Results 101 to 110 of about 13,841 (218)

Enhanced Performance of Optoelectronic Devices Using Metal Chalcogenide Complex Ligands‐Capped InAs/ZnSe Quantum Dots as Electron Transport Layers

open access: yesAdvanced Energy Materials, EarlyView.
Thin‐shell InAs/ZnSe quantum dots functionalized with metal chalcogenide ligands were employed as electron transport layers in organic optoelectronic devices, yielding optimized conduction band alignment and film morphology. Consequently, the devices achieved enhanced charge transport, a detectivity of ∼1013 Jones, and a power conversion efficiency of ...
Yonghoon Choi   +8 more
wiley   +1 more source

Verification and Mitigation of Proton‐Induced Non‐Ionizing Damage in Perovskite Solar Cells for Space Applications

open access: yesAdvanced Energy Materials, EarlyView.
Metal‐halide perovskite solar cells offer high‐efficiency power for orbital missions but suffer from permanent proton‐induced degradation. This work identifies non‐ionizing energy loss (NIEL) as the primary driver of irreversible failure, inducing atomic displacements and microcracks in the high‐fluence regime. Through energy‐tuned mapping and scalable
Jangwon Byun   +10 more
wiley   +1 more source

Leveraging the Amorphous Nature of Sn–P Alloys for Improved Stability and Energy Density in Na‐Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
Amorphous SnP3 undergoes homogeneous solid‐solution sodiation, delivering exceptional cycling stability and volumetric capacity. In contrast, crystalline Sn4P3 phase‐separates into Na‐Sn and Na‐P domains, causing rapid capacity decay and severe pulverization.
Yixiang Zhang   +10 more
wiley   +1 more source

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

open access: yesAdvanced 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

Efficient Flexible Monolithic Perovskite/CIGS Tandem Solar Cell by Using Two‐Step Hybrid Deposition Approach

open access: yesAdvanced Energy Materials, EarlyView.
Novel low‐temperature two‐step hybrid (co‐evaporation/solution) processing suppresses Zn‐induced perovskite degradation in monolithic perovskite/CIGS tandems. Lewis‐base additive engineering restores high crystallinity under the reduced‐temperature constraint.
Muhammad Rehan   +17 more
wiley   +1 more source

Synergistic Optimization of Cathode Composite Architecture and Stack Pressure for High‐Performance All‐Solid‐State Chloride‐Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
Composite cathode engineering and stack pressure co‐optimization enable a high‐performance all‐solid‐state chloride‐ion battery based on a VOCl/CsSn₀.₉In₀.₀₆₇Cl3/In architecture, delivering 169 mAh g−1 with 500‐cycle durability. Electrode‐resolved impedance tracking via distribution of relaxation times revealed progressive interphase and charge ...
Soutam Panja   +7 more
wiley   +1 more source

Maximum Stability Point Tracking Stabilizes Wide‐Bandgap Mixed‐Halide Perovskite Solar Cells

open access: yesAdvanced Energy Materials, EarlyView.
A maximum stability point tracking (MSPT) strategy suppresses charge trapping‐induced halide segregation, enabling wide‐bandgap perovskite solar cells to achieve significantly enhanced operational stability compared to conventional maximum power point tracking (MPPT).
Seongheon Kim   +7 more
wiley   +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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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