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Record W4403684568 · doi:10.1039/d4cp03597f

Modeling the ionization mechanism of amorphous solid particles without an external energy source coupled to mass spectrometry

2024· article· en· W4403684568 on OpenAlexfundno aff
Styliani Consta, Lisa M. Wingen, Yiming Qin, Véronique Perraud, Barbara J. Finlayson‐Pitts

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2024
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsnot available
FundersUniversity of California, IrvineAlliance de recherche numérique du CanadaFulbright CanadaNational Science Foundation
KeywordsMass spectrometryIonizationThermal ionization mass spectrometryChemistryChromatographyIon

Abstract

fetched live from OpenAlex

desorption of charged analytes from the surface of solid amorphous glutaric acid particles, without the assistance of an external energy source, has been shown to be a promising method that can be coupled to mass spectrometry. We conduct mechanistic studies of the later stages of this ionization process using atomistic molecular dynamics. Our analysis focuses on the hydrogen bonding, diffusion, and ion desorption from nano-aggregates of glutaric acid. These nano-aggregates exhibit an extended H-bonded network, often comprising H-bonded chains, linear dimeric assemblies, and occasionally cyclic trimeric assemblies. These local structures serve as centers for proton transfer reactions. The intermediate hydrocarbon chain between the proton-carrying oxygen sites prevents proton diffusion over a long distance unless there is significant translational or rotational movement of the proton-carrying diacid molecule. Our calculations show that diffusion on the surface is an order of magnitude faster than in the core of the nano-aggregate, which aids effective proton transfer on the particle's exterior. We find that ionic species desorb from the aggregate's surface through independent evaporation events of small clusters, where the ion is coordinated by only a few glutaric acid molecules. Near the nano-aggregate's Rayleigh limit, jets capable of releasing multiple ions were not observed. These observations suggest a more general ion-evaporation mechanism that applies to low-dielectric particles of various sizes, complementing the original ion-evaporation mechanism proposed for aqueous droplets with an approximate radius of 10-15 nm. The combined evidence from molecular modeling presented here and the thermodynamic properties of solid and supercooled liquid glutaric acid indicates that the stronger signals of glutaric acid observed in the mass spectra, relative to other experimentally tested diacids, can be attributed to its significantly lower melting point and the reduced enthalpy of vaporization of its amorphous state compared to other tested diacids.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.262
Teacher spread0.249 · 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
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

Citations2
Published2024
Admission routes1
Has abstractyes

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