Results 251 to 260 of about 3,054,371 (368)

Synthesis and Optical Properties of Ln2Ln′2‐Tetranuclear Lanthanide(III) Complexes

open access: yesEuropean Journal of Inorganic Chemistry, EarlyView.
A series of new heterotetranuclear lanthanide complexes (Ln2Ln′2) is synthesized to study Ln‐to‐Ln′ energy transfer. Using stable dinuclear precursors, Tb2Yb2 and Nd2Tb2 are prepared and show visible/NIR emission. Reduced Tb3+ lifetimes suggest energy transfer to Yb3+ or Nd3+, offering a modular route to mixed‐lanthanide systems.
Maria Storm Thomsen   +2 more
wiley   +1 more source

Exploring Platinum Thin Films as Electrodes for High‐Temperature and ‐Pressure Electrochemical Studies in Aqueous Systems

open access: yesElectrochemical Science Advances, EarlyView.
ABSTRACT This work reports a methodology for the fabrication of Pt thin‐film electrodes for electrochemical studies in hydrothermal systems. The research process was meticulous, with particular attention paid to the multilayer Ti/Pt/Ti/Al2O3 film structure and annealing conditions that are expected to impact the morphology of the films, surface ...
Muna Abdulaziz   +5 more
wiley   +1 more source

Possible ferrimagnetic coupling in light-rare-earth transition-metal intermetallic compounds [PDF]

open access: green, 1994
Zhigang Zhao   +4 more
openalex   +1 more source

Interfacial adhesion effects of liquid metal printed electronics on general substrates: Mechanisms and applications

open access: yesInfoMat, EarlyView.
Printed electronics technology is known for its low cost, large area, ease of operation, and high speed, making it suitable for flexible electronic devices. Liquid metals, particularly gallium‐based alloys, are ideal for creating stretchable electronics due to their conductivity.
Chunxue Wan   +5 more
wiley   +1 more source

Machine Learning Helps Data Mining to Build Descriptor Databases for Lithium‐Ion Batteries

open access: yesMetalMat, EarlyView.
Machine learning‐driven research methodologies for lithium‐ion batteries are gaining increasing favor among researchers. By leveraging machine learning algorithms to extract essential descriptor data, this approach can substantially accelerate the development of high‐performance lithium‐ion batteries.
Xiran Zhao   +5 more
wiley   +1 more source

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