Research using a deep learning model built on AIZOTH’s AI analytics platform, Multi-Sigma® to accurately predict the 100-year Global Warming Potential (GWP100) of single-component refrigerants has been published in ACS Sustainable Chemistry & Engineering, a peer-reviewed journal of the American Chemical Society (ACS).
The study was conducted by AIZOTH researchers.
Against the backdrop of international climate targets and regulatory requirements such as the Kigali Amendment, the study presents a practical prediction framework for rapidly identifying refrigerant candidates with lower environmental impact.
This research was supported under Project JPNP23001 of the New Energy and Industrial Technology Development Organization (NEDO).
Reference
NEDO Project JPNP23001
https://www.nedo.go.jp/activities/ZZJP_100244.html
For further details, please refer to the paper below.
Publication Details
Title
A Deep Learning Framework for Predicting Global Warming Potential of Refrigerants for Sustainable Chemical Design
Authors
Navin Rajapriya and Kotaro Kawajiri
Journal
ACS Sustainable Chemistry & Engineering (2025), 13, 45, 19528–19535
Publication Year
2025
