Results 201 to 210 of about 81,856 (309)

Proton Irradiation Tolerance of Fully Printed Self‐Powered Carbon‐Electrode Perovskite Photodetectors

Advanced Electronic Materials, EarlyView.
Proton irradiation effects on fully printed carbon‐electrode perovskite photodiodes are systematically examined. Devices exposed to 0.5 MeV protons retain structural integrity while exhibiting defect‐induced changes in local coordination and recombination dynamics.
Almaz R. Beisenbayev, Mussakhan A. Aryslan, Yersain K. Nurmagambetov, Bauyrzhan Idreisov, Hryhorii P. Parkhomenko, Maratbek T. Gabdullin, Annie Ng, Askhat N. Jumabekov, Yerassyl Yerlanuly   +8 more
wiley   +1 more source

ZnO Doping-Induced Performance Boost in Co₂TiO₄/n-Si Schottky Self-Powered Photodetectors. [PDF]

ACS Omega
Hussaini AA, Sarilmaz A, Ozel F, Erdal MO, Yildirim M.   +4 more
europepmc   +1 more source

Surface Acidity Engineering: From Fundamental Insights to Universal Design Rules for Electrocatalytically and Electrically Active Oxides

Advanced Energy Materials, EarlyView.
This comprehensive review highlights surface acidity engineering as a versatile strategy to modulate surface charge and boost catalytic performance in functional oxides. It explores recent advances in practical implementation, structural reconstruction approaches, and mechanistic origins from diverse complementary viewpoints.
Gyu Rac Lee, Harry L. Tuller
wiley   +1 more source

Ultrasensitive photodetectors enabled by pressure-induced atomic-level optimization of graphene-based heterojunctions. [PDF]

Nat Commun
Fang Z, Wang J, Liu W, Liang Z, Pan Q, Lu P, Cui B, Lu X, Jiang J, Li Y, Gu Z, Xiu P, Wang H, Fang H.   +13 more
europepmc   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Reactive sputtered Zn₃N₂-CN _<i>x</i> hybrid films for silicon heterojunction photodetection. [PDF]

RSC Adv
Addie AJ, Ismail RA, Hassan AI, Mohammed MA.   +3 more
europepmc   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

Much improved thin-film photodiodes with novel organic interlayer. [PDF]

Natl Sci Rev
Leo K.
europepmc   +1 more source

First‐Principles Study of Structural, Mechanical, Electronic, Thermodynamical, and Optical Properties of XGaO2 (X = Rb and Cs): Unlocking Its Green Energy Potential

Advanced Physics Research, EarlyView.
This study employs density functional theory (DFT) to investigate the structural, mechanical, electronic, optical, and thermodynamic properties of RbGaO2 and CsGaO2. The calculated band structures and band‐edge positions indicate semiconducting behavior and favorable alignment for photocatalytic dye degradation and hydrogen evolution, highlighting ...
Md. Zuel Rana, Md. Saiful Islam, Jahid Hasan, Abdul Barik, Mahamud Hasan Reedoy, Afroza Khatun, Md. Abde Mannaf, Ehesanul Hoq, Neelufar Panna, M. S. Alam   +9 more
wiley   +1 more source

Stacking ensemble machine learning for predicting photodetector performance under varying illumination intensities. [PDF]

Sci Rep
Öter A, Berktaş Z, Ersöz B, Sağıroğlu Ş, Orhan E.   +4 more
europepmc   +1 more source