Deep reinforcement learning for microstructural optimisation of silica aerogels

Pandit, Prakul and Abdusalamov, Rasul and Itskov, Mikhail and Rege, Ameya Govind (2024) Deep reinforcement learning for microstructural optimisation of silica aerogels. Scientific Reports. Nature Publishing Group. doi: 10.1038/s41598-024-51341-y. ISSN 2045-2322.

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Official URL: https://www.nature.com/articles/s41598-024-51341-y

Abstract

https://www.nature.com/articles/s41598-024-51341-y

Item URL in elib:

https://elib.dlr.de/206950/

Document Type:

Article

Title:

Deep reinforcement learning for microstructural optimisation of silica aerogels

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Pandit, Prakul	Prakul.Pandit (at) dlr.de	https://orcid.org/0000-0002-1343-3046	151555193
Abdusalamov, Rasul	RWTH Aachen University	UNSPECIFIED	UNSPECIFIED
Itskov, Mikhail	itskov (at) km.rwth-aachen.de	UNSPECIFIED	UNSPECIFIED
Rege, Ameya Govind	Ameya.Rege (at) dlr.de	https://orcid.org/0000-0001-9564-5482	UNSPECIFIED

Date:

17 January 2024

Journal or Publication Title:

Scientific Reports

Refereed publication:

Yes

Open Access:

Yes

Gold Open Access:

Yes

In SCOPUS:

Yes

In ISI Web of Science:

Yes

DOI:

10.1038/s41598-024-51341-y

Publisher:

Nature Publishing Group

ISSN:

2045-2322

Status:

Published

Keywords:

aerogels, AI in materials, material informatics

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Transport

HGF - Program Themes:

Road Transport

DLR - Research area:

Transport

DLR - Program:

V ST Straßenverkehr

DLR - Research theme (Project):

V - ReBar - Reducing Barriers for AI in (applied) Research

Location:

Köln-Porz

Institutes and Institutions:

Institute of Materials Research > Aerogels and Aerogel Composites

Deposited By:

Pandit, Prakul

Deposited On:

01 Oct 2024 10:51

Last Modified:

01 Oct 2024 10:51

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