Liquid organic hydrogen carrier hydrogenation–dehydrogenation : from ab initio catalysis to reaction micro-kinetics modelling

Rakić, Emilija (avtor), Grilc, Miha (avtor), Likozar, Blaž (avtor)

The continued selective focus on the exploitation of fossil fuel chemicals as one of the main environment-depleting sources of energy is one of the reasons for the carbon dioxide emissions, severe air pollution and market crisis of today. The related easy transition to efficient renewable resources also brings challenges, such as the storing of performance generated year round. Consistent application option is to convert the formed transferred electricity produced into the hydrogen through electrolysis, store gaseous H$_2$, and reversibly proceed with reforming or cracking. This routine way is also referred to in literature as evolving green H$_2$. A relatively new method of storage is liquid organic carriers (LOHCs). These are molecules that are in a (l) state at room temperature measurements, contain unsaturated covalent bonds, and can be hydrogenated/dehydrogenated in the many loading cycles without catalytic decomposition products. Paper presents possible structure systems that have been previously investigated as an alternative to conventional. The process of catalysis, reduction and coking, catalysts, and the most commonly used elementary groups, interactions, and reaction condition analyses are listed, while an overview of studies that have assessed technical transfer phenomena is also provided. Reports, dealing with derived micro-kinetic modelling/computational fluid dynamics (CFD), which is a direction for further research activities, are few. As for multiscale, review ranges from the density functional theory (DFT) to CFD. The review paper also addresses the latest studies on LOHCs in the field of artificial intelligence (AI), machine learning (ML), and artificial neural networks (ANN). The progress within the area with approaches is highlighted. Mesoscale surface–selectivity relationships, the robustness towards deactivation and techno-economics are dominant in linking the digital twin design to operation.

• Jezik: Angleški jezik
• Ključne besede: liquid organic hydrogen carrier molecules, LOHC, multiscale modelling chemical reaction kinetics, density functional theory, DFT, computational fluid dynamics, CFD, machine learning, ML, catalysis, H$_2$ storage
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.02 - Pregledni znanstveni članek
• Organizacija: FKKT - Fakulteta za kemijo in kemijsko tehnologijo
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2023
• Št. strani: 23 str.
• Številčenje: Vol. 472, art. 144836
• PID: 20.500.12556/RUL-152906
• UDK: 544.3/.4
• ISSN pri članku: 1873-3212
• DOI: 10.1016/j.cej.2023.144836
• COBISS.SI-ID: 165967619
• Datum objave v RUL: 11.12.2023

Gradivo je del revije

• Naslov: Chemical engineering journal
• Založnik: Elsevier
• ISSN: 1873-3212
• COBISS.SI-ID: 23123973

Licence

• Licenca: CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
• Opis: Najbolj omejujoča licenca Creative Commons. Uporabniki lahko prenesejo in delijo delo v nekomercialne namene in ga ne smejo uporabiti za nobene druge namene.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: kataliza, katalizatorji, fosilna goriva, dinamika fluidov, CFD

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P2-0152
• Naslov: Kemijsko reakcijsko inženirstvo

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: J2-2492
• Naslov: Razvoj procesov valorizacije lignina kot vira aromatskih gradnikov za proizvodnjo bioosnovanih polimerov