Results 131 to 140 of about 137,793 (228)
This review highlights recent advancements in stabilizing single metal atoms on graphitic carbon nitride emphasizing innovative synthesis strategies and emerging applications in electrocatalysis, photocatalysis and organic transformations, along with key challenges and future perspective. Abstract Emerging as a new frontier in catalysis science, single‐
Wenyao Zhang +6 more
wiley +1 more source
Assessing projected quantum kernels for the classification of IoT data
The use of quantum computing for machine learning is among the most promising applications of quantum technologies. Quantum models inspired by classical algorithms are developed to explore some possible advantages over classical approaches.
Francesco D’Amore +6 more
doaj +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas +6 more
wiley +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
In this study, we introduce a hybrid quantum machine learning method to identify Normal signal, DoS, and Fuzzy attacks on the CAN bus utilized in autonomous vehicles.
Meghana R +2 more
doaj +1 more source
Diffusion–Model–Driven Discovery of Ferroelectrics for Photocurrent Applications
We developed a diffusion model–based generative AI and high‐throughput screening framework that accelerates the discovery of photovoltaic ferroelectrics. By coupling AI driven crystal generation with machine learning and DFT screening, we identified Ca3P2 and LiCdP as new ferroelectric materials exhibiting strong polarization, feasible switching ...
Byung Chul Yeo +3 more
wiley +1 more source
Electrolyte Additive Strategies in Aqueous Zn‐Ion Batteries: Recent Advances and Prospects
This article provides a comprehensive overview of the current status and future development directions of AZIBs electrolyte additives in three aspects: stabilizing zinc anodes (uniform deposition, inhibition of dendritic crystals), protecting cathodes (structural stability, inhibition of dissolution), and enhancing electrolyte stability (wider ...
Yuanze Yu +7 more
wiley +1 more source
This review surveys nanoparticle‐based strategies to enhance adoptive cell therapy, particularly CAR‐T cell approaches, in solid tumor treatment. It describes how nanoparticles can improve tumor immunogenicity and T‐cell infiltration while reducing toxicity, and how they enable in vivo CAR‐T cell generation.
Erica Frostegård +19 more
wiley +1 more source

