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Record W1132783058

Electro-Thermal Mechanical Modeling of Microbolometer for Reliability Analysis

2010· dissertation· en· W1132783058 on OpenAlexfundno aff
Dawit Effa

Bibliographic record

VenueUWSpace (University of Waterloo) · 2010
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsnot available
FundersCanadian Space Agency
KeywordsMicrobolometerReliability (semiconductor)ThermalThermal analysisReliability engineeringEngineering physicsEngineeringMaterials scienceMechanical engineeringElectrical engineeringPhysicsBolometerThermodynamicsDetector
DOInot available

Abstract

fetched live from OpenAlex

Infrared (IR) imaging is a key technology in a variety of military and civilian applications, especially for night vision and remote sensing. Compared with cryogenically cooled IR sensors, uncooled infrared imaging devices have the advantages of being low cost, light weight, and superior reliability. The electro-thermal analysis of a microbolometer pixel is critical to determine both device performance and reliability. To date, most microbolometer analysis research has focused on performance optimization and computation of thermal conductance directly from the geometry. However, modeling of the thermal distribution across the microbolometer pixel is critical for the comprehensive analysis of system performance and reliability. Therefore, this thesis investigates the electro-thermo-mechanical characteristics of a microbolometer pixel considering the effects of joule heating and incoming IR energy. \n\t \nThe contributions of the present research include the electro-thermal models for microbolometer and methods of validating thermal distribution using experimental results. The electro-thermal models explain the effect of microbolometer material properties and geometry on device performance and reliability. The research also contributes methods of estimating the thermal conductivity of microbolometer, which take into account different heat transfer mechanisms, including radiation and convection. Previous approaches for estimating the thermal conductance of uncooled microbolometer consider heat conduction via legs from the geometry of the pixel structure and material properties [2]. This approach assumes linear temperature distribution in the pixel legs structure. It also leaves out the various electro-thermal effects existing for multilayer structures. In the present research, a different approach is used to develop the thermal conductance of microbolometer pixel structure. The temperature distribution in the pixel is computed from an electro-thermal model. Then, the average temperature in the pixel microplate and the total heat energy generated by joule heating is utilized to compute the thermal conductance of the structure. \n \nThe thesis discusses electro-thermal and thermo-mechanical modeling, simulation and testing of Polysilicon Multi-User MEMS Process (PolyMUMPs®) test devices as the groundwork for the investigation of microbolometer performance and reliability in space applications. An electro-thermal analytical and numerical model was developed to predict the temperature distribution across the microbolometer pixel by solving the second order differential heat equation. To provide a qualitative insight of the effect of different parameters in the thermal distribution, including material properties and device geometry, first an explicit formulation for the solution of the electro-thermal coupling is obtained using the analytical method. In addition, the electro-thermal model, which accounts for the effect of IR energy and radiation heat transfer, spreading resistance and transient conditions, was studied using numerical methods. \n \nIn addition, an analytical model has been developed to compute the IR absorption coefficient of a Thin Single Stage (TSS) microbolometer pixel. The simulation result of this model was used to compute absorbed IR energy for the numerical model. Subsequently, the temperature distribution calculated from the analytical model is used to obtain the deflections that the structure undergoes, which will be fundamental for the reliability analysis of the device. Finite element analysis (FEA) has been simulated for the selected device using commercial software, ANSYS® multiphysics. Finite element simulation shows that the electro-thermal models predict the temperature distribution across a microbolometer pixel at steady-state conditions within 2.3% difference from the analytical model. The analytical and numerical models are also simulated and results for a temperature distribution within 1.6% difference. In addition, to validate the analytical and numerical electro-thermal and thermo-mechanical models, a PolyMUMPs® test device has been used. The test results showed a close agreement with the FEM simulation deflection of the test device.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2010
Admission routes1
Has abstractyes

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