Partial Least Squares Regression analysis of natural gas-like mixtures absorption spectra collected using a mid-infrared supercontinuum broadband source Article Swipe
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.6084/m9.figshare.c.7976648.v2
We report on a broadband gas sensor based on direct absorption spectroscopy in the mid-infrared range for the simultaneous detection of methane, ethane, and propane in natural gas-like mixtures. The system employs a broadband supercontinuum light source, coupled with an absorption cell and an optical spectrum analyzer with a resolution of 0.5 cm-1. This configuration enables reconstruction of the full absorption bands of the target alkanes, which exhibit significant spectral overlap in the 2.8-3.2 μm spectral region. A comparative study between multiple linear regression (MLR) and partial least-squares regression (PLSR) was conducted to determine the concentration of each individual component. The results highlight the superior performance of PLSR in the presence of unbalanced concentration ratios (1:10) among the three alkanes, achieving mean prediction accuracy of 98%, 93% and 94% for methane, ethane and propane, respectively.
Related Topics
- Type
- other
- Landing Page
- https://doi.org/10.6084/m9.figshare.c.7976648.v2
- OA Status
- gold
- OpenAlex ID
- https://openalex.org/W7106012568
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W7106012568Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.6084/m9.figshare.c.7976648.v2Digital Object Identifier
- Title
-
Partial Least Squares Regression analysis of natural gas-like mixtures absorption spectra collected using a mid-infrared supercontinuum broadband sourceWork title
- Type
-
otherOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-01Full publication date if available
- Authors
-
zifarelli, Andrea, formica, Paola, Sampaolo Angelo, Wu Hong-Peng, Dong Lei, Spagnolo Vincenzo, Patimisco PietroList of authors in order
- Landing page
-
https://doi.org/10.6084/m9.figshare.c.7976648.v2Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.6084/m9.figshare.c.7976648.v2Direct OA link when available
- Concepts
-
Supercontinuum, Partial least squares regression, Broadband, Absorption (acoustics), Optics, Analytical Chemistry (journal), Materials science, Absorption spectroscopy, Spectrum analyzer, Spectral line, Spectroscopy, Range (aeronautics), Linear regression, Spectral resolution, Propane, Computational physics, Chemistry, Wavelength, Calibration, Resolution (logic), Beer–Lambert law, Regression analysis, Absorptance, Least-squares function approximation, OptoelectronicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
Full payload
| id | https://openalex.org/W7106012568 |
|---|---|
| doi | https://doi.org/10.6084/m9.figshare.c.7976648.v2 |
| ids.doi | https://doi.org/10.6084/m9.figshare.c.7976648.v2 |
| ids.openalex | https://openalex.org/W7106012568 |
| fwci | |
| type | other |
| title | Partial Least Squares Regression analysis of natural gas-like mixtures absorption spectra collected using a mid-infrared supercontinuum broadband source |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C191154138 |
| concepts[0].level | 4 |
| concepts[0].score | 0.9681649804115295 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1059326 |
| concepts[0].display_name | Supercontinuum |
| concepts[1].id | https://openalex.org/C22354355 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7891997694969177 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q422009 |
| concepts[1].display_name | Partial least squares regression |
| concepts[2].id | https://openalex.org/C509933004 |
| concepts[2].level | 2 |
| concepts[2].score | 0.72981858253479 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q194163 |
| concepts[2].display_name | Broadband |
| concepts[3].id | https://openalex.org/C125287762 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5870054960250854 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1758948 |
| concepts[3].display_name | Absorption (acoustics) |
| concepts[4].id | https://openalex.org/C120665830 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5508301258087158 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q14620 |
| concepts[4].display_name | Optics |
