Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy Article Swipe
Christopher C. Price
,
Akash Singh
,
Nathan C. Frey
,
Vivek B. Shenoy
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1126/sciadv.abq5944
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1126/sciadv.abq5944
Small-molecule adsorption energies correlate with energy barriers of catalyzed intermediate reaction steps, determining the dominant microkinetic mechanism. Straining the catalyst can alter adsorption energies and break scaling relationships that inhibit reaction engineering, but identifying desirable strain patterns using density functional theory is intractable because of the high-dimensional search space. We train a graph neural network to predict the adsorption energy response of a catalyst/adsorbate system under a proposed surface strain pattern. The training data are generated by randomly straining and relaxing Cu-based binary alloy catalyst complexes taken from the Open Catalyst Project. The trained model successfully predicts the adsorption energy response for 85% of strains in unseen test data, outperforming ensemble linear baselines. Using ammonia synthesis as an example, we identify Cu-S alloy catalysts as promising candidates for strain engineering. Our approach can locate strain patterns that break adsorption energy scaling relations to improve catalyst performance.
Related Topics
Concepts
Catalysis
Adsorption
Strain (injury)
Scaling
Materials science
Biological system
Density functional theory
Artificial neural network
Computer science
Chemical physics
Chemical engineering
Chemistry
Computational chemistry
Mathematics
Physical chemistry
Artificial intelligence
Organic chemistry
Biology
Engineering
Anatomy
Geometry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1126/sciadv.abq5944
- OA Status
- gold
- Cited By
- 37
- References
- 69
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4310088459
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4310088459Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1126/sciadv.abq5944Digital Object Identifier
- Title
-
Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-23Full publication date if available
- Authors
-
Christopher C. Price, Akash Singh, Nathan C. Frey, Vivek B. ShenoyList of authors in order
- Landing page
-
https://doi.org/10.1126/sciadv.abq5944Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1126/sciadv.abq5944Direct OA link when available
- Concepts
-
Catalysis, Adsorption, Strain (injury), Scaling, Materials science, Biological system, Density functional theory, Artificial neural network, Computer science, Chemical physics, Chemical engineering, Chemistry, Computational chemistry, Mathematics, Physical chemistry, Artificial intelligence, Organic chemistry, Biology, Engineering, Anatomy, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
37Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 19, 2024: 10, 2023: 8Per-year citation counts (last 5 years)
- References (count)
-
69Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4310088459 |
|---|---|
| doi | https://doi.org/10.1126/sciadv.abq5944 |
| ids.doi | https://doi.org/10.1126/sciadv.abq5944 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/36417537 |
| ids.openalex | https://openalex.org/W4310088459 |
| fwci | 2.51003984 |
| type | article |
| title | Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy |
| biblio.issue | 47 |
| biblio.volume | 8 |
| biblio.last_page | eabq5944 |
| biblio.first_page | eabq5944 |
| topics[0].id | https://openalex.org/T12112 |
| topics[0].field.id | https://openalex.org/fields/15 |
| topics[0].field.display_name | Chemical Engineering |
| topics[0].score | 0.9997000098228455 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1503 |
| topics[0].subfield.display_name | Catalysis |
| topics[0].display_name | Ammonia Synthesis and Nitrogen Reduction |
| topics[1].id | https://openalex.org/T11948 |
| topics[1].field.id | https://openalex.org/fields/25 |
| topics[1].field.display_name | Materials Science |
| topics[1].score | 0.9995999932289124 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2505 |
| topics[1].subfield.display_name | Materials Chemistry |
| topics[1].display_name | Machine Learning in Materials Science |
| topics[2].id | https://openalex.org/T10078 |
| topics[2].field.id | https://openalex.org/fields/21 |
| topics[2].field.display_name | Energy |
| topics[2].score | 0.9994999766349792 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2105 |
| topics[2].subfield.display_name | Renewable Energy, Sustainability and the Environment |
| topics[2].display_name | Advanced Photocatalysis Techniques |
| is_xpac | False |
| apc_list.value | 4500 |
| apc_list.currency | USD |
| apc_list.value_usd | 4500 |
| apc_paid.value | 4500 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 4500 |
| concepts[0].id | https://openalex.org/C161790260 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8307643532752991 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q82264 |
| concepts[0].display_name | Catalysis |
