Results 241 to 250 of about 60,387 (338)

Hetero-Diels-Alder and CuAAC Click Reactions for Fluorine-18 Labeling of Peptides: Automation and Comparative Study of the Two Methods. [PDF]

open access: yesMolecules
Maujean T   +8 more
europepmc   +1 more source

Technetium-99m Verses Fluorine-18

open access: yesInternational Journal of Nuclear Medicine Research, 2018
openaire   +1 more source

Azaporphyrinoid‐Based Photo‐ and Electroactive Architectures for Advanced Functional Materials

open access: yesAdvanced Materials, EarlyView.
A long‐standing collaboration between the Torres and Guldi groups has yielded diverse azaporphyrinoid‐based donor‐acceptor nanohybrids with promising applications in solar energy conversion. This conspectus highlights key molecular platforms and structure‐function relationships that govern light and charge management, supporting the rational design of ...
Jorge Labella   +3 more
wiley   +1 more source

Resistance of Oil‐Infused PDMS with Different Macroporosities Against Bacterial Attachment

open access: yesAdvanced Materials Interfaces, EarlyView.
In this study, a series of environmentally benign, nonfluorinated liquid paraffin‐infused porous PDMS networks with varying porosities is created. By introducing different homogenous and heterogenous bulk structures and varying interfacial roughness by sugar and salt templating, the role of porosity and oil availability on the resistance against ...
Regina Kopecz   +3 more
wiley   +1 more source

Unveiling SEI Formation Dynamics of PEO: LiTFSI with Lithium Metal: An In Situ Approach Combining SIMS, XPS, and CTTA

open access: yesAdvanced Materials Interfaces, EarlyView.
This study examines the interphase formation of polyethylene oxide (PEO) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) with lithium metal. Utilizing secondary ion mass spectrometry (SIMS), X‐ray photoelectron spectroscopy (XPS), and coulometric titration time analysis (CTTA), it analyzes the solid electrolyte interphase (SEI) layer's ...
Timo Weintraut   +5 more
wiley   +1 more source

Deep Learning Analysis of Solid‐Electrolyte Interphase Microstructures in Lithium‐Ion Batteries

open access: yesAdvanced Materials Interfaces, EarlyView.
A transformer‐based deep learning model is developed for segmenting and analyzing high‐resolution TEM images of the solid‐electrolyte interphase (SEI) in lithium‐ion batteries. The model is trained on DFT‐based simulated images and predicts SEI grain and grain boundaries, revealing key microstructural features that govern ion transport and degradation.
Ishraque Zaman Borshon   +4 more
wiley   +1 more source

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