Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 305

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Supramolecular Hydrogel Exhibiting Four Basic Logic Gate Functions To Fine-Tune Substance Release

Komatsu, Harunobu, Matsumoto, Shinji, Tamaru, Shun-ichi, Kaneko, Kenji, Ikeda, Masato, Hamachi, Itaru·2009·Journal of the American Chemical Society

Abstract

Logic-gate operations displaying macroscopic outputs are promising systems for the development of intelligent soft materials that can perform effective functions in response to various input patterns. A supramolecular hydrogel comprising the phosphate-type hydrogelator 1 exhibits macroscopic gel-sol behavior in response to four distinct input stimuli: temperature, pH, Ca(2+), and light. We characterized this performance through microscopic, spectroscopic, and rheological measurements. On the basis of its multiple-stimulus responsiveness, we constructed gel-based supramolecular logic gates from hydrogelator 1 that demonstrated AND, OR, NAND, and NOR types of stimulus-responsive gel-sol behavior in the presence of various combinations of the four stimuli. Implementation of such logic-gate functions into semiwet soft materials (e.g., supramolecular hydrogels) is an important step toward the design of controlled drug delivery and release systems. Indeed, we demonstrate herein that one of our gel-based supramolecular logic gates is capable of holding and releasing bioactive substances in response to logic triggers. Furthermore, combining our supramolecular gel-based AND logic gate with a photoresponsive supramolecular gel could temporarily modulate the release rate of the bioactive substance.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ja8098239

Cites

39 of 39 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cites

Show all 39 references

Cited by

Metadata

Authors
Komatsu, H., Matsumoto, S., Tamaru, S.-I., Kaneko, K., Ikeda, M., & Hamachi, I.
Venue
Journal of the American Chemical Society
Published
2009-03-30
Volume
131
Issue
15
Pages
5580-5585
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2083779691
Cited by
305
References
39
FWCI
10.94
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

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.