| concepts[1].id | https://openalex.org/C150394285 |
| concepts[1].level | 2 |
| concepts[1].score | 0.8112190365791321 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q180254 |
| concepts[1].display_name | Adsorption |
| concepts[2].id | https://openalex.org/C2778022156 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5867709517478943 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q576145 |
| concepts[2].display_name | Strain (injury) |
| concepts[3].id | https://openalex.org/C99844830 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5283185839653015 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q102441924 |
| concepts[3].display_name | Scaling |
| concepts[4].id | https://openalex.org/C192562407 |
| concepts[4].level | 0 |
| concepts[4].score | 0.4898218810558319 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[4].display_name | Materials science |
| concepts[5].id | https://openalex.org/C186060115 |
| concepts[5].level | 1 |
| concepts[5].score | 0.46100494265556335 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q30336093 |
| concepts[5].display_name | Biological system |
| concepts[6].id | https://openalex.org/C152365726 |
| concepts[6].level | 2 |
| concepts[6].score | 0.44053882360458374 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1048589 |
| concepts[6].display_name | Density functional theory |
| concepts[7].id | https://openalex.org/C50644808 |
| concepts[7].level | 2 |
| concepts[7].score | 0.41531771421432495 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[7].display_name | Artificial neural network |
| concepts[8].id | https://openalex.org/C41008148 |
| concepts[8].level | 0 |
| concepts[8].score | 0.3961560130119324 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[8].display_name | Computer science |
| concepts[9].id | https://openalex.org/C159467904 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3672288656234741 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q2001702 |
| concepts[9].display_name | Chemical physics |
| concepts[10].id | https://openalex.org/C42360764 |
| concepts[10].level | 1 |
| concepts[10].score | 0.3659537732601166 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q83588 |
| concepts[10].display_name | Chemical engineering |
| concepts[11].id | https://openalex.org/C185592680 |
| concepts[11].level | 0 |
| concepts[11].score | 0.2978413701057434 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[11].display_name | Chemistry |
| concepts[12].id | https://openalex.org/C147597530 |
| concepts[12].level | 1 |
| concepts[12].score | 0.25074881315231323 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q369472 |
| concepts[12].display_name | Computational chemistry |
| concepts[13].id | https://openalex.org/C33923547 |
| concepts[13].level | 0 |
| concepts[13].score | 0.20486056804656982 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[13].display_name | Mathematics |
| concepts[14].id | https://openalex.org/C147789679 |
| concepts[14].level | 1 |
| concepts[14].score | 0.19900482892990112 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11372 |
| concepts[14].display_name | Physical chemistry |
| concepts[15].id | https://openalex.org/C154945302 |
| concepts[15].level | 1 |
| concepts[15].score | 0.1384216547012329 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[15].display_name | Artificial intelligence |
| concepts[16].id | https://openalex.org/C178790620 |
| concepts[16].level | 1 |
| concepts[16].score | 0.10659146308898926 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q11351 |
| concepts[16].display_name | Organic chemistry |
| concepts[17].id | https://openalex.org/C86803240 |
| concepts[17].level | 0 |
| concepts[17].score | 0.08254456520080566 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[17].display_name | Biology |
| concepts[18].id | https://openalex.org/C127413603 |
| concepts[18].level | 0 |
| concepts[18].score | 0.07828882336616516 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[18].display_name | Engineering |
| concepts[19].id | https://openalex.org/C105702510 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q514 |
| concepts[19].display_name | Anatomy |
| concepts[20].id | https://openalex.org/C2524010 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[20].display_name | Geometry |
| keywords[0].id | https://openalex.org/keywords/catalysis |
| keywords[0].score | 0.8307643532752991 |
| keywords[0].display_name | Catalysis |
| keywords[1].id | https://openalex.org/keywords/adsorption |
| keywords[1].score | 0.8112190365791321 |
| keywords[1].display_name | Adsorption |
| keywords[2].id | https://openalex.org/keywords/strain |
| keywords[2].score | 0.5867709517478943 |
| keywords[2].display_name | Strain (injury) |
| keywords[3].id | https://openalex.org/keywords/scaling |
| keywords[3].score | 0.5283185839653015 |
| keywords[3].display_name | Scaling |
| keywords[4].id | https://openalex.org/keywords/materials-science |
| keywords[4].score | 0.4898218810558319 |
| keywords[4].display_name | Materials science |
