Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces Article Swipe
Mehrdad Jalali
,
Lachlan Caulfield
,
Eric Sauter
,
Alexei Nefedov
,
Chengwu Yang
,
Christof Wöll
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/aidi.202500046
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/aidi.202500046
This study presents a novel convolutional neural network (CNN) architecture that represents a significant advancement in the unsupervised analysis of data from infrared (IR) spectroscopy, both in IRRAS (infrared reflection absorption spectroscopy) and in DRIFTS (diffuse reflection infrared Fourier transform spectroscopy). After measuring reference data for single‐crystal samples using IRRAS, DRIFTS allows the characterization of surfaces exposed by cerium oxide powder particles through the stretch frequency of adsorbed probe molecules. To enable real‐time monitoring of catalyst modification during exposure to reactive gases under reaction conditions, a rapid, unsupervised analysis of the DRIFTS data is required. It is demonstrated that this goal can be achieved by using a CNN with an optimized architecture. This model is proficient in determining the intensities of the adsorbed CO bands, which depend on the crystallographic orientation and oxidation state of the exposed facets. The CNN design incorporates parallel 1D convolutional layers with varied kernel sizes. These layers work in tandem to capture spectral features. To address the challenge of overfitting, advanced regularization techniques within the CNN are integrated, enhancing the model's performance on new, unseen data. In particular, this approach to generating synthetic data has been instrumental in improving the performance of the CNN. The employment of the Adam optimizer and the mean squared error loss function aligns the model for efficient learning, ensuring accurate and reliable predictions. By introducing this CNN architecture, a robust, precise, and adaptable tool for rapid, unsupervised spectroscopic analysis is provided, demonstrating the potential of deep learning combined with synthetic data generation for advanced spectroscopy applications.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/aidi.202500046
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046
- OA Status
- hybrid
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413491847
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4413491847Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/aidi.202500046Digital Object Identifier
- Title
-
Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts SurfacesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-08-25Full publication date if available
- Authors
-
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof WöllList of authors in order
- Landing page
-
https://doi.org/10.1002/aidi.202500046Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046Direct OA link when available
- Concepts
-
Characterization (materials science), Catalysis, Spectroscopy, Materials science, Infrared spectroscopy, Artificial neural network, Chemical engineering, Nanotechnology, Chemistry, Computer science, Organic chemistry, Engineering, Physics, Artificial intelligence, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4413491847 |
|---|---|
| doi | https://doi.org/10.1002/aidi.202500046 |
| ids.doi | https://doi.org/10.1002/aidi.202500046 |
| ids.openalex | https://openalex.org/W4413491847 |
| fwci | 0.0 |
| type | article |
| title | Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces |
| awards[0].id | https://openalex.org/G8275781865 |
| awards[0].funder_id | https://openalex.org/F4320320879 |
| awards[0].display_name | |
| awards[0].funder_award_id | 426888090‐SFB 1441 |
| awards[0].funder_display_name | Deutsche Forschungsgemeinschaft |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10192 |
| topics[0].field.id | https://openalex.org/fields/25 |
| topics[0].field.display_name | Materials Science |
| topics[0].score | 0.9926000237464905 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2505 |
| topics[0].subfield.display_name | Materials Chemistry |
| topics[0].display_name | Catalytic Processes in Materials Science |
| topics[1].id | https://openalex.org/T10461 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9824000000953674 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2208 |
| topics[1].subfield.display_name | Electrical and Electronic Engineering |
| topics[1].display_name | Gas Sensing Nanomaterials and Sensors |
| topics[2].id | https://openalex.org/T14249 |
| topics[2].field.id | https://openalex.org/fields/23 |
| topics[2].field.display_name | Environmental Science |
