DataVXACS NanoPaper
journal article·2022-10-25

Lateral Heterostructured Vis–NIR Photodetectors with Multimodal Detection for Rapid and Precise Classification of Glioma

Hongfei Xie, Qi Pan, Dongdong Wu, Feifei Qin, Shuoran Chen, Wei Sun, Xu Yang, Sisi Chen, Tingqing Wu, Jimei Chi, Zengqi Huang, Huadong Wang, Zeying Zhang, Bingda Chen, Jan Carmeliet, Meng Su, Yanlin Song

ACS Nano· Volume 16· Issue 10
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Source abstract

Abstract

Precise diagnosis of the boundary and grade of tumors is especially important for surgical dissection. Recently, visible and near-infrared (Vis–NIR) absorption differences of tumors are demonstrated for a precise tumor diagnosis. Here, a template-assisted sequential printing strategy is investigated to construct lateral heterostructured Vis–NIR photodetectors, relying on the up-conversion nanoparticles (UCNPs)/perovskite arrays. Under the sequential printing process, the synergistic effect and co-confinement are demonstrated to induce the UCNPs to cover both sides of the perovskite microwire. The side-wrapped lateral heterogeneous UCNPs/perovskite structure exhibits more satisfactory responsiveness to Vis–NIR light than the common fully wrapped structure, due to sufficient visible-light-harvesting ability. The Vis–NIR photodetectors with R reaching 150 mA W–1 at 980 nm and 1084 A W–1 at 450 nm are employed for the rapid classification of glioma. The detection accuracy rate of 99.3% is achieved through a multimodal analysis covering the Vis–NIR light, which provides a reliable basis for glioma grade diagnosis. This work provides a concrete example for the application of photodetectors in tumor detection and surgical diagnosis.
Source: openalex_inverted_index · Quality: baseline

Research context

NanomaterialsElectronic materials

OpenAlex topics: Perovskite Materials and Applications · Quantum Dots Synthesis And Properties · Advanced Sensor and Energy Harvesting Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS)Beijing100190, China

University of Chinese Academy of Sciences, Beijing100049, China

Department of Neurosurgery, The First Medical Centre, Chinese PLA General Hospital, Beijing100853, China

Medical School of Chinese PLA Hospital, Beijing100853, China

Department of Mechanical and Process Engineering, Swiss Federal Institute of Technology in Zürich (ETH Zürich), Zürich8092, Switzerland

Research Center for Green Printing Nanophotonic Materials, Suzhou University of Science and Technology, Suzhou, 215009, China

Institute of Software, Chinese Academy of Sciences, Beijing100049, China

Funding

Ministry of Science and Technology of the People's Republic of China · China Postdoctoral Science Foundation · Beijing Municipal Science and Technology Commission · National Natural Science Foundation of China · Beijing National Laboratory for Molecular Sciences

References (53)

Show source-provided references
1. Wang S. · Sci. Adv. · 2021 · 7 · 358810.1126/sciadv.abe3588 ↗
2. 10.1021/acsnano.2c0231410.1021/acsnano.2c02314 ↗
3. 10.1021/acsnano.1c0812010.1021/acsnano.1c08120 ↗
4. 10.1038/s41565-020-00843-710.1038/s41565-020-00843-7 ↗
5. 10.1016/j.apsb.2019.12.01210.1016/j.apsb.2019.12.012 ↗
6. 10.1126/scitranslmed.300683910.1126/scitranslmed.3006839 ↗
7. 10.1038/nrneurol.2017.4410.1038/nrneurol.2017.44 ↗
8. 10.1038/nm.226810.1038/nm.2268 ↗
9. 10.1038/srep3514210.1038/srep35142 ↗
10. 10.1126/sciadv.abb410510.1126/sciadv.abb4105 ↗
11. 10.1007/s00259-017-3916-910.1007/s00259-017-3916-9 ↗
12. 10.1093/brain/awh39910.1093/brain/awh399 ↗
13. 10.1016/j.biomaterials.2022.12153510.1016/j.biomaterials.2022.121535 ↗
14. 10.3390/photonics809036510.3390/photonics8090365 ↗
15. 10.1002/anie.20140742010.1002/anie.201407420 ↗
16. 10.1126/sciadv.abm707710.1126/sciadv.abm7077 ↗
17. 10.1038/s41598-019-45181-410.1038/s41598-019-45181-4 ↗
18. 10.1002/jbio.20210007210.1002/jbio.202100072 ↗
19. 10.1088/0031-9155/58/11/R3710.1088/0031-9155/58/11/R37 ↗
20. 10.1126/science.aaz257010.1126/science.aaz2570 ↗
21. 10.1002/adma.20160046810.1002/adma.201600468 ↗
22. Zou H. · ACS Nano · 2019 · 13 · 2289
23. 10.1126/sciadv.abg671610.1126/sciadv.abg6716 ↗
24. 10.1002/adma.20170141210.1002/adma.201701412 ↗
25. 10.1002/smll.20170253410.1002/smll.201702534 ↗
26. 10.1002/adma.20210611010.1002/adma.202106110 ↗
27. 10.1002/anie.20170659910.1002/anie.201706599 ↗
28. 10.1002/anie.20200491210.1002/anie.202004912 ↗
29. 10.1039/C6CS00896H10.1039/C6CS00896H ↗
30. 10.1038/s41928-018-0101-510.1038/s41928-018-0101-5 ↗
31. 10.1002/adma.20200548110.1002/adma.202005481 ↗
32. 10.1038/srep0059110.1038/srep00591 ↗
33. 10.1038/nature1413310.1038/nature14133 ↗
34. 10.1039/C4CS00173G10.1039/C4CS00173G ↗
35. 10.1103/PhysRevLett.7.41410.1103/PhysRevLett.7.414 ↗
36. 10.1126/science.abk259310.1126/science.abk2593 ↗
37. 10.1016/j.carbon.2019.01.07110.1016/j.carbon.2019.01.071 ↗
38. 10.1002/anie.20200258010.1002/anie.202002580 ↗
39. 10.1002/anie.20170060010.1002/anie.201700600 ↗
40. 10.1021/acsami.7b0322910.1021/acsami.7b03229 ↗
41. 10.1002/adma.20160443110.1002/adma.201604431 ↗
42. 10.1021/acs.chemrev.1c0030310.1021/acs.chemrev.1c00303 ↗
43. 10.1002/adma.20170314310.1002/adma.201703143 ↗
44. 10.1002/aenm.20150245810.1002/aenm.201502458 ↗
45. 10.1038/nphoton.2015.17510.1038/nphoton.2015.175 ↗
46. 10.1002/solr.20200021310.1002/solr.202000213 ↗
47. 10.1017/jfm.2019.6910.1017/jfm.2019.69 ↗
48. 10.1016/j.ijheatmasstransfer.2020.12000010.1016/j.ijheatmasstransfer.2020.120000 ↗
49. 10.1002/adma.20160599310.1002/adma.201605993 ↗
50. 10.1002/adma.20200199810.1002/adma.202001998 ↗
51. 10.1002/adma.20200330910.1002/adma.202003309 ↗
52. 10.1038/s41551-022-00860-y10.1038/s41551-022-00860-y ↗
53. 10.3390/s2114482610.3390/s21144826 ↗