| keywords[5].id | https://openalex.org/keywords/biological-system |
| keywords[5].score | 0.46100494265556335 |
| keywords[5].display_name | Biological system |
| keywords[6].id | https://openalex.org/keywords/density-functional-theory |
| keywords[6].score | 0.44053882360458374 |
| keywords[6].display_name | Density functional theory |
| keywords[7].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[7].score | 0.41531771421432495 |
| keywords[7].display_name | Artificial neural network |
| keywords[8].id | https://openalex.org/keywords/computer-science |
| keywords[8].score | 0.3961560130119324 |
| keywords[8].display_name | Computer science |
| keywords[9].id | https://openalex.org/keywords/chemical-physics |
| keywords[9].score | 0.3672288656234741 |
| keywords[9].display_name | Chemical physics |
| keywords[10].id | https://openalex.org/keywords/chemical-engineering |
| keywords[10].score | 0.3659537732601166 |
| keywords[10].display_name | Chemical engineering |
| keywords[11].id | https://openalex.org/keywords/chemistry |
| keywords[11].score | 0.2978413701057434 |
| keywords[11].display_name | Chemistry |
| keywords[12].id | https://openalex.org/keywords/computational-chemistry |
| keywords[12].score | 0.25074881315231323 |
| keywords[12].display_name | Computational chemistry |
| keywords[13].id | https://openalex.org/keywords/mathematics |
| keywords[13].score | 0.20486056804656982 |
| keywords[13].display_name | Mathematics |
| keywords[14].id | https://openalex.org/keywords/physical-chemistry |
| keywords[14].score | 0.19900482892990112 |
| keywords[14].display_name | Physical chemistry |
| keywords[15].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[15].score | 0.1384216547012329 |
| keywords[15].display_name | Artificial intelligence |
| keywords[16].id | https://openalex.org/keywords/organic-chemistry |
| keywords[16].score | 0.10659146308898926 |
| keywords[16].display_name | Organic chemistry |
| keywords[17].id | https://openalex.org/keywords/biology |
| keywords[17].score | 0.08254456520080566 |
| keywords[17].display_name | Biology |
| keywords[18].id | https://openalex.org/keywords/engineering |
| keywords[18].score | 0.07828882336616516 |
| keywords[18].display_name | Engineering |
| language | en |
| locations[0].id | doi:10.1126/sciadv.abq5944 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2737427234 |
| locations[0].source.issn | 2375-2548 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2375-2548 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Science Advances |
| locations[0].source.host_organization | https://openalex.org/P4310315823 |
| locations[0].source.host_organization_name | American Association for the Advancement of Science |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310315823 |
| locations[0].source.host_organization_lineage_names | American Association for the Advancement of Science |
| locations[0].license | cc-by-nc |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Science Advances |
| locations[0].landing_page_url | https://doi.org/10.1126/sciadv.abq5944 |
| locations[1].id | pmid:36417537 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Science advances |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/36417537 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:9683700 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | other-oa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/other-oa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Sci Adv |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/9683700 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5044676254 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-4702-5817 |
| authorships[0].author.display_name | Christopher C. Price |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. |
| authorships[0].institutions[0].id | https://openalex.org/I79576946 |
| authorships[0].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | University of Pennsylvania |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Christopher C. Price |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. |
| authorships[1].author.id | https://openalex.org/A5043199660 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-0202-7170 |
| authorships[1].author.display_name | Akash Singh |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. |
| authorships[1].institutions[0].id | https://openalex.org/I79576946 |
| authorships[1].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | University of Pennsylvania |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Akash Singh |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. |
| authorships[2].author.id | https://openalex.org/A5090160831 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-5291-6131 |
| authorships[2].author.display_name | Nathan C. Frey |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210122954, https://openalex.org/I63966007 |
| authorships[2].affiliations[0].raw_affiliation_string | Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA 02421, USA. |
