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Record W3155441572 · doi:10.1038/s42005-021-00576-6

Deconvolution of dissipative pathways for the interpretation of tapping-mode atomic force microscopy from phase-contrast

2021· article· en· W3155441572 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCommunications Physics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Calgary
FundersKorea Institute of Materials ScienceCanada Research ChairsUniversity of Calgary
KeywordsMetastabilityAmplitudeDissipative systemPhase (matter)ChemistryMolecular physicsChemical physicsMaterials scienceOpticsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract Phase-contrast in tapping-mode atomic force microscopy (TM-AFM) results from dynamic tip-surface interaction losses which allow soft and hard nanoscale features to be distinguished. So far, phase-contrast in TM-AFM has been interpreted using homogeneous Boltzmann-like loss distributions that ignore fluctuations. Here, we revisit the origin of phase-contrast in TM-AFM by considering the role of fluctuation-driven transitions and heterogeneous loss. At ultra-light tapping amplitudes <3 nm, a unique amplitude dependent two-stage distribution response is revealed, alluding to metastable viscous relaxations that originate from tapping-induced surface perturbations. The elastic and viscous coefficients are also quantitatively estimated from the resulting strain rate at the fixed tapping frequency. The transitional heterogeneous losses emerge as the dominant loss mechanism outweighing homogeneous losses at smaller amplitudes for a soft-material. Analogous fluctuation mediated phase-contrast is also apparent in contact resonance enhanced AFM-IR (infrared), showing promise in decoupling competing thermal loss mechanisms via radiative and non-radiative pathways. Understanding the loss pathways can provide insights on the bio-physical origins of heterogeneities in soft-bio-matter e.g., single cancer cell, tumors, and soft-tissues.

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.

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: none
Teacher disagreement score0.834
Threshold uncertainty score0.415

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 science0.0010.000
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 head0.026
GPT teacher head0.354
Teacher spread0.328 · 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