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Molecular Nanoparticles Are Unique Elements for Macromolecular Science: From “Nanoatoms” to Giant Molecules
Abstract
In this Perspective, we present a unique approach to the design and synthesis of giant molecules based on “nanoatoms” for engineering structures across multiple length scales and controlling their macroscopic properties. Herein, “nanoatoms” refer to shape-persistent molecular nanoparticles (MNPs) with precisely defined chemical structures and surface functionalities that can serve as elemental building blocks for the precision synthesis of giant molecules by methods such as sequential “click” approach. Typical “nanoatoms” include those MNPs based on fullerenes, polyhedral oligomeric silsesquioxanes, polyoxometalates, and folded globular proteins. The resulting giant molecules are precisely defined macromolecules. They include, but are not limited to, giant surfactants, giant shape amphiphiles, and giant polyhedra. Giant surfactants are polymer tail-tethered “nanoatoms” where the two components have drastic chemical differences to impart amphiphilicity. Giant shape amphiphiles not only are built up by covalently bonded MNPs of distinct shapes where the self-assembly is driven by chemical interactions but also are largely influenced by the packing constraints of each individual shape. Giant polyhedra are either made of a large MNP or by deliberately placing “nanoatoms” at the vertices of a polyhedron. In general, giant molecules capture the essential structural features of their small-molecule counterparts in many ways but possess much larger sizes. They are recognized in certain cases as size-amplified versions of those counterparts, and often, they bridge the gap between small molecules and traditional macromolecules. Highly diverse, thermodynamically stable and metastable hierarchal structures are commonly observed in the bulk, thin film, and solution states of these giant molecules. Controlled structural variations by precision synthesis further reveal a remarkable sensitivity of their self-assembled structures to the primary chemical structures. Unconventional nanostructures can be obtained in confined environments or through directed self-assembly. All the results demonstrate that MNPs are unique elements for macromolecular science, providing a versatile platform for engineering nanostructures that are not only scientifically intriguing but also technologically relevant.
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Metadata
- Authors
- Zhang, W.-B., Yu, X., Wang, C.-L., Sun, H.-J., Hsieh, I.-F., Li, Y., Dong, X.-H., Yue, K., Van Horn, R., & Cheng, S. Z. D.
- Venue
- Macromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-01-15
- Volume
- 47
- Issue
- 4
- Pages
- 1221-1239
- ISSN
- 0024-9297 (ISSN-L)
- 1520-5835
- OpenAlex
- W2036105438
- Cited by
- 354
- References
- 103
- FWCI
- 17.63
- 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 ›
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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.