Evidence map›Paper›PMID 41656366›Full record

ArticleScientific reports2026

High-performance adsorption of sulfamethoxazole and phenol using graphene-like carbon derived from glucose.

Lakshmi Prasanna Lingamdinne, Ganesh Kumar Reddy Angaru, Bhanu Shrestha, Janardhan Reddy Koduru, Rama Rao Karri

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lakshmi Prasanna LingamdinneDepartment of Environmental Engineering, Kwangwoon University, Seoul, 01897, Republic of Korea.
Ganesh Kumar Reddy AngaruInstitute of Municipal and Environmental Engineering, College of Civil Engineering, Huaqiao University, Xiamen, 361021, Fujian, China.
Bhanu ShresthaDepartment of Information Convergence System, Graduate School of Smart Convergence, Kwangwoon University, Seoul, 01897, Republic of Korea.
Janardhan Reddy KoduruDepartment of Environmental Engineering, Kwangwoon University, Seoul, 01897, Republic of Korea. reddyjchem@gmail.com.
Rama Rao KarriChemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan, BE-1410, Brunei Darussalam. kramarao.iitd@gmail.com.

Funding

National Research Foundation of Korea 2021R1F1A1063793
6 · The paper itself

Abstract

The eradication of sulfamethoxazole (SMX) and phenol from water sources is critical due to their detrimental impact on the aquatic ecological balance. In this study, a porous graphene-like carbon (GLC-900) material was synthesized using glucose as the carbon precursor via pyrolysis at 900 °C. The GLC-900 characterization shows a significant Brunauer–Emmett–Teller (BET) surface area of 935.24 m²/g, enhancing its adsorption capacity for both SMX and phenol. The adsorption capacities for SMX and Phenol were 289.23 and 231.73 mg/g, respectively, as determined by the Langmuir model. The porous structure of GLC-900 enabled rapid adsorption, with equilibrium reached within 60 min for both pollutants. Thermodynamic analysis confirmed that the process was spontaneous, endothermic, and driven by physisorption. The physisorption between GLC-900 and the pollutants involved was demonstrated via hydrogen bonding, hydrophobic interactions, and π-π stacking interactions, as confirmed by advanced analytical techniques and experiments. Additionally, GLC-900 maintained its removal efficiency for SMX and Phenol over four reuse cycles with above 90% removal. These findings suggest that GLC-900, as a biobased material with high adsorption capacity and fast kinetics, holds significant potential for wastewater treatment applications.

Indexed as

High-performance adsorbentsHydrogen bondingPorous carbon materialsSurface functionalizationWastewater treatment

Identifiers

PMID41656366
PMCPMC12948963

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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.