Results 141 to 150 of about 2,283,559 (289)

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

Computational Protein Redesign of Bacteriophages by Using Evolutionary Algorithms. [PDF]

open access: yesBiology (Basel)
Armas R   +4 more
europepmc   +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

An Analysis of Vocal Features for Parkinson's Disease Classification Using Evolutionary Algorithms. [PDF]

open access: yesDiagnostics (Basel), 2022
Dao SVT   +5 more
europepmc   +1 more source

Moiré Phase Mapping in Twisted Bilayer Liquid Crystals with Reconfigurable Light Polarization States

open access: yesAdvanced Materials, EarlyView.
Twisted bilayer liquid crystals are developed by vertical stacking assembly of two liquid crystals having designer domains and optical properties. These moiré‐symmetry, twisted liquid crystals demonstrate reconfigurable polarization states, moiré patterns and phases controlled by twist angles, providing a route to design active optical devices for ...
Jordan A. Wilson   +7 more
wiley   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

open access: yesAdvanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh   +5 more
wiley   +1 more source

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