{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T07:35:18Z","timestamp":1780644918769,"version":"3.54.1"},"reference-count":58,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,12,20]],"date-time":"2019-12-20T00:00:00Z","timestamp":1576800000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanghai Academic\/Technology Research Leader Program","award":["19XD1422900"],"award-info":[{"award-number":["19XD1422900"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51572173, 51602197, 51771121 and 51702212"],"award-info":[{"award-number":["51572173, 51602197, 51771121 and 51702212"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["19ZR1435200, 18511110600 and 19JC1410402"],"award-info":[{"award-number":["19ZR1435200, 18511110600 and 19JC1410402"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation Program of Shanghai Municipal Education Commission","award":["2019-01-07-00-07-E00015"],"award-info":[{"award-number":["2019-01-07-00-07-E00015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>In this work, we reported a formaldehyde (HCHO) gas sensor with highly sensitive and selective gas-sensing performance at low operating temperature based on graphene oxide (GO)@SnO2 nanofiber\/nanosheets (NF\/NSs) nanocomposites. Hierarchical SnO2 NF\/NSs coated with GO nanosheets showed enhanced sensing performance for HCHO gas, especially at low operating temperature. A series of characterization methods, including X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), Transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS) and Brunauer\u2013Emmett\u2013Teller (BET) were used to characterize their microstructures, morphologies, compositions, surface areas and so on. The sensing performance of GO@SnO2 NF\/NSs nanocomposites was optimized by adjusting the loading amount of GO ranging from 0.25% to 1.25%. The results showed the optimum loading amount of 1% GO in GO@SnO2 NF\/NSs nanocomposites not only exhibited the highest sensitivity value (Ra\/Rg = 280 to 100 ppm HCHO gas) but also lowered the optimum operation temperature from 120 \u00b0C to 60 \u00b0C. The response value was about 4.5 times higher than that of pure hierarchical SnO2 NF\/NSs (Ra\/Rg = 64 to 100 ppm). GO@SnO2 NF\/NSs nanocomposites showed lower detection limit down to 0.25 ppm HCHO and excellent selectivity against interfering gases (ethanol (C2H5OH), acetone (CH3COCH3), methanol (CH3OH), ammonia (NH3), methylbenzene (C7H8), benzene (C6H6) and water (H2O)). The enhanced sensing performance for HCHO was mainly ascribed to the high specific surface area, suitable electron transfer channels and the synergistic effect of the SnO2 NF\/NSs and GO nanosheets network.<\/jats:p>","DOI":"10.3390\/molecules25010035","type":"journal-article","created":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T03:23:12Z","timestamp":1577071392000},"page":"35","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Graphene Oxide@3D Hierarchical SnO2 Nanofiber\/Nanosheets Nanocomposites for Highly Sensitive and Low-Temperature Formaldehyde Detection"],"prefix":"10.3390","volume":"25","author":[{"given":"Kechuang","family":"Wan","sequence":"first","affiliation":[{"name":"School of Materials Science and Engineering, University of Shanghai for Science &amp; Technology, No. 516 JunGong Road, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Materials Science and Engineering, University of Shanghai for Science &amp; Technology, No. 516 JunGong Road, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ding","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Materials Science and Engineering, University of Shanghai for Science &amp; Technology, No. 516 JunGong Road, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianying","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Materials Science and Engineering, University of Shanghai for Science &amp; Technology, No. 516 JunGong Road, Shanghai 200093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.snb.2016.08.085","article-title":"Quantitative detection of formaldehyde and ammonia gas via metal oxide-modified graphene-based sensor array combining with neural network model","volume":"240","author":"Zhang","year":"2017","journal-title":"Sens. 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