Evidence map›Paper›PMID 37901555›Full record

ArticleACS omega2023

Investigation into the Ideal Concoction for Performance and Emissions Enhancement of Jatropha Biodiesel-Diesel with CuO Nanoparticles Using Response Surface Methodology.

Elumalai Ramachandran, Ravi Krishnaiah, Elumalai Perumal Venkatesan, Saboor Shaik, Chanduveetil Ahamed Saleel, Fayaz Hussain

Open access · goldAbstract read
In one paragraph

Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
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

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Synthesis of FeMolecules (Basel, Switzerland) · 2024
    Article
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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

6 authors at 4 institutions in 3 countries.

Elumalai RamachandranSchool of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India.ORCID https://orcid.org/0000-0002-4970-8777
Ravi KrishnaiahSchool of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India.ORCID https://orcid.org/0000-0001-7911-0437
Elumalai Perumal VenkatesanDepartment of Mechaical Engineering, Aditya Engineering College, Surampalem 533437, India.ORCID https://orcid.org/0000-0002-7536-8200
Saboor ShaikSchool of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India.ORCID https://orcid.org/0000-0002-0490-4766
Chanduveetil Ahamed SaleelDepartment of Mechanical Engineering, College of Engineering, King Khalid University, PO Box 394, Abha 61421, Saudi Arabia.
Fayaz HussainModeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam.
Vellore Institute of Technology University · INAditya Birla (India) · INKing Khalid University · SATon Duc Thang University · VN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present work covers the preparation of biodiesel from jatropha oil through the transesterification process followed by its characterization, and furthermore, performance and emission analyses were done in terms of blending biodiesel with fossil diesel and CuO nanoparticles. Jatropha biodiesel blends (B10, B20, and B30) were chosen for this preliminary investigation based on the observation that B20 outperformed other blends. Next stage B20 with copper oxide (CuO) nanoparticle concentrations of 25, 50, 75, and 50 ppm are used to examine the performance and emission characteristics of a constant speed single cylinder, 4-stroke, 3.5 kW compression ignition (CI) engine. Finally, The response surface methodology (RSM) was utilized to determine the optimal nanoparticle concentration for B20. The results revealed that the blend of B20 with 80 ppm nanoparticles had the highest desirability (0.9732), and the developed RSM model was able to predict engine responses with a mean absolute percentage error (MAPE) of 3.113%. A confirmation test with an error in prediction of less than 5% verified the model's adequacy. When comparing optimized B20CuO80 to diesel, brake specific energy consumption (BSEC) increased by 8.49% and brake thermal efficiency (BTE) was lowered by 3.34%. Hydrocarbon (HC), carbon monoxide (CO), carbon dioxide (CO

Identifiers

PMID37901555
PMCPMC10601086
OpenAlexW4387494034

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.