Results 81 to 90 of about 1,576 (215)

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

open access: yesAdvanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair   +3 more
wiley   +1 more source

AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing

open access: yesAdvanced Materials, EarlyView.
This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee   +21 more
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

Path‐Decoupled Cation‐Eutaxy III–V van der Waals Memristive Semiconductors for Mitigating the Neuromorphic Accuracy‐Energy Trade‐off

open access: yesAdvanced Materials, EarlyView.
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae   +13 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

Emergent Spin Supersolids in Frustrated Quantum Materials

open access: yesAdvanced Materials, EarlyView.
This review highlights developments in the study of spin super‐solids in frustrated quantum materials. Advanced experimental characterizations and computational studies enable a comprehensive understanding of the driving mechanisms of spin super‐solidity in various layered transition‐metal compounds, bridging materials, experiments, and theory aspects.
Yixuan Huang   +2 more
wiley   +1 more source

Large‐Scale Determination of Frontier Orbital Energies of Disordered Small‐Molecule Organic Semiconductors Using Exciplex Emission Spectra

open access: yesAdvanced Materials, EarlyView.
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald   +7 more
wiley   +1 more source

Lead Halide Perovskite Photoelectrocatalysis

open access: yesAdvanced Materials, EarlyView.
Lead halide perovskite semiconductors have emerged as highly promising materials for solar fuel and chemical synthesis. This perspective discusses advances made in the rational photoelectrode design to improve solar‐to‐chemical conversion, product scope, and scalability.
Virgil Andrei
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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