| topics[2].score | 0.9812999963760376 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2311 |
| topics[2].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[2].display_name | Water Quality Monitoring and Analysis |
| funders[0].id | https://openalex.org/F4320320879 |
| funders[0].ror | https://ror.org/018mejw64 |
| funders[0].display_name | Deutsche Forschungsgemeinschaft |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2780841128 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7752457857131958 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5073781 |
| concepts[0].display_name | Characterization (materials science) |
| concepts[1].id | https://openalex.org/C161790260 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7572579979896545 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q82264 |
| concepts[1].display_name | Catalysis |
| concepts[2].id | https://openalex.org/C32891209 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5688179135322571 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q483666 |
| concepts[2].display_name | Spectroscopy |
| concepts[3].id | https://openalex.org/C192562407 |
| concepts[3].level | 0 |
| concepts[3].score | 0.5096461772918701 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[3].display_name | Materials science |
| concepts[4].id | https://openalex.org/C153642686 |
| concepts[4].level | 2 |
| concepts[4].score | 0.44392693042755127 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q70906 |
| concepts[4].display_name | Infrared spectroscopy |
| concepts[5].id | https://openalex.org/C50644808 |
| concepts[5].level | 2 |
| concepts[5].score | 0.43874645233154297 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[5].display_name | Artificial neural network |
| concepts[6].id | https://openalex.org/C42360764 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3897855877876282 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q83588 |
| concepts[6].display_name | Chemical engineering |
| concepts[7].id | https://openalex.org/C171250308 |
| concepts[7].level | 1 |
| concepts[7].score | 0.2947995066642761 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11468 |
| concepts[7].display_name | Nanotechnology |
| concepts[8].id | https://openalex.org/C185592680 |
| concepts[8].level | 0 |
| concepts[8].score | 0.27557140588760376 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[8].display_name | Chemistry |
| concepts[9].id | https://openalex.org/C41008148 |
| concepts[9].level | 0 |
| concepts[9].score | 0.24333590269088745 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[9].display_name | Computer science |
| concepts[10].id | https://openalex.org/C178790620 |
| concepts[10].level | 1 |
| concepts[10].score | 0.12528428435325623 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11351 |
| concepts[10].display_name | Organic chemistry |
| concepts[11].id | https://openalex.org/C127413603 |
| concepts[11].level | 0 |
| concepts[11].score | 0.09040197730064392 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[11].display_name | Engineering |
| concepts[12].id | https://openalex.org/C121332964 |
| concepts[12].level | 0 |
| concepts[12].score | 0.08448895812034607 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[12].display_name | Physics |
| concepts[13].id | https://openalex.org/C154945302 |
| concepts[13].level | 1 |
| concepts[13].score | 0.08276501297950745 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[13].display_name | Artificial intelligence |
| concepts[14].id | https://openalex.org/C62520636 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[14].display_name | Quantum mechanics |
| keywords[0].id | https://openalex.org/keywords/characterization |
| keywords[0].score | 0.7752457857131958 |
| keywords[0].display_name | Characterization (materials science) |
| keywords[1].id | https://openalex.org/keywords/catalysis |
| keywords[1].score | 0.7572579979896545 |
| keywords[1].display_name | Catalysis |
| keywords[2].id | https://openalex.org/keywords/spectroscopy |
| keywords[2].score | 0.5688179135322571 |
| keywords[2].display_name | Spectroscopy |
| keywords[3].id | https://openalex.org/keywords/materials-science |
| keywords[3].score | 0.5096461772918701 |
| keywords[3].display_name | Materials science |
| keywords[4].id | https://openalex.org/keywords/infrared-spectroscopy |
| keywords[4].score | 0.44392693042755127 |
| keywords[4].display_name | Infrared spectroscopy |
| keywords[5].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[5].score | 0.43874645233154297 |
| keywords[5].display_name | Artificial neural network |
