Results 101 to 110 of about 650,978 (244)
Batteries &Supercaps, Volume 6, Issue 1, January 2023., 2023 We introduce a computer algorithm that incorporates the experience of battery researchers to extract information from experimental data reproducibly. This enables the fitting of complex models that take up to a few minutes to simulate. For validation, we process full‐cell GITT measurements to characterize the diffusivities of both electrodes non ...
Yannick Kuhn +3 more
wiley +1 more source
Transport Resistance Dominates the Fill Factor Losses in Record Organic Solar Cells
Advanced Energy Materials, EarlyView.Organic photovoltaics are a promising solar cell technology, but even the record devices with 20% efficiency have significant fill factor losses due to low active layer conductivities. In this Perspective, the authors describe the origin of these losses, discuss experimental methods for their quantification, and explain how to minimize them to optimize
Chen Wang +6 more
wiley +1 more source
Advanced Energy Materials, EarlyView.This concept article provides a comprehensive introduction and overview of how (fully) organic batteries and the respective redox‐active organic electrode materials work. Options for cell setups are discussed, as well as the difference between half‐ and full‐cells and the relevance of the two types. At the material level, the difference between organic
Robin Wessling +2 more
wiley +1 more source
Advanced Energy and Sustainability Research, EarlyView.Light‐driven H2 evolution catalysis is reported for oleylamine‐capped MCo Prussian blue analogs (PBAs, M = Ni, Co, Zn, Cu) within phospholipid bilayers and using a ruthenium‐based amphiphilic photosensitizer. The hydrophobic interactions between the active units bring them in close proximity facilitating catalysis.
Subrata Mandal +5 more
wiley +1 more source
Rigidity for Einstein manifolds under bounded covering geometry [PDF]
arXivIn this note we prove three rigidity results for Einstein manifolds with bounded covering geometry. (1) An almost flat manifold $(M,g)$ must be flat if it is Einstein, i.e. $\operatorname{Ric}_g=\lambda g$ for some real number $\lambda$. (2) A compact Einstein manifolds with a non-vanishing and almost maximal volume entropy is hyperbolic.
arxiv
Electrodeposited Iron‐Incorporated Cobalt Phosphide for Improved Supercapacitor Applications
Advanced Energy and Sustainability Research, EarlyView.The electrodeposition method has been used to synthesize Fe–CoP deposited on nickel foam, resulting in excellent cycling stability and capacitance retention compared to CoP and FeP. Furthermore, a detailed charge storage mechanism, emphasizing the enhanced electrochemical performance has been discussed. Supercapacitors have gained significant attention
Gaurav Pandey +2 more
wiley +1 more source
On weakly Einstein Kähler surfaces [PDF]
arXivRiemannian four-manifolds in which the triple contraction of the curvature tensor against itself yields a functional multiple of the metric are called weakly Einstein. We focus on weakly Einstein K\"ahler surfaces. We provide several conditions characterizing those K\"ahler surfaces which are weakly Einstein, classify weakly Einstein K\"ahler surfaces ...
arxiv
Impact of Host–Emitter Interactions on Light Amplification in Laser Dyes
Aggregate, EarlyView.A new organic semiconductor laser material, QSBCz, based on stilbene tetramer, is presented. Compared to high‐performance laser material with stilbene dimer, BSBCz, increased conjugation contributes to enhancing radiative rate constant and gain cross‐section.
Masashi Mamada +7 more
wiley +1 more source
Advances in exosome biomarkers for cervical cancer
Cancer Medicine, Volume 11, Issue 24, Page 4966-4978, December 2022., 2022 Cancer‐derived exosomes may promote CC metastasis by boosting cellular epithelial‐mesenchymal transformation (EMT), controlling the proliferation, invasion, or migration of cancer cells, as well as influencing immune escape and aiding angiogenesis.
Zihan Ran +5 more
wiley +1 more source
Machine Learning‐Assisted Simulations and Predictions for Battery Interfaces
Advanced Intelligent Systems, EarlyView.This review summarizes machine learning (ML)‐assisted simulations and predictions at battery interfaces. It highlights how employing ML algorithms with machine vision, enables the lithium dendrite growth simulation, the solid–electrolyte interphase formation, and other interfacial dynamics.
Zhaojun Sun +4 more
wiley +1 more source