Results 131 to 140 of about 246,254 (290)

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

open access: yesAdvanced Materials, EarlyView.
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

Algorithmic Bias as a Core Legal Dilemma in the Age of Artificial Intelligence: Conceptual Basis and the Current State of Regulation

open access: yesLaws
This article examines algorithmic bias as a pressing legal challenge, situating the issue within the broader context of artificial intelligence (AI) governance. We employed comparative legal analysis and reviewed pertinent regulatory documents to examine
Gergely Ferenc Lendvai   +1 more
doaj   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

open access: yesAdvanced Materials, EarlyView.
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

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena   +3 more
wiley   +1 more source

Monolithic 3D‐Integrated All‐Solid Ion‐Gated Carbon Nanotube Transistors With Tunable Ionic Conductance for Multi‐Timescale Reservoir Computing

open access: yesAdvanced Materials, EarlyView.
A dual‐timescale reservoir based on monolithically 3D (M3D)‐integrated CNT solid ion‐gated transistors is demonstrated. Tunable ionic dynamics and pulse‐engineered operation enable linear and symmetric synaptic updates. The M3D‐integrated array achieves robust temporal encoding and accurate classification of moving MNIST sequences, highlighting its ...
Haksoon Jung   +9 more
wiley   +1 more source

Field‐Programmed Anisotropy in Magneto‐Piezoelectric Composites for Material‐Encoded Mechanoperception

open access: yesAdvanced Materials, EarlyView.
Field‐programmed anisotropy imparts material‐level intelligence to soft composites. Magnetic torque dynamics drive magneto‐piezoelectric nanowires from random dispersion into deterministic axial alignment. The resulting hierarchical percolation networks confine electromechanical coupling to specific axes and intrinsically decouple superposed force ...
Yubin Kim   +9 more
wiley   +1 more source

Resolving Heterogeneity of Targeted Lipid Nanoparticles Through Solution‐Based Biophysical Analyses

open access: yesAdvanced Materials, EarlyView.
AF4‐UV‐DLS‐MALS‐SAXS resolves previously inaccessible targeted lipid nanoparticle (tLNP) subpopulations that differ in size, shape, and composition. Correlation of subpopulation‐resolved biophysical properties with in vivo RNA delivery reveals that targeted placental transfection is associated with distinct tLNP subpopulations rather than ensemble ...
Hannah C. Geisler   +14 more
wiley   +1 more source

Intrinsically interpretable machine learning-based building energy load prediction method with high accuracy and strong interpretability

open access: yesEnergy and Built Environment
Black-box models have demonstrated remarkable accuracy in forecasting building energy loads. However, they usually lack interpretability and do not incorporate domain knowledge, making it difficult for users to trust their predictions in practical ...
Chaobo Zhang   +3 more
doaj   +1 more source

Navigating Lipid Nanostructure Design Space Through Continuous Microfluidic Automation

open access: yesAdvanced Materials, EarlyView.
LipidXplorer is a novel microfluidic platform which enables rapid navigation of lipid particle design space for high‐resolution phase mapping, lipid nanoparticle optimization, membrane biophysics, and functional nanomaterial discovery. It combines programmable composition control, continuous nanoparticle formation, and automated well‐plate collection ...
Bradley Diggines   +10 more
wiley   +1 more source

Mechanistically Interpretable Artificial Intelligence for Designing Oxygen Electrocatalysts

open access: yesAdvanced Materials, EarlyView.
Mechanistically interpretable artificial intelligence screens nearly seven million perovskite compositions and identifies key descriptors—d‐p hybridization and densification resistance—that govern oxygen electrocatalysis. The discovered BaCo0.8Nb0.1Zr0.1O3‐δ achieves a record 2.68 W cm−2 peak power density at 600°C with over 500 h of durable operation ...
Xueyu Hu   +15 more
wiley   +1 more source

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