Strojno učenje potencijala za CsPbBr_xI_(3-x)

Šopar, Šimun

prikaz prve stranice dokumenta Strojno učenje potencijala za CsPbBr_xI_(3-x)

Download
PDF 3.22 MB

master's thesis

44 38

Strojno učenje potencijala za CsPbBr_xI_(3-x)

Zagreb: University of Zagreb, Faculty of Science, 2023. urn:nbn:hr:217:172931

Šopar, Šimun

University of Zagreb
Faculty of Science
Department of Physics

Institutional repository: Repository of the Faculty of Science

Cite this document

APA 6th Edition

Šopar, Š. (2023). Strojno učenje potencijala za CsPbBr_xI_(3-x) (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:172931

MLA 8th Edition

Šopar, Šimun. "Strojno učenje potencijala za CsPbBr_xI_(3-x)." Master's thesis, University of Zagreb, Faculty of Science, 2023. https://urn.nsk.hr/urn:nbn:hr:217:172931

Chicago 17th Edition

Šopar, Šimun. "Strojno učenje potencijala za CsPbBr_xI_(3-x)." Master's thesis, University of Zagreb, Faculty of Science, 2023. https://urn.nsk.hr/urn:nbn:hr:217:172931

Harvard

Šopar, Š. (2023). 'Strojno učenje potencijala za CsPbBr_xI_(3-x)', Master's thesis, University of Zagreb, Faculty of Science, accessed 03 April 2025, https://urn.nsk.hr/urn:nbn:hr:217:172931

Vancouver

Šopar Š. Strojno učenje potencijala za CsPbBr_xI_(3-x) [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2023 [cited 2025 April 03] Available at: https://urn.nsk.hr/urn:nbn:hr:217:172931

IEEE

Š. Šopar, "Strojno učenje potencijala za CsPbBr_xI_(3-x)", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:217:172931

Cite this item: https://urn.nsk.hr/urn:nbn:hr:217:172931

Metadata

Title	Strojno učenje potencijala za CsPbBr_xI_(3-x)
Title (english)	Machine learning of potential for CsPbBr_xI_(3-x)
Author	Šimun Šopar
Mentor	Ivor Lončarić (mentor)
Mentor	Nikola Poljak (komentor)
Committee member	Nikola Poljak (predsjednik povjerenstva)
Committee member	Ivor Lončarić (član povjerenstva)
Committee member	Danko Radić (član povjerenstva)
Committee member	Damir Pajić (član povjerenstva)
Committee member	Denis Sunko (član povjerenstva)
Granter	University of Zagreb Faculty of Science (Department of Physics) Zagreb
Defense date and country	2023-07-13, Croatia
Scientific / art field, discipline and subdiscipline	NATURAL SCIENCES Physics
Abstract	U ovom radu proučavana je uporaba modela dubokog učenja za konstrukciju međuatomskog potencijala CsPb(BrxI1−x)3 kako bi se izbjegla uporaba numerički zahtjevnih kvantnomehaničkih izračuna. U tu svrhu korišten je model Allegro specijaliziran za rad s kristalima. Allegro je neuronska mreža zasnovana na mehanizmu slanja poruka koja čuva simetrije kristala. U sklopu rada detaljno je opisan rad Allegro modela. Ispitano je prijenosno učenje kao način učenja modela korištenjem manjeg broja... More
Keywords
Language	croatian
URN:NBN	urn:nbn:hr:217:172931
Project	Number: UIP-2020-02-5675 Title: Povećanje prostorne i vremenske skale modeliranja materijala iz prvih principa pomoću strojnog učenja Title: Extending length and time scales of first principles material modelling via machine learning Acronym: ExtMatModelML Leader: Ivor Lončarić Jurisdiction: Croatia Funder: HRZZ Funding stream: UIP
Study programme	Title: The University Integrated Undergraduate and Graduate Programme in Physics; Research Physics; specializations in: Research Physics Course: Research Physics Study programme type: university Study level: integrated undergraduate and graduate Academic / professional title: sveučilišni magistar fizike (sveučilišni magistar fizike)
Type of resource	Text
File origin	Born digital
Access conditions	Open access Embargo expiration date: 2024-07-13
Terms of use
Created on	2024-02-15 14:39:22

Search form

closeAccessibilityrefresh

Accessibility