Millisecond X-ray reflectometry and neural network analysis:
unveiling fast processes in spin coating

J 2024

Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating

SCHUMI-MAREČEK, David; Florian BERTRAM; Petr MIKULÍK; Devanshu VARSHNEY; Jiří NOVÁK et. al.

Základní údaje

Originální název

Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating

Autoři

SCHUMI-MAREČEK, David; Florian BERTRAM; Petr MIKULÍK (203 Česká republika, domácí); Devanshu VARSHNEY (356 Indie, domácí); Jiří NOVÁK (203 Česká republika, domácí) a Stefan KOWARIK (garant)

Vydání

Journal of Applied Crystallography, International Union of Crystallography, 2024, 1600-5767

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10302 Condensed matter physics

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 5.200 v roce 2023

Kód RIV

RIV/00216224:14310/24:00135826

Organizační jednotka

Přírodovědecká fakulta

DOI

http://dx.doi.org/10.1107/S1600576724001171

UT WoS

001208800100011

EID Scopus

2-s2.0-85189944139

Klíčová slova anglicky

millisecond XRR; neural network analysis; spin coating; X-ray reflectometry; X-ray reflectometry

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 11. 10. 2024 13:59, Mgr. Marie Novosadová Šípková, DiS.

Anotace

V originále

X-ray reflectometry (XRR) is a powerful tool for probing the structural characteristics of nanoscale films and layered structures, which is an important field of nanotechnology and is often used in semiconductor and optics manufacturing. This study introduces a novel approach for conducting quantitative high-resolution millisecond monochromatic XRR measurements. This is an order of magnitude faster than in previously published work. Quick XRR (qXRR) enables real time and in situ monitoring of nanoscale processes such as thin film formation during spin coating. A record qXRR acquisition time of 1.4 ms is demonstrated for a static gold thin film on a silicon sample. As a second example of this novel approach, dynamic in situ measurements are performed during PMMA spin coating onto silicon wafers and fast fitting of XRR curves using machine learning is demonstrated. This investigation primarily focuses on the evolution of film structure and surface morphology, resolving for the first time with qXRR the initial film thinning via mass transport and also shedding light on later thinning via solvent evaporation. This innovative millisecond qXRR technique is of significance for in situ studies of thin film deposition. It addresses the challenge of following intrinsically fast processes, such as thin film growth of high deposition rate or spin coating. Beyond thin film growth processes, millisecond XRR has implications for resolving fast structural changes such as photostriction or diffusion processes.

Návaznosti

EH22_008/0004572, projekt VaV

Název: Kvantové materiály pro aplikace v udržitelných technologiích

GA22-04551S, projekt VaV

Název: Růst organických polovodičů na grafenu: od vzniku první monovrstvy k molekulárním multivrstvám (Akronym: GOSG)

Investor: Grantová agentura ČR, Growth of organic semiconductors on graphene: from the first monolayer formation to molecular multilayers

Citovat

SCHUMI-MAREČEK, David; Florian BERTRAM; Petr MIKULÍK; Devanshu VARSHNEY; Jiří NOVÁK a Stefan KOWARIK. Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating. Journal of Applied Crystallography. International Union of Crystallography, 2024, roč. 57, č. 2, s. 314-323. ISSN 1600-5767. Dostupné z: https://dx.doi.org/10.1107/S1600576724001171.

@article{2394837,
   author = {SchumiandMareček, David and Bertram, Florian and Mikulík, Petr and Varshney, Devanshu and Novák, Jiří and Kowarik, Stefan},
   article_number = {2},
   doi = {http://dx.doi.org/10.1107/S1600576724001171},
   keywords = {millisecond XRR; neural network analysis; spin coating; X-ray reflectometry; X-ray reflectometry},
   language = {eng},
   issn = {1600-5767},
   journal = {Journal of Applied Crystallography},
   title = {Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating},
   url = {https://journals.iucr.org/j/issues/2024/02/00/jo5099/index.html},
   volume = {57},
   year = {2024}
}

TY  - JOUR
ID  - 2394837
AU  - Schumi-Mareček, David - Bertram, Florian - Mikulík, Petr - Varshney, Devanshu - Novák, Jiří - Kowarik, Stefan
PY  - 2024
TI  - Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating
JF  - Journal of Applied Crystallography
VL  - 57
IS  - 2
SP  - 314-323
EP  - 314-323
PB  - International Union of Crystallography
SN  - 16005767
KW  - millisecond XRR
KW  - neural network analysis
KW  - spin coating
KW  - X-ray reflectometry
KW  - X-ray reflectometry
UR  - https://journals.iucr.org/j/issues/2024/02/00/jo5099/index.html
N2  - X-ray reflectometry (XRR) is a powerful tool for probing the structural characteristics of nanoscale films and layered structures, which is an important field of nanotechnology and is often used in semiconductor and optics manufacturing. This study introduces a novel approach for conducting quantitative high-resolution millisecond monochromatic XRR measurements. This is an order of magnitude faster than in previously published work. Quick XRR (qXRR) enables real time and in situ monitoring of nanoscale processes such as thin film formation during spin coating. A record qXRR acquisition time of 1.4 ms is demonstrated for a static gold thin film on a silicon sample. As a second example of this novel approach, dynamic in situ measurements are performed during PMMA spin coating onto silicon wafers and fast fitting of XRR curves using machine learning is demonstrated. This investigation primarily focuses on the evolution of film structure and surface morphology, resolving for the first time with qXRR the initial film thinning via mass transport and also shedding light on later thinning via solvent evaporation. This innovative millisecond qXRR technique is of significance for in situ studies of thin film deposition. It addresses the challenge of following intrinsically fast processes, such as thin film growth of high deposition rate or spin coating. Beyond thin film growth processes, millisecond XRR has implications for resolving fast structural changes such as photostriction or diffusion processes.
ER  -

SCHUMI-MAREČEK, David; Florian BERTRAM; Petr MIKULÍK; Devanshu VARSHNEY; Jiří NOVÁK a Stefan KOWARIK. Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating. \textit{Journal of Applied Crystallography}. International Union of Crystallography, 2024, roč.~57, č.~2, s.~314-323. ISSN~1600-5767. Dostupné z: https://dx.doi.org/10.1107/S1600576724001171.

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