| concepts[5].id | https://openalex.org/C113196181 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5346150994300842 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q485223 |
| concepts[5].display_name | Analytical Chemistry (journal) |
| concepts[6].id | https://openalex.org/C192562407 |
| concepts[6].level | 0 |
| concepts[6].score | 0.5340409874916077 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[6].display_name | Materials science |
| concepts[7].id | https://openalex.org/C119824511 |
| concepts[7].level | 2 |
| concepts[7].score | 0.524538516998291 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q13553575 |
| concepts[7].display_name | Absorption spectroscopy |
| concepts[8].id | https://openalex.org/C158007255 |
| concepts[8].level | 2 |
| concepts[8].score | 0.5181956887245178 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1055222 |
| concepts[8].display_name | Spectrum analyzer |
| concepts[9].id | https://openalex.org/C4839761 |
| concepts[9].level | 2 |
| concepts[9].score | 0.48224934935569763 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q212111 |
| concepts[9].display_name | Spectral line |
| concepts[10].id | https://openalex.org/C32891209 |
| concepts[10].level | 2 |
| concepts[10].score | 0.4691936671733856 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q483666 |
| concepts[10].display_name | Spectroscopy |
| concepts[11].id | https://openalex.org/C204323151 |
| concepts[11].level | 2 |
| concepts[11].score | 0.418844997882843 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q905424 |
| concepts[11].display_name | Range (aeronautics) |
| concepts[12].id | https://openalex.org/C48921125 |
| concepts[12].level | 2 |
| concepts[12].score | 0.4041418433189392 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q10861030 |
| concepts[12].display_name | Linear regression |
| concepts[13].id | https://openalex.org/C124967146 |
| concepts[13].level | 3 |
| concepts[13].score | 0.3423413634300232 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q3457898 |
| concepts[13].display_name | Spectral resolution |
| concepts[14].id | https://openalex.org/C2776345496 |
| concepts[14].level | 2 |
| concepts[14].score | 0.33331194519996643 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q131189 |
| concepts[14].display_name | Propane |
| concepts[15].id | https://openalex.org/C30475298 |
| concepts[15].level | 1 |
| concepts[15].score | 0.3151777386665344 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q909554 |
| concepts[15].display_name | Computational physics |
| concepts[16].id | https://openalex.org/C185592680 |
| concepts[16].level | 0 |
| concepts[16].score | 0.3059160113334656 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[16].display_name | Chemistry |
| concepts[17].id | https://openalex.org/C6260449 |
| concepts[17].level | 2 |
| concepts[17].score | 0.3026132881641388 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q41364 |
| concepts[17].display_name | Wavelength |
| concepts[18].id | https://openalex.org/C165838908 |
| concepts[18].level | 2 |
| concepts[18].score | 0.29579249024391174 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q736777 |
| concepts[18].display_name | Calibration |
| concepts[19].id | https://openalex.org/C138268822 |
| concepts[19].level | 2 |
| concepts[19].score | 0.29524776339530945 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q1051925 |
| concepts[19].display_name | Resolution (logic) |
| concepts[20].id | https://openalex.org/C127339321 |
| concepts[20].level | 2 |
| concepts[20].score | 0.2807796001434326 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q217351 |
| concepts[20].display_name | Beer–Lambert law |
| concepts[21].id | https://openalex.org/C152877465 |
| concepts[21].level | 2 |
| concepts[21].score | 0.2723624110221863 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q208042 |
| concepts[21].display_name | Regression analysis |
| concepts[22].id | https://openalex.org/C2780851986 |
| concepts[22].level | 3 |
| concepts[22].score | 0.2650444805622101 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q16635541 |
| concepts[22].display_name | Absorptance |
| concepts[23].id | https://openalex.org/C9936470 |
| concepts[23].level | 3 |
| concepts[23].score | 0.2582106590270996 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q6510405 |
