Results 81 to 90 of about 86,402 (258)
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Opportunities of Semiconducting Oxide Nanostructures as Advanced Luminescent Materials in Photonics
The review discusses the challenges of wide and ultrawide bandgap semiconducting oxides as a suitable material platform for photonics. They offer great versatility in terms of tuning microstructure, native defects, doping, anisotropy, and micro‐ and nano‐structuring. The review focuses on their light emission, light‐confinement in optical cavities, and
Ana Cremades +7 more
wiley +1 more source
Computational theories of learning
This research paper, authored by Disha (2025), introduces a novel theoretical framework titled Computational Theories of Learning, which seeks to unify cognitive science, artificial intelligence, and mathematical computation into a coherent understanding of how learning emerges, evolves, and self-optimizes within dynamic environments.
openaire +2 more sources
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Spectrum prediction improvement with phenomenological statistical learning
Statistical learning can be used for spectrum prediction, significantly reducing the large computational resources required by simulation software. However, traditional statistical learning methods face challenges such as interpretability and issues with
Zijian Zhang
doaj +1 more source
Single‐Chromophore Homojunction Organic Solar Cells: A Path to Simplicity and Efficiency
This perspective discusses how the intrinsic optoelectronic properties of organic semiconductors, their molecular packing in the solid‐state, and internal energetic gradients within a device can enable free‐charge carrier generation in homojunction organic solar cells.
Shaun McAnally +2 more
wiley +1 more source
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
This review exploits the crucial role of computational methods in discovering and optimizing materials for redox flow batteries (RFBs). Integration of high‐throughput computational screening (HTCS) and machine learning (ML) accelerates materials ...
Lina Tang +3 more
doaj +1 more source

