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New-Generation Refrigerants: Performance Analysis, AI-Driven Prediction, Thermodynamic Modelling, and Environmental Transition
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: https://doi.org/10.64388/IREV9I10-1715868
Abstract
The accelerating phase-down of hydrofluorocarbons (HFCs) under the Kigali Amendment to the Montreal Protocol has intensified global research into low-global-warming-potential (GWP) refrigerants that can meet the dual imperatives of environmental sustainability and thermodynamic efficiency. This paper presents a comprehensive review of emerging refrigerant classes — including hydrofluoroolefins (HFOs), hydrochlorofluoroolefins (HCFOs), natural refrigerants (CO₂, ammonia, hydrocarbons), and novel blends — evaluating their thermophysical properties, cycle performance, safety classifications, and compatibility with existing vapor-compression infrastructure. A comparative thermodynamic analysis is conducted using the coefficient of performance (COP), volumetric refrigerating capacity, and exergy efficiency as primary benchmarks. Special attention is given to HFO- 1234yf, HFO-1234ze(E), and R-290 (propane) as front-runner replacements in residential, commercial, and automotive refrigeration sectors. The study further examines regulatory frameworks, material compatibility challenges, lubricant interactions, and the economic feasibility of retrofit and drop-in solutions. Findings indicate that while no single refrigerant universally replicates the performance of incumbent HFCs, optimized low-GWP blends and CO₂-based trans critical systems demonstrate strong potential across a broad range of applications. This work aims to inform engineers, policymakers, and manufacturers in navigating the ongoing refrigerant transition toward a climate-responsible cooling industry.
Keywords
Refrigerant Science, Thermal Engineering, Environmental Impact, HFO Blends, AI/Data Mining, Vaporisation Theory, R-410A Alternatives, Regulatory Compliance
How to cite this paper
@article{1715868,
author = {Venktesh Sharma, Dr. Vikas Bansal, Dr. Rohit Mishra, Dr. Kamal Doraj},
title = {New-Generation Refrigerants: Performance Analysis, AI-Driven Prediction, Thermodynamic Modelling, and Environmental Transition},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {33-43},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715868.pdf},
abstract = {The accelerating phase-down of hydrofluorocarbons (HFCs) under the Kigali Amendment to the Montreal Protocol has intensified global research into low-global-warming-potential (GWP) refrigerants that can meet the dual imperatives of environmental sustainability and thermodynamic efficiency. This paper presents a comprehensive review of emerging refrigerant classes — including hydrofluoroolefins (HFOs), hydrochlorofluoroolefins (HCFOs), natural refrigerants (CO₂, ammonia, hydrocarbons), and novel blends — evaluating their thermophysical properties, cycle performance, safety classifications, and compatibility with existing vapor-compression infrastructure. A comparative thermodynamic analysis is conducted using the coefficient of performance (COP), volumetric refrigerating capacity, and exergy efficiency as primary benchmarks. Special attention is given to HFO- 1234yf, HFO-1234ze(E), and R-290 (propane) as front-runner replacements in residential, commercial, and automotive refrigeration sectors. The study further examines regulatory frameworks, material compatibility challenges, lubricant interactions, and the economic feasibility of retrofit and drop-in solutions. Findings indicate that while no single refrigerant universally replicates the performance of incumbent HFCs, optimized low-GWP blends and CO₂-based trans critical systems demonstrate strong potential across a broad range of applications. This work aims to inform engineers, policymakers, and manufacturers in navigating the ongoing refrigerant transition toward a climate-responsible cooling industry.},
keywords = {Refrigerant Science, Thermal Engineering, Environmental Impact, HFO Blends, AI/Data Mining, Vaporisation Theory, R-410A Alternatives, Regulatory Compliance},
month = {April},
doi = {https://doi.org/10.64388/IREV9I10-1715868}
}