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Record W6987551906

Thermoelastic damping in micromechanical and nanomechanical resonators

2015· dissertation· en· W6987551906 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldEngineering
TopicThermoelastic and Magnetoelastic Phenomena
Canadian institutionsMcGill University
Fundersnot available
KeywordsThermoelastic dampingDissipationThermal conductionViscoelasticityResonatorMagnetic dampingThermalDamping torque
DOInot available

Abstract

fetched live from OpenAlex

Thermoelastic damping (TED) is a fundamental mechanism of material damping in which energy is dissipated by the irreversible conduction of heat across thermoelastic temperature gradients within an oscillating structure. The first studies of TED were conducted over 85 years ago. Since that time, thermoelastic damping has been extensively studied, especially when it became clear in 1990 that TED can be a major mechanism of damping in microelectromechanical systems (MEMS). Nevertheless, as revealed by a careful survey of the literature, many aspects of TED remain to be investigated and understood. In this thesis, four such topics are addressed using a combination of analytical and numerical techniques.For monolithic beams, thermoelastic damping can be computed using a closed-form expression. Similar expressions were lacking for flexural-mode bilayer resonators, consisting of a substrate coated with a thin film, which are widely used in MEMS. To fill this gap in knowledge, a closed-form expression was developed for calculating TED in bilayers, and the formula was used to explore the nature and structure of the thermoelastic dissipation over several decades of frequency in a large set of materials and structures. This exploration showed that TED exhibits a rich variety of spectral features and provided useful information into the existence of multiple well-resolved dissipation peaks. Previously, numerical studies of TED in plates and membranes had concluded that TED can be decreased by subjecting the structures to in-plane tensile stresses. To gain a better understanding of the underlying mechanisms, simple closed-form analytical formulas were developed for the energy dissipated per cycle (ΔW) and TED for nanomembranes subjected to uniform biaxial, in-plane, tensile stresses. The results show that the effects of stress on dissipation are quite subtle: depending on the frequency, ΔW can increase, remain constant, or decrease when the structure is stressed in tension. The majority of the literature on TED is based on a linear analysis of damping. The sparse literature on nonlinear TED focuses on nonlinearities that have their origins in large deformations (that is, geometrical nonlinearities) or due to interactions with other energy domains (for example, electromechanical nonlinearities in electrostatically-actuated microresonators). In this thesis, a new type of dissipative nonlinearity (also called thermal nonlinearity) is studied. A finite-difference scheme was developed to solve the nonlinear governing equation and explore the effects of the dissipative nonlinearity on TED in stress-free silicon microcantilever beams and highly-stressed silicon nitride nanomembranes.Finally, the thesis considers an emerging topic in studies of TED, namely, computing dissipation using large-scale atomistic simulations. Classical molecular dynamics was used to simulate damping in the longitudinal-mode of single-crystal nickel resonators. Isothermal simulations were performed using the Nosé-Hoover thermostat to control the temperature. A protocol was devised for estimating the specific damping capacity and phase angle by identifying the factors that must be considered while selecting simulation parameters, and establishing criteria for convergence and linearity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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.

Study designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

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