MétaCan
Menu
Back to cohort
Record W2784147589 · doi:10.1116/1.5005115

Numerical and experimental thermal analysis of polyimide-based x-ray masks at the Canadian Light Source

2018· article· en· W2784147589 on OpenAlexaffabout
Sven Achenbach, Chen Shen, Garth Wells

Bibliographic record

VenueJournal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Photolithography Techniques
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersSandia National Laboratories
KeywordsMaterials scienceFabricationThermocoupleLIGAThermal conductivityWaferHeat transferPolyimidePhotoresistOpticsLithographyBeamlineX-ray lithographyOptoelectronicsComposite materialBeam (structure)ResistPhysics

Abstract

fetched live from OpenAlex

In deep x-ray lithography (DXRL), synchrotron radiation is applied to transfer absorber patterns on an x-ray mask into thick photoresist to generate high quality microstructures. Fabrication of the required x-ray masks is a demanding process sequence and constitutes a bottleneck in DXRL technology. Polymer-based mask membranes offer many benefits during mask fabrication and operation, but usually suffer from large thermal distortions during x-ray exposure. These are due to the low thermal conductivity of most polymers (approximately 0.2 W/m K), which results in inefficient heat transfer to the cooled areas around mask and substrate. The power tuning capabilities at the Synchrotron Laboratory for Micro and Nano Devices beamline, Canadian Light Source, however, allow the beam power to be adjusted and consequently limit thermal distortions. In this study, x-ray masks based on 30 μm thick polyimide membranes are studied. Numerical simulations of the thermal and thermoelastic behavior were performed using the software package ansys r14.5. The beam power input parameters were calculated with the software lex-d. For experimental verification, a process to fabricate simple test masks was developed. The polymer membranes were processed on stainless steel sacrificial wafers and were patterned with 80 μm thick nickel absorbers in two macroscopic layouts. Five chromel/alumel (K-type) thermocouples where then bonded to the absorbers to measure the heat distribution. The measurements generally validated the numerical results. The simulated thermal distributions consistently overestimate the experimental values by approximately 4–6 K, which is mainly attributed to uncertainties in the experimental proximity gap settings. The thermal simulation results indicate that the dominant heating mechanism of the resist is conduction: Energy absorbed in the mask absorbers is conducted through the helium gas in the proximity gap to the nonexposed poly(methyl methacrylate) (PMMA) areas and the substrate (cooled to 18 °C). For 500 μm thick PMMA resist, exposed with a synchrotron beam power of 19.6 W, maximum temperatures in the mask are 31.0 and 25.8 °C in the resist below. Maximum single-axis resist deformations in the mask plane amount to 4.12 μm. At 250 μm resist thickness, the observed temperatures are only 25.4 °C in the mask and 22.3 °C in the resist, with maximum mask plane deformations of about 2.3 μm. Integrated over the entire absorber size of 60 mm, these deformations roughly double. Local structure accuracy results were obtained by measuring distortions in a micropatterned polyimide mask. Deformations verify simulation results, vary with the position on the layout, and scale with the incident beam power. At 3.3 W incident beam power, typical deformations around 1–1.5 μm and maximum deformations of 2.3 μm were measured in 100 μm thick resist.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.228
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and PhenomenaSame topicAdvancements in Photolithography TechniquesFrench-language works237,207