| keywords[6].id | https://openalex.org/keywords/chemical-engineering |
| keywords[6].score | 0.3897855877876282 |
| keywords[6].display_name | Chemical engineering |
| keywords[7].id | https://openalex.org/keywords/nanotechnology |
| keywords[7].score | 0.2947995066642761 |
| keywords[7].display_name | Nanotechnology |
| keywords[8].id | https://openalex.org/keywords/chemistry |
| keywords[8].score | 0.27557140588760376 |
| keywords[8].display_name | Chemistry |
| keywords[9].id | https://openalex.org/keywords/computer-science |
| keywords[9].score | 0.24333590269088745 |
| keywords[9].display_name | Computer science |
| keywords[10].id | https://openalex.org/keywords/organic-chemistry |
| keywords[10].score | 0.12528428435325623 |
| keywords[10].display_name | Organic chemistry |
| keywords[11].id | https://openalex.org/keywords/engineering |
| keywords[11].score | 0.09040197730064392 |
| keywords[11].display_name | Engineering |
| keywords[12].id | https://openalex.org/keywords/physics |
| keywords[12].score | 0.08448895812034607 |
| keywords[12].display_name | Physics |
| keywords[13].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[13].score | 0.08276501297950745 |
| keywords[13].display_name | Artificial intelligence |
| language | en |
| locations[0].id | doi:10.1002/aidi.202500046 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S5407036554 |
| locations[0].source.issn | 2943-9981 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 2943-9981 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Advanced Intelligent Discovery |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Advanced Intelligent Discovery |
| locations[0].landing_page_url | https://doi.org/10.1002/aidi.202500046 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5002207845 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2465-4933 |
| authorships[0].author.display_name | Mehrdad Jalali |
| authorships[0].countries | DE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[0].affiliations[0].raw_affiliation_string | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[0].affiliations[1].raw_affiliation_string | Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[0].affiliations[2].institution_ids | https://openalex.org/I4210091948 |
| authorships[0].affiliations[2].raw_affiliation_string | Applied Data Science and Artificial Intelligence SRH University Heidelberg Heidelberg Germany |
| authorships[0].affiliations[3].institution_ids | https://openalex.org/I223822909, https://openalex.org/I4210091948 |
| authorships[0].affiliations[3].raw_affiliation_string | Applied Data Science and Artificial Intelligence, SRH University Heidelberg, Heidelberg, Germany |
| authorships[0].institutions[0].id | https://openalex.org/I158675288 |
| authorships[0].institutions[0].ror | https://ror.org/0387prb75 |
| authorships[0].institutions[0].type | nonprofit |
| authorships[0].institutions[0].lineage | https://openalex.org/I158675288, https://openalex.org/I315704651 |
| authorships[0].institutions[0].country_code | DE |
| authorships[0].institutions[0].display_name | FIZ Karlsruhe – Leibniz Institute for Information Infrastructure |
| authorships[0].institutions[1].id | https://openalex.org/I223822909 |
| authorships[0].institutions[1].ror | https://ror.org/038t36y30 |
| authorships[0].institutions[1].type | education |
| authorships[0].institutions[1].lineage | https://openalex.org/I223822909 |
| authorships[0].institutions[1].country_code | DE |
| authorships[0].institutions[1].display_name | Heidelberg University |
| authorships[0].institutions[2].id | https://openalex.org/I102335020 |
| authorships[0].institutions[2].ror | https://ror.org/04t3en479 |
| authorships[0].institutions[2].type | education |
| authorships[0].institutions[2].lineage | https://openalex.org/I102335020, https://openalex.org/I1305996414 |
| authorships[0].institutions[2].country_code | DE |
| authorships[0].institutions[2].display_name | Karlsruhe Institute of Technology |
| authorships[0].institutions[3].id | https://openalex.org/I4210091948 |
| authorships[0].institutions[3].ror | https://ror.org/00g07sz63 |
| authorships[0].institutions[3].type | education |
| authorships[0].institutions[3].lineage | https://openalex.org/I4210091948 |
| authorships[0].institutions[3].country_code | DE |
| authorships[0].institutions[3].display_name | SRH Hochschule Heidelberg |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mehrdad Jalali |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Applied Data Science and Artificial Intelligence SRH University Heidelberg Heidelberg Germany, Applied Data Science and Artificial Intelligence, SRH University Heidelberg, Heidelberg, Germany, Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany, Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[1].author.id | https://openalex.org/A5100281736 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Lachlan Caulfield |
