Results 201 to 210 of about 1,146,792 (246)

Free Charge Generation in Organic Photoconversion Devices–the Impact of Electrostatic Potentials

open access: yesAdvanced Energy Materials, EarlyView.
Free charge generation in organic photovoltaic and photodetector devices typically requires an external driving force to separate bound excitons formed upon photoexcitation. This review details how electrostatic potentials, arising from molecular charge distributions in organic semiconductors, can impact interfacial energetic landscapes and promote ...
Emily J. Yang   +3 more
wiley   +1 more source

Covalently Locked Donor–Acceptor Block Copolymer Nanoparticles Enable Efficient, Stable and Reproducible Photocatalytic Hydrogen Evolution

open access: yesAdvanced Energy Materials, EarlyView.
To overcome the efficiency–stability trade‐off of traditional donor:acceptor blends, covalently locked all‐conjugated block copolymer nanoparticles are developed for solar hydrogen production. This strategy achieves an outstanding HER rate exceeding 120 mmol cm−2 g−1 h−1, alongside exceptional operational stability (95% retention after 96 h) and high ...
Alexandre Holmes   +14 more
wiley   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

open access: yesAdvanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

open access: yesAdvanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez   +4 more
wiley   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu   +11 more
wiley   +1 more source

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