The DOI matches its Crossref record.
Field-Flow Fractionation: Analysis of Macromolecular, Colloidal, and Particulate Materials
Abstract
Field-flow fractionation (FFF) is a family of flexible elution techniques capable of simultaneous separation and measurement. Its sample domain extends across a broad macromolecular-colloidal-particulate continuum from about 1 nanometer to more than 100 micrometers and incorporates both simple and complex macromaterials of biological, biomedical, industrial, and environmental relevance. Complex materials are separated into components to simplify measurement. Component properties measurable by FFF include mass, size, density, charge, diffusivity, and thickness of adsorbed layers. When characterization by these properties is inadequate, other measurement tools can be readily coupled to FFF, either off-line or on-line, by virtue of its flow-elution operation. This article describes the principles and major subtechniques of the FFF family along with application of its measurement and separative capabilities.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Chip integrated strategies for acoustic separation and manipulation of cells and particles
Laurell, T., Petersson, F., & Nilsson, A. (2007) · Chem. Soc. Rev. · doi:10.1039/b601326k · Cited by 874
Yamada, M., Nakashima, M., & Seki, M. (2004) · Analytical Chemistry · doi:10.1021/ac049863r · Cited by 746
Methods for the analysis of submicrometer- and nanoplastic particles in the environment
Schwaferts, C., Niessner, R., Elsner, M., & Ivleva, N. P. (2019) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2018.12.014 · Cited by 522
Inertial microfluidics for continuous particle filtration and extraction
Bhagat, A. A. S., Kuntaegowdanahalli, S. S., & Papautsky, I. (2009) · Microfluidics and Nanofluidics · doi:10.1007/s10404-008-0377-2 · Cited by 334
Chen, Y., Guo, Z., Wang, X., & Qiu, C. (2008) · Journal of Chromatography A · doi:10.1016/j.chroma.2007.10.026 · Cited by 316
Metadata
- Authors
- Giddings, J. C.
- Venue
- Science
- Published
- 1993-06-04
- Volume
- 260
- Issue
- 5113
- Pages
- 1456-1465
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2103633180
- Cited by
- 1,141
- References
- 0
- FWCI
- 25.12
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Field-Flow Fractionation: Analysis of Macromolecular, Colloidal, and Particulate Materials. https://app.cochat.ai/papers/10.1126/science.8502990
- The paper
- Giddings, J. C. (1993). Field-Flow Fractionation: Analysis of Macromolecular, Colloidal, and Particulate Materials. Science. https://doi.org/10.1126/science.8502990
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
