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Evaporation Resistance of Grooved Wicks Fabricated Using Laser Powder Bed Fusion

2024· article· en· W4403918440 on OpenAlexaff
Mohamed Hasan, Jason Durfee, Roger Kempers

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsMagna International (Canada)York University
Fundersnot available
KeywordsMaterials scienceFusionEvaporationLaserComposite materialOptics

Abstract

fetched live from OpenAlex

As electronic devices become more powerful and compact, they generate higher heat fluxes, which can lead to reduced performance and failure if not properly managed. Two-phase cooling systems, such as heat pipes and vapour chambers, are highly effective at dissipating heat from electronic components, using the latent heat of vaporization to transfer large amounts of heat with minimal temperature difference. The design of the wick structure used inside two-phase heat transport technologies is important for thermal and hydraulic performance: The wick sustains the working fluid circulation and is a dominant contributor to the thermal resistance at the evaporator and condenser regions. Recently, additive manufacturing (AM) technologies, such as laser powder bed fusion (LPBF), have been leveraged to develop improved heat pipe technologies in terms of overall device form factor and to fabricate integrated AM wick structures. In the current study, four grooved wicks were developed using the LPBF process by modifying the laser hatch spacing of the process, resulting in wicks with two different groove heights (0.6 and 0.8 mm) and two different groove widths (200 and 300 µm). These hatched grooved wicks were fabricated by changing the laser hatch spacing between 0.42 and 0.52 mm, with zero angle rotation between layers. Alsi10Mg powder material was used to fabricate the wicks. The evaporator wick thermal resistance was measured in a thermal-hydraulic testing apparatus under saturated vapor conditions and capillary-fed liquid flow through the tested wicks. Results showed a minimum thermal resistance of 0.115 K/w for the hatched wick with a groove height of 0.8 mm and a groove width of 300 µm. In addition, the same hatched wick achieved the highest heat input flux of 43.5 W/cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>.

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)0.000
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 score0.027
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.231
Teacher spread0.215 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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