| authorships[1].countries | DE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[1].affiliations[0].raw_affiliation_string | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[1].affiliations[1].raw_affiliation_string | Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[1].institutions[0].id | https://openalex.org/I158675288 |
| authorships[1].institutions[0].ror | https://ror.org/0387prb75 |
| authorships[1].institutions[0].type | nonprofit |
| authorships[1].institutions[0].lineage | https://openalex.org/I158675288, https://openalex.org/I315704651 |
| authorships[1].institutions[0].country_code | DE |
| authorships[1].institutions[0].display_name | FIZ Karlsruhe – Leibniz Institute for Information Infrastructure |
| authorships[1].institutions[1].id | https://openalex.org/I102335020 |
| authorships[1].institutions[1].ror | https://ror.org/04t3en479 |
| authorships[1].institutions[1].type | education |
| authorships[1].institutions[1].lineage | https://openalex.org/I102335020, https://openalex.org/I1305996414 |
| authorships[1].institutions[1].country_code | DE |
| authorships[1].institutions[1].display_name | Karlsruhe Institute of Technology |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Lachlan Caulfield |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany, Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[2].author.id | https://openalex.org/A5027626637 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-7630-8675 |
| authorships[2].author.display_name | Eric Sauter |
| authorships[2].countries | DE |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[2].affiliations[0].raw_affiliation_string | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany |
| authorships[2].affiliations[1].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[2].affiliations[1].raw_affiliation_string | Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[2].institutions[0].id | https://openalex.org/I158675288 |
| authorships[2].institutions[0].ror | https://ror.org/0387prb75 |
| authorships[2].institutions[0].type | nonprofit |
| authorships[2].institutions[0].lineage | https://openalex.org/I158675288, https://openalex.org/I315704651 |
| authorships[2].institutions[0].country_code | DE |
| authorships[2].institutions[0].display_name | FIZ Karlsruhe – Leibniz Institute for Information Infrastructure |
| authorships[2].institutions[1].id | https://openalex.org/I102335020 |
| authorships[2].institutions[1].ror | https://ror.org/04t3en479 |
| authorships[2].institutions[1].type | education |
| authorships[2].institutions[1].lineage | https://openalex.org/I102335020, https://openalex.org/I1305996414 |
| authorships[2].institutions[1].country_code | DE |
| authorships[2].institutions[1].display_name | Karlsruhe Institute of Technology |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Eric Sauter |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany, Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[3].author.id | https://openalex.org/A5063865325 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-2771-6386 |
| authorships[3].author.display_name | Alexei Nefedov |
| authorships[3].countries | DE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[3].affiliations[0].raw_affiliation_string | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[3].affiliations[1].raw_affiliation_string | Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[3].institutions[0].id | https://openalex.org/I158675288 |
| authorships[3].institutions[0].ror | https://ror.org/0387prb75 |
| authorships[3].institutions[0].type | nonprofit |
| authorships[3].institutions[0].lineage | https://openalex.org/I158675288, https://openalex.org/I315704651 |
| authorships[3].institutions[0].country_code | DE |
| authorships[3].institutions[0].display_name | FIZ Karlsruhe – Leibniz Institute for Information Infrastructure |
| authorships[3].institutions[1].id | https://openalex.org/I102335020 |
| authorships[3].institutions[1].ror | https://ror.org/04t3en479 |
| authorships[3].institutions[1].type | education |
| authorships[3].institutions[1].lineage | https://openalex.org/I102335020, https://openalex.org/I1305996414 |
| authorships[3].institutions[1].country_code | DE |
