ReviewHeliyon2019
Progress on pharmaceutical drugs, plant extracts and ionic liquids as corrosion inhibitors.
Review in Heliyon, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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
8 citing papers in PubMed, 119 citations in OpenAlex.
- Assessment of Sustainable Ethanolamine-Based Protic Ionic Liquids with Varied Carboxylic Acid Chains as Corrosion Inhibitors for Carbon Steel in Saline Environments.Molecules (Basel, Switzerland) · 2025Article
- Synthesis and evaluation of CuNi-MOF as a corrosion inhibitor of AISI 304 and 316 stainless steel in 1N HCl solution.Heliyon · 2025Article
- Article
- Investigation of mild steel corrosion inhibition in acidic media by Viola extract based on bulk and nanometer size.Scientific reports · 2024Article
- Article
- Green tea and tulsi extracts as efficient green corrosion inhibitor for aluminum alloy in alkaline medium.Heliyon · 2023Article
- Investigation of Dracocephalum extract based on bulk and nanometer size as green corrosion inhibitor for mild steel in different corrosive media.Scientific reports · 2023Article
- The role of pH in corrosion inhibition of tin using the proline amino acid: theoretical and experimental investigations.RSC advances · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the past, lives and wealth have been lost due to corrosion in almost all engineering fields. Not only this, the cost of reviving damaged equipments in the industry due to corrosion contributed a lot to the gross domestic product of a nation. Thus, all hands must be on desk to combat this harzadous act via time to time research on its final resolution. However, current research works have revealed effective and reliable corrosion inhibitors from pharmaceutical drugs, plant extracts and ionic liquids as organic green corrosion inhibitors (OGCIs) with accommodative attributes such as being environmentally friendly, readily available, biodegradable, non-harmful, relatively cheap and many others to mention a few. This paper opens readers mind into the detailed classifications, mechanisms and active functional groups of these eco-friendly OGCIs. Not only the corrosion efficiency calculation ways but also influencing factors on efficiency were presented. Plant extracts, pharmaceutical drugs, ionic liquids and synthetic inhibitors, as among major sources of OGCIs, used in preventing material corrosion in corrosive media were separately and comprehensively examined. The significance of values obtained from simulating presented mathematical models governing OGCIs kinetics, adsorption isotherm and adsorption thermodynamics was also included. In conclusion, beneficial recommendations for both current and prospective researchers in the field of Corrosion Engineering were presented.
Indexed as
Identifiers
What OpenQuestion holds
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.