Results 131 to 140 of about 6,452 (264)

Twisted Kähler-Einstein metrics

, 2019
We prove an existence result for twisted Kähler-Einstein metrics, assuming an appropriate twisted K-stability condition. An improvement over earlier results is that certain non-negative twisting forms are allowed.
Ross, Julius, Székelyhidi, Gábor
openaire   +2 more sources

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

Optimize Before You Synthesize—Enhancing the Ionic Conductivity of Li7SiPS8 Using Bayesian Optimization

Angewandte Chemie, EarlyView.
Bayesian optimization was used to optimize the synthesis parameters of the solid electrolyte Li7SiPS8$\mathrm {Li}_7\mathrm {SiPS}_8$ in order to increase the ionic conductivity. After only 32 iterations, the ionic conductivity was successfully increased from 2 to 7 mS cm−1$\mathrm {cm}^{-1}$ at 25∘C$^\circ\mathrm {C}$, while synthesis temperature and ...
Lucas G. Balzat, Robert Calaminus, Yinghan Zhao, Kristina Gjorgjevikj, Igor Moudrakovski, Simon Krause, Arnd Koeppe, Britta Nestler, Bettina V. Lotsch   +8 more
wiley   +2 more sources

Dark energy and the spinning superparticle

Journal of High Energy Physics
We revisit the theory of background fields constructed on the BRST-algebra of a spinning particle with N $$ \mathcal{N} $$ = 4 worldline supersymmetry, whose spectrum contains the graviton but no other fields.
Daniel Bockisch, Ivo Sachs
doaj   +1 more source

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

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

Color‐Pure Organic Luminophores: Characteristics, Definitions, Physical Basis and Fundamental Design Principles

Angewandte Chemie, EarlyView.
Color‐pure all‐organic emitters, i.e., with narrow spectral characteristics, are intensively studied for high‐definition organic LEDs and multi‐color bioimaging. In order to guide targeted materials design, this educative review discusses spectral characteristics, proper definitions and units, and the physical basis of spectral broadening, to distill ...
Johannes Gierschner, Sunwu Song, Siyang Feng, Liangxuan Wang, Miguel Ródenas, Begoña Milián‐Medina, Min Sang Kwon   +6 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 Li3YCl6−xBrx 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

‘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