ReviewChemSusChem2026
Surface-Enhanced Raman Spectroscopy for Lithium Battery Interfaces.
Review in ChemSusChem, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The electrode/electrolyte interface has a significant impact on the performance of lithium batteries. At the interface, the charged electrode surface, electric double layer (EDL), and solid electrolyte interphase/cathode electrolyte interphase (SEI/CEI) change with voltage, electrolyte, and surface structure. Although post-cycling characterization can identify many interfacial products, it is often difficult to determine when these species form or how they change during charge and discharge. Surface-enhanced Raman spectroscopy (SERS) can detect interfacial Raman signals, allowing specific electrolyte components, intermediates, and interfacial products to be monitored under operating conditions. This review discusses the application of SERS in studies of lithium battery interfaces, including SERS enhancement mechanisms and substrate structures. Typical applications of SERS are summarized for anode interfaces, cathode interfaces, and Li-O
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.