Title |
Selective layer-free blood serum ionogram based on ion-specific interactions with a nanotransistor
|
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Published in |
Nature Materials, February 2018
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DOI | 10.1038/s41563-017-0016-y |
Pubmed ID | |
Authors |
R. Sivakumarasamy, R. Hartkamp, B. Siboulet, J.-F. Dufrêche, K. Nishiguchi, A. Fujiwara, N. Clément |
Abstract |
Despite being ubiquitous in the fields of chemistry and biology, the ion-specific effects of electrolytes pose major challenges for researchers. A lack of understanding about ion-specific surface interactions has hampered the development and application of materials for (bio-)chemical sensor applications. Here, we show that scaling a silicon nanotransistor sensor down to ~25 nm provides a unique opportunity to understand and exploit ion-specific surface interactions, yielding a surface that is highly sensitive to cations and inert to pH. The unprecedented sensitivity of these devices to Na+ and divalent ions can be attributed to an overscreening effect via molecular dynamics. The surface potential of multi-ion solutions is well described by the sum of the electrochemical potentials of each cation, enabling selective measurements of a target ion concentration without requiring a selective organic layer. We use these features to construct a blood serum ionogram for Na+, K+, Ca2+ and Mg2+, in an important step towards the development of a versatile, durable and mobile chemical or blood diagnostic tool. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Australia | 1 | 13% |
United Kingdom | 1 | 13% |
United States | 1 | 13% |
Unknown | 5 | 63% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 63% |
Scientists | 2 | 25% |
Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 67 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 20 | 30% |
Researcher | 13 | 19% |
Student > Master | 5 | 7% |
Student > Bachelor | 3 | 4% |
Lecturer | 3 | 4% |
Other | 7 | 10% |
Unknown | 16 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 14 | 21% |
Chemistry | 8 | 12% |
Physics and Astronomy | 7 | 10% |
Materials Science | 4 | 6% |
Agricultural and Biological Sciences | 3 | 4% |
Other | 10 | 15% |
Unknown | 21 | 31% |