Determination of the heat capacity of cellulosic biosamples employing diverse machine learning approaches-Reference-Cited by-同舟云学术

Determination of the heat capacity of cellulosic biosamples employing diverse machine learning approaches

Published:2022-04-13 Issue:6 Volume:10 Page:1925-1939
ISSN:2050-0505
Container-title:Energy Science & Engineering
language:en
Short-container-title:Energy Science & Engineering

Author:

Karimi Mohsen¹,Khosravi Marzieh²,Fathollahi Reza³,Khandakar Amith⁴^ORCID,Vaferi Behzad⁵^ORCID

Affiliation:

1. Laboratory of Separation and Reaction Engineering (LSRE), Associate Laboratory (LSRE/LCM), Department of Chemical Engineering Faculty of Engineering, University of Porto Porto Portugal

2. Department of Civil and Environmental Engineering, College of Engineering Villanova University Pennsylvania USA

3. Engineering Faculty of Khoy Urmia University of Technology Urmia Iran

4. Electrical Engineering Department, College of Engineering Qatar University Qatar

5. Department of Chemical Engineering Shiraz Branch, Islamic Azad University Shiraz Iran

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.1155

Reference76 articles.

1. CO2 Capture in Chemically and Thermally Modified Activated Carbons Using Breakthrough Measurements: Experimental and Modeling Study

2. Designing a simple volumetric apparatus for measuring gas adsorption equilibria and kinetics of sorption. Application and validation for CO2, CH4 and N2 adsorption in binder-free beads of 4A zeolite

3. Comparison of two different flow types on CO removal along a two-stage hydrogen permselective membrane reactor for methanol synthesis

4. Compost from Municipal Solid Wastes as a Source of Biochar for CO 2 Capture

5. Hydrocarbon reservoirs characterization by co-interpretation of pressure and flow rate data of the multi-rate well testing

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