| authorships[3].institutions[1].display_name | Karlsruhe Institute of Technology |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Alexei Nefedov |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany, Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[4].author.id | https://openalex.org/A5103035336 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-9518-1937 |
| authorships[4].author.display_name | Chengwu Yang |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210159903 |
| authorships[4].affiliations[0].raw_affiliation_string | State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences Taiyuan China |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I4210159903 |
| authorships[4].affiliations[1].raw_affiliation_string | State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, China |
| authorships[4].institutions[0].id | https://openalex.org/I4210159903 |
| authorships[4].institutions[0].ror | https://ror.org/05j73fd60 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210159903 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Institute of Coal Chemistry |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Chengwu Yang |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences Taiyuan China, State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, China |
| authorships[5].author.id | https://openalex.org/A5064307923 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-1078-3304 |
| authorships[5].author.display_name | Christof Wöll |
| authorships[5].countries | DE |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[5].affiliations[0].raw_affiliation_string | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany |
| authorships[5].affiliations[1].institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| authorships[5].affiliations[1].raw_affiliation_string | Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| authorships[5].institutions[0].id | https://openalex.org/I158675288 |
| authorships[5].institutions[0].ror | https://ror.org/0387prb75 |
| authorships[5].institutions[0].type | nonprofit |
| authorships[5].institutions[0].lineage | https://openalex.org/I158675288, https://openalex.org/I315704651 |
| authorships[5].institutions[0].country_code | DE |
| authorships[5].institutions[0].display_name | FIZ Karlsruhe – Leibniz Institute for Information Infrastructure |
| authorships[5].institutions[1].id | https://openalex.org/I102335020 |
| authorships[5].institutions[1].ror | https://ror.org/04t3en479 |
| authorships[5].institutions[1].type | education |
| authorships[5].institutions[1].lineage | https://openalex.org/I102335020, https://openalex.org/I1305996414 |
| authorships[5].institutions[1].country_code | DE |
| authorships[5].institutions[1].display_name | Karlsruhe Institute of Technology |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Christof Wöll |
| authorships[5].is_corresponding | True |
| authorships[5].raw_affiliation_strings | Institute of Functional Interfaces Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany, Institute of Functional Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046 |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10192 |
| primary_topic.field.id | https://openalex.org/fields/25 |
| primary_topic.field.display_name | Materials Science |
| primary_topic.score | 0.9926000237464905 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2505 |
| primary_topic.subfield.display_name | Materials Chemistry |
| primary_topic.display_name | Catalytic Processes in Materials Science |
| related_works | https://openalex.org/W1542038854, https://openalex.org/W3131063699, https://openalex.org/W4230137352, https://openalex.org/W2108613701, https://openalex.org/W2415545749, https://openalex.org/W2185041379, https://openalex.org/W1612801273, https://openalex.org/W4255036497, https://openalex.org/W3128057522, https://openalex.org/W2137261382 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1002/aidi.202500046 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S5407036554 |
| best_oa_location.source.issn | 2943-9981 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 2943-9981 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Advanced Intelligent Discovery |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Advanced Intelligent Discovery |
| best_oa_location.landing_page_url | https://doi.org/10.1002/aidi.202500046 |
| primary_location.id | doi:10.1002/aidi.202500046 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S5407036554 |
| primary_location.source.issn | 2943-9981 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 2943-9981 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Advanced Intelligent Discovery |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500046 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Advanced Intelligent Discovery |
