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Record W1988806779 · doi:10.1073/pnas.120129097

Size exclusion chromatography does not require pores

2000· article· en· W1988806779 on OpenAlexaff
Donald E. Brooks, Charles A. Haynes, Doina Hritcu, Bradley M. Steels, Werner Müller

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2000
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMacromoleculeSize-exclusion chromatographyPolymerPolystyrenePartition coefficientChemistryPartition (number theory)Excluded volumePhase (matter)Mixing (physics)Gel permeation chromatographyThermodynamicsBeadPorosityChemical physicsChromatographyMaterials scienceOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Separation of macromolecules on the basis of their molecular weight by size exclusion chromatography has long been considered to be caused by the geometry-dependent partition of macromolecules between a continuous phase and the porous interior of a gel or cross-linked bead. The volume of a pore accessible to a solute is limited by its relative dimensions, so larger molecules will have access to a smaller volume and will remain in a bead for a shorter time than smaller solutes. Our recent alternate picture proposes that the partition coefficient can be calculated from a thermodynamic model for the free energy of mixing of the solute with the gel phase. Size-dependent exclusion caused by the unfavorable entropy of mixing associated with the partition is predicted; the magnitude of the effect is modified by enthalpic interactions between the solute and the gel phase. This concept is extended here to describe the partition of macromolecules into a layer of terminally attached polymer chains grafted onto a solid bead. Both simple mean field and self-consistent field theory calculations predict size-dependent entropic exclusion. Experimental results obtained with neutral polymer chains grafted onto solid polystyrene latex beads confirm the predictions.

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)0.000
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: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.243
Teacher spread0.230 · 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.

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

Citations38
Published2000
Admission routes1
Has abstractyes

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