Skip to content

PeerfordResearch intelligence

Countries
Institutions
Researchers
Fields
Rankings
Compare
Commons

Search institutions, scholars, countries and publications

Countries
Institutions
Researchers
Fields
Rankings
Compare

CommonsWhere researchers talk about their work

Search institutions, scholars, countries and publications

Every figure here is counted by Peerford from the works themselves, the same way for every institution.

Browse

Countries
Institutions
Researchers
Fields
Rankings
Commons, for researchers

About

How Peerford counts
Compare institutions
Privacy
Terms of use

Contact

hello@peerford.com
https://wa.me/peerford · WhatsApp

Language

English
FrançaisFrench
PortuguêsPortuguese
العربيةArabic

Theme

SystemLightDark

V. E. Okoruwa · Peerford

University of Ibadan / Scholars

VO

V. E. Okoruwa

University of Ibadan

Publishing since 2026

Catalysis
Computational Mechanics
Fluid Flow and Transfer Processes

Their record on OpenAlex
Download CV:PDF Word
Who they write with Where their co-authors are Every publication
Is this you? Sign in to edit your profile

Publications: 12026
Citations: 0to those papers
h-index: 0i10-index 0
Field-weighted impact: 0.001.00 is the world average
World top 10%: 0%0 of 1 scored papers
Open access: 100%1 papers free to read

What they work on

From the classification of each paper

Subfields

Catalysis1100%
Computational Mechanics1100%
Fluid Flow and Transfer Processes1100%

Physical Sciences

Topics most written on

Advanced Combustion Engine Technologies1
Ammonia Synthesis and Nitrogen Reduction1
Combustion and flame dynamics1

Publications

1 in all

Machine Learning-Based Prediction of Combustion Characteristics of Ammonia-Blended Fuels for Automotive Applications
2026Journal of Global Ecology and EnvironmentJournalOpen access0 citations10.56557/jogee/2026/v22i210498

Where they publish

Journal of Global Ecology and Environment1

How it can be read

100% free to read

Diamond 1 · 100%Free to read and to publish

Development goals addressed

From each paper’s title and abstract

9Industry, innovation and infrastructure1

Most cited

Machine Learning-Based Prediction of Combustion Characteristics of Ammonia-Blended Fuels for Automotive Applications
Journal of Global Ecology and Environment9
20260 citationsOpen access · Diamond