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Record W2803041593 · doi:10.1149/ma2018-01/42/2465

Pressure Sensor at Barometric Levels Using Ionized Gas

2018· article· en· W2803041593 on OpenAlexaff
Matthew C. Stewart, Xuehan Liu, John D. Jones, Albert M. Leung

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAtmospheric pressureIonizationVolume (thermodynamics)Current (fluid)LinearityIonIon currentPressure measurementPressure sensorMaterials scienceAtomic physicsAnalytical Chemistry (journal)ChemistryElectrical engineeringPhysicsMechanical engineeringEngineeringMeteorology

Abstract

fetched live from OpenAlex

This paper shows experimental evidence of the feasibility of using ionized gas pressure sensors at barometric pressures. Through building an experimental setup with millimeter scale gap length which represents the critical dimension of in defining the geometry of the sensing element, our research has verified function and linearity at relevant pressure. The electrical current in the sensing element itself is on the order of tens of pA. In combination with low power amplification circuitry, a device built based on the results of this experiment would be suitable for use in ultra-low power applications. An ion-based pressure sensor uses a small alpha particle source, in our case Americium-241, to ionize a volume of gas. A gas at a higher pressure, i.e. higher molecule density, will be subject to more ionization interactions with alpha particles and produce a higher ion density. These ions can then be collected through the application of an electric field across the volume and measurement of electrical current collected at electrodes. Under certain conditions, the resulting current is linearly proportional to the gas pressure. An experiment using some of these concepts was first conducted in 1946 [1]. Later, in 1996, a, experiment using a 20 mm gap length was built to explore this concept as a vacuum sensor for the harsh environment of Mars, establishing suitability at low pressures with experimental data focusing on pressures from 0-2 kPa [2]. A more thorough theoretical examination was conducted at that time. These sensors are theorized to be mechanically resilient and to minimize susceptibility to sensor drift due to material fatigue over time. Using the setup shown in Figure 1, we conducted an experiment using a much smaller gap length. Our sensor has been constructed with a variable size and has been tested to gap lengths as short as 4 mm, representing a significant reduction. By examining the sensor dependence on the parameters of voltage and gap length, we are able to extrapolate to smaller structures and can verify that our design is scalable down to sub-millimeter structures. We tested and collected data verifying function and linearity. Figure 2 shows experimental data over a pressure range from low vacuum to atmospheric pressure for gap lengths of 4 mm and 10 mm. This plot shows that both are linear and approach a zero reading at vacuum, making them suitable as absolute pressure sensors. Our study focused on an application as a small resilient barometer, so we collected the data shown in Figure 3 in the range of ambient atmospheric pressure ± 10 kPa with gap length of 4 mm. The linearity was verified to within the limits of our reference sensor. References [1] J. R. Downing and G. Mellen, “A sensitive vacuum gauge with linear response,” The Review of Scientific Instruments, vol. 17, no. 6, pp. 218-223, Jun. 1946. [2] M. G. Buehler, L. D. Bell, and M. H. Hecht, “Alpha-particle gas-pressure sensor,” Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, vol. 14, pp. 1281-1287, May/Jun. 1996. Figure 1

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.237
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2018
Admission routes1
Has abstractyes

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