| primary_location.landing_page_url | https://doi.org/10.1002/aidi.202500046 |
| publication_date | 2025-08-25 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W1985932475, https://openalex.org/W4391815520, https://openalex.org/W4327950405, https://openalex.org/W4377097130, https://openalex.org/W4390731798, https://openalex.org/W4281777292, https://openalex.org/W2989713123, https://openalex.org/W4400612834, https://openalex.org/W2564339002, https://openalex.org/W2770854636, https://openalex.org/W4392718537, https://openalex.org/W4407977858, https://openalex.org/W4403907309, https://openalex.org/W2560681522, https://openalex.org/W3088453147, https://openalex.org/W2917488426, https://openalex.org/W4399704261, https://openalex.org/W4386445127, https://openalex.org/W4393951483, https://openalex.org/W4297014968, https://openalex.org/W4391134001, https://openalex.org/W4384023804, https://openalex.org/W4384625967, https://openalex.org/W3101195217, https://openalex.org/W2790596925, https://openalex.org/W4312116392, https://openalex.org/W4313827455, https://openalex.org/W2051143281, https://openalex.org/W2957505348, https://openalex.org/W2562951671, https://openalex.org/W4405929415, https://openalex.org/W4280624957, https://openalex.org/W4397023103, https://openalex.org/W3012727703 |
| referenced_works_count | 34 |
| abstract_inverted_index.a | 3, 12, 85, 106, 228 |
| abstract_inverted_index.1D | 143 |
| abstract_inverted_index.By | 223 |
| abstract_inverted_index.CO | 123 |
| abstract_inverted_index.In | 181 |
| abstract_inverted_index.It | 95 |
| abstract_inverted_index.To | 70, 159 |
| abstract_inverted_index.an | 109 |
| abstract_inverted_index.be | 102 |
| abstract_inverted_index.by | 57, 104 |
| abstract_inverted_index.in | 15, 26, 33, 116, 153, 192 |
| abstract_inverted_index.is | 93, 96, 114, 239 |
| abstract_inverted_index.of | 19, 54, 66, 74, 89, 120, 134, 163, 196, 201, 244 |
| abstract_inverted_index.on | 127, 177 |
| abstract_inverted_index.to | 79, 155, 185 |
| abstract_inverted_index.CNN | 107, 139, 170, 226 |
| abstract_inverted_index.The | 138, 199 |
| abstract_inverted_index.and | 32, 131, 205, 220, 231 |
| abstract_inverted_index.are | 171 |
| abstract_inverted_index.can | 101 |
| abstract_inverted_index.for | 45, 215, 234, 252 |
| abstract_inverted_index.has | 189 |
| abstract_inverted_index.the | 16, 52, 63, 90, 118, 121, 128, 135, 161, 169, 174, 194, 197, 202, 206, 213, 242 |
| abstract_inverted_index.(IR) | 23 |
| abstract_inverted_index.Adam | 203 |
| abstract_inverted_index.CNN. | 198 |
| abstract_inverted_index.This | 0, 112 |
| abstract_inverted_index.been | 190 |
| abstract_inverted_index.both | 25 |
| abstract_inverted_index.data | 20, 44, 92, 188, 250 |
| abstract_inverted_index.deep | 245 |
| abstract_inverted_index.from | 21 |
| abstract_inverted_index.goal | 100 |
| abstract_inverted_index.loss | 210 |
| abstract_inverted_index.mean | 207 |
| abstract_inverted_index.new, | 178 |
| abstract_inverted_index.that | 10, 98 |
| abstract_inverted_index.this | 99, 183, 225 |
| abstract_inverted_index.tool | 233 |
| abstract_inverted_index.with | 108, 146, 248 |
| abstract_inverted_index.work | 152 |
| abstract_inverted_index.(CNN) | 8 |
| abstract_inverted_index.After | 41 |
| abstract_inverted_index.IRRAS | 27 |
| abstract_inverted_index.These | 150 |
| abstract_inverted_index.data. | 180 |
| abstract_inverted_index.error | 209 |
| abstract_inverted_index.gases | 81 |
| abstract_inverted_index.model | 113, 214 |
| abstract_inverted_index.novel | 4 |
| abstract_inverted_index.oxide | 59 |
| abstract_inverted_index.probe | 68 |
| abstract_inverted_index.state | 133 |
| abstract_inverted_index.study | 1 |
| abstract_inverted_index.under | 82 |
| abstract_inverted_index.using | 48, 105 |
| abstract_inverted_index.which | 125 |
| abstract_inverted_index.DRIFTS | 34, 50, 91 |
| abstract_inverted_index.IRRAS, | 49 |
| abstract_inverted_index.aligns | 212 |
| abstract_inverted_index.allows | 51 |
| abstract_inverted_index.bands, | 124 |
| abstract_inverted_index.cerium | 58 |
| abstract_inverted_index.depend | 126 |
| abstract_inverted_index.design | 140 |
| abstract_inverted_index.during | 77 |
| abstract_inverted_index.enable | 71 |
| abstract_inverted_index.kernel | 148 |
| abstract_inverted_index.layers | 145, 151 |
| abstract_inverted_index.neural | 6 |
| abstract_inverted_index.powder | 60 |
| abstract_inverted_index.rapid, | 86, 235 |
| abstract_inverted_index.sizes. | 149 |
| abstract_inverted_index.tandem | 154 |
| abstract_inverted_index.unseen | 179 |
| abstract_inverted_index.varied | 147 |