| concepts[23].display_name | Least-squares function approximation |
| concepts[24].id | https://openalex.org/C49040817 |
| concepts[24].level | 1 |
| concepts[24].score | 0.253757506608963 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q193091 |
| concepts[24].display_name | Optoelectronics |
| keywords[0].id | https://openalex.org/keywords/supercontinuum |
| keywords[0].score | 0.9681649804115295 |
| keywords[0].display_name | Supercontinuum |
| keywords[1].id | https://openalex.org/keywords/partial-least-squares-regression |
| keywords[1].score | 0.7891997694969177 |
| keywords[1].display_name | Partial least squares regression |
| keywords[2].id | https://openalex.org/keywords/broadband |
| keywords[2].score | 0.72981858253479 |
| keywords[2].display_name | Broadband |
| keywords[3].id | https://openalex.org/keywords/absorption |
| keywords[3].score | 0.5870054960250854 |
| keywords[3].display_name | Absorption (acoustics) |
| keywords[4].id | https://openalex.org/keywords/analytical-chemistry |
| keywords[4].score | 0.5346150994300842 |
| keywords[4].display_name | Analytical Chemistry (journal) |
| keywords[5].id | https://openalex.org/keywords/absorption-spectroscopy |
| keywords[5].score | 0.524538516998291 |
| keywords[5].display_name | Absorption spectroscopy |
| keywords[6].id | https://openalex.org/keywords/spectrum-analyzer |
| keywords[6].score | 0.5181956887245178 |
| keywords[6].display_name | Spectrum analyzer |
| keywords[7].id | https://openalex.org/keywords/spectral-line |
| keywords[7].score | 0.48224934935569763 |
| keywords[7].display_name | Spectral line |
| language | |
| locations[0].id | doi:10.6084/m9.figshare.c.7976648.v2 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | |
| locations[0].raw_type | article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | False |
| locations[0].is_published | |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.6084/m9.figshare.c.7976648.v2 |
| indexed_in | datacite |
| authorships[0].author.id | |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | zifarelli, Andrea |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | zifarelli, Andrea |
| authorships[0].is_corresponding | True |
| authorships[1].author.id | |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | formica, Paola |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | formica, Paola |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A2744580156 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Sampaolo Angelo |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sampaolo, Angelo |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A2755957428 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Wu Hong-Peng |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Wu, Hongpeng |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A2095845528 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-7859-6420 |
| authorships[4].author.display_name | Dong Lei |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Dong, Lei |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A2743736157 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Spagnolo Vincenzo |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Spagnolo, Vincenzo |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A2742984227 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Patimisco Pietro |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Patimisco, Pietro |
| authorships[6].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.6084/m9.figshare.c.7976648.v2 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-11-19T00:00:00 |
| display_name | Partial Least Squares Regression analysis of natural gas-like mixtures absorption spectra collected using a mid-infrared supercontinuum broadband source |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-19T23:39:43.309859 |
| primary_topic | |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.6084/m9.figshare.c.7976648.v2 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | |
| best_oa_location.raw_type | article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.6084/m9.figshare.c.7976648.v2 |
| primary_location.id | doi:10.6084/m9.figshare.c.7976648.v2 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | |
| primary_location.raw_type | article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.6084/m9.figshare.c.7976648.v2 |
