ArticleMolecules (Basel, Switzerland)2022
A Simple Route to Produce Highly Efficient Porous Carbons Recycled from Tea Waste for High-Performance Symmetric Supercapacitor Electrodes.
Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Tea-residue-derived carbon nanomaterials for adsorption-degradation coupling: mechanistic insights into pollutant removal and sustainability challenges.RSC advances · 2026Review
- Manganese Oxide-Doped Hierarchical Porous Carbon Derived from Tea Leaf Waste for High-Performance Supercapacitors.International journal of molecular sciences · 2024Article
- Nanoporous Carbon from Oil Palm Leaves via Hydrothermal Carbonization-Combined KOH Activation for Paraquat Removal.Molecules (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
High-performance porous carbons derived from tea waste were prepared by hydrothermal treatment, combined together with KOH activation. The heat-treatment-processed materials possess an abundant hierarchical structure, with a large specific surface of 2235 m
Indexed as
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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.