| abstract_inverted_index.within | 168 |
| abstract_inverted_index.Fourier | 38 |
| abstract_inverted_index.address | 160 |
| abstract_inverted_index.capture | 156 |
| abstract_inverted_index.exposed | 56, 136 |
| abstract_inverted_index.facets. | 137 |
| abstract_inverted_index.model's | 175 |
| abstract_inverted_index.network | 7 |
| abstract_inverted_index.robust, | 229 |
| abstract_inverted_index.samples | 47 |
| abstract_inverted_index.squared | 208 |
| abstract_inverted_index.stretch | 64 |
| abstract_inverted_index.through | 62 |
| abstract_inverted_index.(diffuse | 35 |
| abstract_inverted_index.accurate | 219 |
| abstract_inverted_index.achieved | 103 |
| abstract_inverted_index.adsorbed | 67, 122 |
| abstract_inverted_index.advanced | 165, 253 |
| abstract_inverted_index.analysis | 18, 88, 238 |
| abstract_inverted_index.approach | 184 |
| abstract_inverted_index.catalyst | 75 |
| abstract_inverted_index.combined | 247 |
| abstract_inverted_index.ensuring | 218 |
| abstract_inverted_index.exposure | 78 |
| abstract_inverted_index.function | 211 |
| abstract_inverted_index.infrared | 22, 37 |
| abstract_inverted_index.learning | 246 |
| abstract_inverted_index.parallel | 142 |
| abstract_inverted_index.precise, | 230 |
| abstract_inverted_index.presents | 2 |
| abstract_inverted_index.reaction | 83 |
| abstract_inverted_index.reactive | 80 |
| abstract_inverted_index.reliable | 221 |
| abstract_inverted_index.spectral | 157 |
| abstract_inverted_index.surfaces | 55 |
| abstract_inverted_index.(infrared | 28 |
| abstract_inverted_index.adaptable | 232 |
| abstract_inverted_index.challenge | 162 |
| abstract_inverted_index.efficient | 216 |
| abstract_inverted_index.enhancing | 173 |
| abstract_inverted_index.features. | 158 |
| abstract_inverted_index.frequency | 65 |
| abstract_inverted_index.improving | 193 |
| abstract_inverted_index.learning, | 217 |
| abstract_inverted_index.measuring | 42 |
| abstract_inverted_index.optimized | 110 |
| abstract_inverted_index.optimizer | 204 |
| abstract_inverted_index.oxidation | 132 |
| abstract_inverted_index.particles | 61 |
| abstract_inverted_index.potential | 243 |
| abstract_inverted_index.provided, | 240 |
| abstract_inverted_index.reference | 43 |
| abstract_inverted_index.required. | 94 |
| abstract_inverted_index.synthetic | 187, 249 |
| abstract_inverted_index.transform | 39 |
| abstract_inverted_index.absorption | 30 |
| abstract_inverted_index.employment | 200 |
| abstract_inverted_index.generating | 186 |
| abstract_inverted_index.generation | 251 |
| abstract_inverted_index.molecules. | 69 |
| abstract_inverted_index.monitoring | 73 |
| abstract_inverted_index.proficient | 115 |
| abstract_inverted_index.reflection | 29, 36 |
| abstract_inverted_index.represents | 11 |
| abstract_inverted_index.techniques | 167 |
| abstract_inverted_index.advancement | 14 |
| abstract_inverted_index.conditions, | 84 |
| abstract_inverted_index.determining | 117 |
| abstract_inverted_index.integrated, | 172 |
| abstract_inverted_index.intensities | 119 |
| abstract_inverted_index.introducing | 224 |
| abstract_inverted_index.orientation | 130 |
| abstract_inverted_index.particular, | 182 |
| abstract_inverted_index.performance | 176, 195 |
| abstract_inverted_index.real‐time | 72 |
| abstract_inverted_index.significant | 13 |
| abstract_inverted_index.architecture | 9 |
| abstract_inverted_index.demonstrated | 97 |
| abstract_inverted_index.incorporates | 141 |
| abstract_inverted_index.instrumental | 191 |
| abstract_inverted_index.modification | 76 |
| abstract_inverted_index.overfitting, | 164 |
| abstract_inverted_index.predictions. | 222 |
| abstract_inverted_index.spectroscopy | 254 |
| abstract_inverted_index.unsupervised | 17, 87, 236 |
| abstract_inverted_index.applications. | 255 |
| abstract_inverted_index.architecture, | 227 |
| abstract_inverted_index.architecture. | 111 |
| abstract_inverted_index.convolutional | 5, 144 |
| abstract_inverted_index.demonstrating | 241 |
| abstract_inverted_index.spectroscopic | 237 |
| abstract_inverted_index.spectroscopy) | 31 |
| abstract_inverted_index.spectroscopy, | 24 |
| abstract_inverted_index.regularization | 166 |
| abstract_inverted_index.spectroscopy). | 40 |
| abstract_inverted_index.characterization | 53 |
| abstract_inverted_index.crystallographic | 129 |
| abstract_inverted_index.single‐crystal | 46 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5064307923 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I102335020, https://openalex.org/I158675288 |
| citation_normalized_percentile.value | 0.34743331 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |