Results 201 to 210 of about 251,351 (310)

A New Customizable Surfactant LLPS Strategy for Sustainable and Highly Efficient Radioactive Metal Ion Separation

open access: yesAdvanced Science, EarlyView.
A diluent‐free, customizable liquid–liquid phase separation (LLPS) platform enables highly efficient radioactive metal ion extraction and stripping. By encapsulating hydrophobic extractants into an ionic surfactant‐rich condensed phase, this LLPS system leverages synergistic electrostatic and coordination interactions.
Ruihan Yan   +7 more
wiley   +1 more source

Suppressed Auger Heating of Hot Carriers in Cu‐Doped Colloidal Quantum Wells

open access: yesAdvanced Science, EarlyView.
ABSTRACT Auger heating represents a major bottleneck for hot carrier (HC) relaxation in colloidal quantum wells (CQWs), delaying carrier accumulation in band‐edge states and diminishing performance in light‐emitting applications. To address this issue, we introduce copper doping in CdSe CQWs to create midgap states, which efficiently suppresses Auger ...
Junhong Yu   +6 more
wiley   +1 more source

Correction: "Distinguishing Phylogenetic Level-2 Networks with Quartets and Inter-Taxon Quartet Distances". [PDF]

open access: yesBull Math Biol
Holtgrefe N   +6 more
europepmc   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

open access: yesAdvanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu   +8 more
wiley   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

open access: yesAdvanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen   +6 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

Normalized Caputo-Fabrizio SVIR modeling and bifurcation analysis. [PDF]

open access: yesSci Rep
Shafqat R   +3 more
europepmc   +1 more source

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