# Fileset

[c8mh01169a1_si.pdf](https://mdr.nims.go.jp/filesets/d299dda9-f834-47d4-b472-0596bceb544a/download)

## Creator

[Kosuke Minami](https://orcid.org/0000-0003-4145-1118), [Gaku Imamura](https://orcid.org/0000-0002-3130-7190), Takahiro Nemoto, [Kota Shiba](https://orcid.org/0000-0001-7775-0318), [Genki Yoshikawa](https://orcid.org/0000-0002-9136-8964)

## Rights



## Other metadata

[Pattern recognition of solid materials by multiple probe gases](https://mdr.nims.go.jp/datasets/5ea1413e-8f06-41c1-b6c3-e4f335cf9729)

## Fulltext

In vivo siRNA delivery to lung via agglutination-induced accumulation and clearance of cationic tetraamino fullereneElectronic Supplementary InformationPattern Recognition of Solid Materials by Multiple Probe GasesKosuke Minami,*a,b Gaku Imamura,a,b Takahiro Nemoto,a Kota Shibaa,b Genki Yoshikawaa,b,va. Center for Functional Sensor & Actuator (CFSN), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan. b. International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Japanc. Materials Science and Engineering, Graduate School of Pure and Applied Science, University of Tsukuba, Tennodai 1-1-1 Tsukuba, Ibaraki 305-8571, Japan* To whom correspondence should be addressed. E-mail: MINAMI.Kosuke@nims.go.jp (K. M.), 1Electronic Supplementary Material (ESI) for Materials Horizons.This journal is © The Royal Society of Chemistry 2018Supplementary TextSelection of solid materials. In general, discrimination of chemically different targets by means of the pattern recognition approaches is rather easy, such as discrimination between hydrophobic and hydrophilic materials. Thus, as a proof-of-concept, we selected practically difficult sets of materials in terms of hydrophobic polymers as well as the different molecular weight of polymers in this present study.2Supplementary FiguresFig. S1  Structures of polymer materials used in this study.3Fig. S2  Signal responses of each material measured with 12 different vapours. Top to bottom figures indicate the response to water, ethanol, 1-hexanol, hexanal, n-heptane, and methylcycloehxane, respectively.4Fig. S2 (Continued)  Signal responses of each material measured with 12 different vapours. Top to bottom figures indicate the response to toluene, ethyl acetate, acetone, chloroform, aniline and propionic acid, respectively.5Fig. S3  Identification of polymers by pattern recognition. PCA (Top left, Top right, Bottom left) and LDA (Bottom right) score plots to identify 4 materials coated on MSS by measuring with 12 different vapours. PS (350k), polystyrene (red); P4MS, poly(4-methylstyrene) (black); PVF, poly(vinylidene fluoride) (green); PCL, polycaprolactone (blue). N = 11.6Fig. S4  Classification accuracy of polymer materials of selected combinations including selected solvents as a function of number of solvents (n). Average classification accuracies with standard deviations are shown. 7Fig. S5  PCA score plots of features from each solvent to discriminate 4 different polymer materials. PS (350k), polystyrene (red); P4MS, poly(4-methylstyrene) (black); PVF, poly(vinylidene fluoride) (green); PCL, polycaprolactone (blue). N = 11.8Fig. S6  Classification accuracy of different molecular weight of selected combinations including selected solvents as a function of number of solvents (n). Average classification accuracies with standard deviations are shown.9Fig. S7  PCA score plots of features from each solvent to discriminate 4 different polymer materials. PS (350k), polystyrene, Mw = 350000 (blue); P4MS, poly(4-methylstyrene), Mw = 72000 (black); PS (280k), polystyrene, Mw = 280000 (red); PS (35k), polystyrene, Mw = 35000 (green).10Fig. S8  PCA score plots of polyvinylfluoride (PVF) (left) and their Mahalanobis distances (right). Red dashed line is an example of the range for determination of quality.Fig. S9  PCA score plots of polycaporolactone (PCL) (left) and their Mahalanobis distances (right). Red dashed line is an example of the range for determination of quality.11