A hybrid mechanistic machine learning approach to model industrial network dynamics for sustainable design of emerging carbon capture and utilization technologies-Reference-Cited by-同舟云学术

A hybrid mechanistic machine learning approach to model industrial network dynamics for sustainable design of emerging carbon capture and utilization technologies

Published:2023 Issue:20 Volume:7 Page:5129-5146
ISSN:2398-4902
Container-title:Sustainable Energy & Fuels
language:en
Short-container-title:Sustainable Energy Fuels

Author:

Shekhar Abhimanyu Raj¹,Moar Raghav R.²,Singh Shweta¹³⁴^ORCID

Affiliation:

1. Agricultural & Biological Engineering, Purdue University, West Lafayette, USA

2. Microsoft Research, Hyderabad, India

3. Environmental & Ecological Engineering, Purdue University, West Lafayette, USA

4. Davidson School of Chemical Engineering (By Courtesy), Purdue University, West Lafayette, USA

Abstract

Industrial networks consist of multiple industrial nodes interacting with each other through material exchanges that support the overall production goal of the network.

Funder

Division of Chemical, Bioengineering, Environmental, and Transport Systems

National Science Foundation

Publisher

Royal Society of Chemistry (RSC)

Subject

Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

Link

http://pubs.rsc.org/en/content/articlepdf/2023/SE/D3SE01032E

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5. Thermolysis of waste plastics to liquid fuelA suitable method for plastic waste management and manufacture of value added products—A world prospective

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