The DOI matches its Crossref record.
Modeling Organic Surfaces with Self‐Assembled Monolayers
Abstract
The interfacial properties of organic materials are of critical importance in many applications, especially the control of wettability, adhesion, tribology, and corrosion. The relationships between the microscopic structure of an organic surface and its macroscopic physical properties are, however, only poorly understood. This short review presents a model system that has the ease of preparation and the structural definition required to provide a firm understanding of interfacial phenomena. Long‐chain thiols, HS(CH 2)n X, adsorb from solution onto gold and form densely packed, oriented monolayers. By varying the terminal functional group, X, of the thiol, organic surfaces can be created having a wide range of structures and properties. More complex systems can be constructed by coadsorbing two or more thiols with different terminal functional groups or with different chain lengths onto a common gold substrate. By these techniques, controlled degrees of disorder can be introduced into model surfaces. We have used these systems to explore the relationships between the microscopic structure of the monolayers on a molecular and supramolecutar scale and their macroscopic properties. Wettability is a macroscopic interfacial property that has proven of particular interest.
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
Biomaterials in Tissue Engineering
Hubbell, J. A. (1995) · Nature Biotechnology · doi:10.1038/nbt0695-565 · Cited by 1,060
Molecular Imprinting Techniques Used for the Preparation of Biosensors
Ertürk, G., & Mattiasson, B. (2017) · Sensors · doi:10.3390/s17020288 · Cited by 292
Metadata
- Authors
- Bain, C. D., & Whitesides, G. M.
- Venue
- Angewandte Chemie International Edition in English
- Publisher
- Wiley
- Published
- 1989-04
- Volume
- 28
- Issue
- 4
- Pages
- 506-512
- ISSN
- 0570-0833 (ISSN-L)
- OpenAlex
- W2103098331
- Cited by
- 433
- References
- 0
- FWCI
- 13.66
- 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: Modeling Organic Surfaces with Self‐Assembled Monolayers. https://app.cochat.ai/papers/10.1002/anie.198905061
- The paper
- Bain, C. D., & Whitesides, G. M. (1989). Modeling Organic Surfaces with Self‐Assembled Monolayers. Angewandte Chemie International Edition in English. https://doi.org/10.1002/anie.198905061
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.