| publication_date | 2025-01-01 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.A | 77 |
| abstract_inverted_index.a | 3, 32, 48 |
| abstract_inverted_index.We | 0 |
| abstract_inverted_index.an | 39, 43 |
| abstract_inverted_index.in | 12, 25, 71, 108 |
| abstract_inverted_index.of | 20, 50, 57, 62, 96, 106, 111, 124 |
| abstract_inverted_index.on | 2, 8 |
| abstract_inverted_index.to | 92 |
| abstract_inverted_index.0.5 | 51 |
| abstract_inverted_index.93% | 126 |
| abstract_inverted_index.94% | 128 |
| abstract_inverted_index.The | 29, 100 |
| abstract_inverted_index.and | 23, 42, 85, 127, 132 |
| abstract_inverted_index.for | 16, 129 |
| abstract_inverted_index.gas | 5 |
| abstract_inverted_index.the | 13, 17, 58, 63, 72, 94, 103, 109, 117 |
| abstract_inverted_index.was | 90 |
| abstract_inverted_index.μm | 74 |
| abstract_inverted_index.98%, | 125 |
| abstract_inverted_index.PLSR | 107 |
| abstract_inverted_index.This | 53 |
| abstract_inverted_index.cell | 41 |
| abstract_inverted_index.each | 97 |
| abstract_inverted_index.full | 59 |
| abstract_inverted_index.mean | 121 |
| abstract_inverted_index.with | 38, 47 |
| abstract_inverted_index.(MLR) | 84 |
| abstract_inverted_index.among | 116 |
| abstract_inverted_index.bands | 61 |
| abstract_inverted_index.based | 7 |
| abstract_inverted_index.cm-1. | 52 |
| abstract_inverted_index.light | 35 |
| abstract_inverted_index.range | 15 |
| abstract_inverted_index.study | 79 |
| abstract_inverted_index.three | 118 |
| abstract_inverted_index.which | 66 |
| abstract_inverted_index.(1:10) | 115 |
| abstract_inverted_index.(PLSR) | 89 |
| abstract_inverted_index.direct | 9 |
| abstract_inverted_index.ethane | 131 |
| abstract_inverted_index.linear | 82 |
| abstract_inverted_index.ratios | 114 |
| abstract_inverted_index.report | 1 |
| abstract_inverted_index.sensor | 6 |
| abstract_inverted_index.system | 30 |
| abstract_inverted_index.target | 64 |
| abstract_inverted_index.2.8-3.2 | 73 |
| abstract_inverted_index.between | 80 |
| abstract_inverted_index.coupled | 37 |
| abstract_inverted_index.employs | 31 |
| abstract_inverted_index.enables | 55 |
| abstract_inverted_index.ethane, | 22 |
| abstract_inverted_index.exhibit | 67 |
| abstract_inverted_index.natural | 26 |
| abstract_inverted_index.optical | 44 |
| abstract_inverted_index.overlap | 70 |
| abstract_inverted_index.partial | 86 |
| abstract_inverted_index.propane | 24 |
| abstract_inverted_index.region. | 76 |
| abstract_inverted_index.results | 101 |
| abstract_inverted_index.source, | 36 |
| abstract_inverted_index.accuracy | 123 |
| abstract_inverted_index.alkanes, | 65, 119 |
| abstract_inverted_index.analyzer | 46 |
| abstract_inverted_index.gas-like | 27 |
| abstract_inverted_index.methane, | 21, 130 |
| abstract_inverted_index.multiple | 81 |
| abstract_inverted_index.presence | 110 |
| abstract_inverted_index.propane, | 133 |
| abstract_inverted_index.spectral | 69, 75 |
| abstract_inverted_index.spectrum | 45 |
| abstract_inverted_index.superior | 104 |
| abstract_inverted_index.achieving | 120 |
| abstract_inverted_index.broadband | 4, 33 |
| abstract_inverted_index.conducted | 91 |
| abstract_inverted_index.detection | 19 |
| abstract_inverted_index.determine | 93 |
| abstract_inverted_index.highlight | 102 |
| abstract_inverted_index.mixtures. | 28 |
| abstract_inverted_index.absorption | 10, 40, 60 |
| abstract_inverted_index.component. | 99 |
| abstract_inverted_index.individual | 98 |
| abstract_inverted_index.prediction | 122 |
| abstract_inverted_index.regression | 83, 88 |
| abstract_inverted_index.resolution | 49 |
| abstract_inverted_index.unbalanced | 112 |
| abstract_inverted_index.comparative | 78 |
| abstract_inverted_index.performance | 105 |
| abstract_inverted_index.significant | 68 |
| abstract_inverted_index.mid-infrared | 14 |
| abstract_inverted_index.simultaneous | 18 |
| abstract_inverted_index.spectroscopy | 11 |
| abstract_inverted_index.concentration | 95, 113 |
| abstract_inverted_index.configuration | 54 |
| abstract_inverted_index.least-squares | 87 |
| abstract_inverted_index.respectively. | 134 |
| abstract_inverted_index.reconstruction | 56 |
| abstract_inverted_index.supercontinuum | 34 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |