Results 241 to 250 of about 261,766 (292)

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

Phase‐Pure and Size‐Tunable Tin Halide Perovskite Quantum Dots

open access: yesAdvanced Materials, EarlyView.
A trioctylphosphine oxide modulated protocol allows for the synthesis and study of the optical properties of a broad library of tin halide perovskite quantum dots across multiple A‐ and X‐site compositions with precise size tuning while eliminating unwanted 2D phases.
Ole F. Dressler   +7 more
wiley   +1 more source

Design and validation of a ribosome display library for synthetic nanobody selection. [PDF]

open access: yesAdv Biotechnol (Singap)
Gu W   +8 more
europepmc   +1 more source

Phase Engineering of Atomically Precise Nanoclusters (APNCs) of Gold and Beyond

open access: yesAdvanced Materials, EarlyView.
Engineering the structural phase of materials is of paramount importance for both fundamental research and practical applications. In this Review, we summarize the recent progress in controlling the phases of atomically precise nanoclusters (APNCs) of gold, silver and copper, as well as bimetallic systems. The phase‐enabled material properties of APNCs
Yitong Wang   +4 more
wiley   +1 more source

Generating Unconventional Spin‐Orbit Torques With Patterned Phase Gradients in Tungsten Thin Films

open access: yesAdvanced Materials, EarlyView.
ABSTRACT A key aim in spintronics is to achieve current‐induced magnetization switching via spin‐orbit torques without external magnetic fields. For this, the focus of recent work has been on introducing controlled lateral gradients across ferromagnet/heavy‐metal devices, giving variations in thickness, composition, or interface quality.
Lauren J. Riddiford   +9 more
wiley   +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

open access: yesAdvanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano   +5 more
wiley   +1 more source

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