The DOI matches its Crossref record.
High-Resolution Thin-Film Device to Sense Texture by Touch
Abstract
Touch (or tactile) sensors are gaining renewed interest as the level of sophistication in the application of minimum invasive surgery and humanoid robots increases. The spatial resolution of current large-area (greater than 1 cm 2 ) tactile sensor lags by more than an order of magnitude compared with the human finger. By using metal and semiconducting nanoparticles, a ∼100-nm-thick, large-area thin-film device is self-assembled such that the change in current density through the film and the electroluminescent light intensity are linearly proportional to the local stress. A stress image is obtained by pressing a copper grid and a United States 1-cent coin on the device and focusing the resulting electroluminescent light directly on the charge-coupled device. Both the lateral and height resolution of texture are comparable to the human finger at similar stress levels of ∼10 kilopascals.
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
Hammock, M. L., Chortos, A., Tee, B. C. ‐., Tok, J. B. ‐., & Bao, Z. (2013) · Advanced Materials · doi:10.1002/adma.201302240 · Cited by 2,396
A wearable and highly sensitive pressure sensor with ultrathin gold nanowires
Gong, S., Schwalb, W., Wang, Y., Chen, Y., Tang, Y., Si, J., Shirinzadeh, B., & Cheng, W. (2014) · Nature Communications · doi:10.1038/ncomms4132 · Cited by 2,064
Schwartz, G., Tee, B. C.-K., Mei, J., Appleton, A. L., Kim, D. H., Wang, H., & Bao, Z. (2013) · Nature Communications · doi:10.1038/ncomms2832 · Cited by 2,042
Advances of flexible pressure sensors toward artificial intelligence and health care applications
Zang, Y., Zhang, F., Di, C.-A., & Zhu, D. (2015) · Materials Horizons · doi:10.1039/c4mh00147h · Cited by 1,272
Recent Progress in Electronic Skin
Wang, X., Dong, L., Zhang, H., Yu, R., Pan, C., & Wang, Z. L. (2015) · Advanced Science · doi:10.1002/advs.201500169 · Cited by 976
Metadata
- Authors
- Maheshwari, V., & Saraf, R. F.
- Venue
- Science
- Published
- 2006-06-09
- Volume
- 312
- Issue
- 5779
- Pages
- 1501-1504
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2027041259
- Cited by
- 277
- References
- 0
- FWCI
- 12.92
- 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: High-Resolution Thin-Film Device to Sense Texture by Touch. https://app.cochat.ai/papers/10.1126/science.1126216
- The paper
- Maheshwari, V., & Saraf, R. F. (2006). High-Resolution Thin-Film Device to Sense Texture by Touch. Science. https://doi.org/10.1126/science.1126216
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.