Rodríguez‐Maciá, James A. Birrell, Marius Horch   +7 more
wiley   +2 more sources

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +1 more source

Steric Hindrance and Secondary Interactions Govern Reconfiguration Between Two Complex CuI Coordination Cages

Angewandte Chemie, EarlyView.
Fine‐tuning steric and C─H···π contacts directs assembly of two CuI cages. An identical naphthylene‐based subcomponent forms a [CuI12L6]12+ pseudo‐hexagonal prism stabilized by 29–32 C─H···π contacts and 12 arene stacking pairs with 6‐methyl‐2‐formylpyridine, whereas the 3‐methyl analog imparts steric clashes, yielding a [CuI8L4]8+ open prism ...
Houyang Xu, Sudhakar Gaikwad, Tanya K. Ronson, Jonathan R. Nitschke   +3 more
wiley   +2 more sources

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Stimuli‐Responsive Silsesquioxane Nanozymes for Organocatalysis in Water and Prodrug Activation in Cells

Angewandte Chemie, EarlyView.
Amino‐bearing silsesquioxanes are water‐stable nanozymes that exhibit aggregation‐ and disaggregation‐dependent catalysis and can be applied to intracellular prodrug activation for cancer therapy. ABSTRACT Synthetic nanozymes have emerged as promising alternatives to natural enzymes for catalytic and therapeutic applications, yet their limited ...
Rabia Zahid, Ariadna Lázaro, Guillermo Moreno‐Alcántar, María Sancho‐Albero, Pierre Picchetti   +4 more
wiley   +2 more sources

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

Predicting Crystal Structures and Ionic Conductivities in Li3 YCl6−x Brx Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential

Advanced Intelligent Systems, EarlyView.
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley   +1 more source

AInstein: numerical Einstein metrics via machine learning

AI for Science
A new semi-supervised machine learning package is introduced which successfully solves the Euclidean vacuum Einstein equations with a cosmological constant, without any symmetry assumptions.
Edward Hirst, Tancredi Schettini Gherardini, Alexander G Stapleton   +2 more
doaj   +1 more source

‘Turkeys Cannot Vote for Christmas’: Why Epistemic Disobedience in an Anti‐Black World Matters

Australian Journal of Social Issues, EarlyView.
ABSTRACT Never in the history of global coloniality has the idea of epistemic disobedience been as important as in the 21st century. This is not only because the struggle for decolonisation has shifted from physical confrontation between the coloniser and the colonised into a battle of ideas but also because the former has deployed the idea of ...
Morgan Ndlovu
wiley   +1 more source