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Record W2169384858 · doi:10.2514/6.2001-4982

A comparison of microfabrication and WakeShield's processing requirements

2001· article· en· W2169384858 on OpenAlexaff
Glenn H. Chapman, Nick Pfeiffer

Bibliographic record

Venue2001 Conference and Exhibit on International Space Station Utilization · 2001
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMicrofabricationComputer science

Abstract

fetched live from OpenAlex

Using orbital vacuum for enhanced semiconductor fabrication was pioneered in the Wake Shield project which produced ultra-high vacuums for epitaxial growth of high quality GaAs like materials. A proposed alternative uses the native Low Earth Orbit vacuum levels to achieve the silicon microfabrication processes needed for manufacturing silicon microchips. Space microfabrication combines many processes that are easier to achieve in LEO, potentially producing a flexible range of Microchips (high value per mass products). However standard terrestrial fabrication techniques are difficult to transfer into the microgravity and vacuum environment of space. They are optimized for using in-situ resources: water, power, air pressure and gravity that are plentiful on Earth. An alternative microfabrication process has been developed using the native vacuum environment which could replace wet terrestrial based microfabrication, with significant savings in equipment size, mass and consumables, while reducing cycle time. Computer models have been developed which compare the standard Earth-based process consumables, power and fabrication time with space-oriented processes resulting in a process flow that is optimized for orbital facilities. ISS based microfabrication testing is possible before developing an integrated orbital microchip facility: FabSat .- a synergistic orbital-based system for microfabrication capable of building and delivering commercially marketable microfabricated structures and devices.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.435

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)0.0000.000

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 head0.086
GPT teacher head0.344
Teacher spread0.258 · 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 designSimulation or modeling
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
Published2001
Admission routes1
Has abstractyes

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