| authorships[2].institutions[0].id | https://openalex.org/I4210122954 |
| authorships[2].institutions[0].ror | https://ror.org/022z6jk58 |
| authorships[2].institutions[0].type | facility |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210122954, https://openalex.org/I63966007 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | MIT Lincoln Laboratory |
| authorships[2].institutions[1].id | https://openalex.org/I63966007 |
| authorships[2].institutions[1].ror | https://ror.org/042nb2s44 |
| authorships[2].institutions[1].type | education |
| authorships[2].institutions[1].lineage | https://openalex.org/I63966007 |
| authorships[2].institutions[1].country_code | US |
| authorships[2].institutions[1].display_name | Massachusetts Institute of Technology |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Nathan C. Frey |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA 02421, USA. |
| authorships[3].author.id | https://openalex.org/A5011906405 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-2645-1016 |
| authorships[3].author.display_name | Vivek B. Shenoy |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. |
| authorships[3].institutions[0].id | https://openalex.org/I79576946 |
| authorships[3].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | University of Pennsylvania |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Vivek B. Shenoy |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1126/sciadv.abq5944 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12112 |
| primary_topic.field.id | https://openalex.org/fields/15 |
| primary_topic.field.display_name | Chemical Engineering |
| primary_topic.score | 0.9997000098228455 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1503 |
| primary_topic.subfield.display_name | Catalysis |
| primary_topic.display_name | Ammonia Synthesis and Nitrogen Reduction |
| related_works | https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W2080164668, https://openalex.org/W2352393472, https://openalex.org/W3092548534, https://openalex.org/W3034058915, https://openalex.org/W2520679681, https://openalex.org/W2049352286, https://openalex.org/W2216249513, https://openalex.org/W2850630682 |
| cited_by_count | 37 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 19 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 10 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 8 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1126/sciadv.abq5944 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2737427234 |
| best_oa_location.source.issn | 2375-2548 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2375-2548 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Science Advances |
| best_oa_location.source.host_organization | https://openalex.org/P4310315823 |
| best_oa_location.source.host_organization_name | American Association for the Advancement of Science |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310315823 |
| best_oa_location.source.host_organization_lineage_names | American Association for the Advancement of Science |
| best_oa_location.license | cc-by-nc |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Science Advances |
| best_oa_location.landing_page_url | https://doi.org/10.1126/sciadv.abq5944 |
| primary_location.id | doi:10.1126/sciadv.abq5944 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2737427234 |
| primary_location.source.issn | 2375-2548 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2375-2548 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Science Advances |
| primary_location.source.host_organization | https://openalex.org/P4310315823 |
| primary_location.source.host_organization_name | American Association for the Advancement of Science |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310315823 |
| primary_location.source.host_organization_lineage_names | American Association for the Advancement of Science |
| primary_location.license | cc-by-nc |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Science Advances |
| primary_location.landing_page_url | https://doi.org/10.1126/sciadv.abq5944 |
| publication_date | 2022-11-23 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2315837940, https://openalex.org/W2078236179, https://openalex.org/W2056506009, https://openalex.org/W2073675832, https://openalex.org/W2084865056, https://openalex.org/W2800558735, https://openalex.org/W2119715237, https://openalex.org/W2035007577, https://openalex.org/W2946117300, https://openalex.org/W2915336924, https://openalex.org/W3202578456, https://openalex.org/W2032364562, https://openalex.org/W2597761442, https://openalex.org/W566353445, https://openalex.org/W2990956209, https://openalex.org/W2007740449, https://openalex.org/W2341535801, https://openalex.org/W2010188612, https://openalex.org/W2797745778, https://openalex.org/W2982215879, https://openalex.org/W2334851015, https://openalex.org/W2270127846, https://openalex.org/W2116106887, https://openalex.org/W2760442154, https://openalex.org/W3139031847, https://openalex.org/W2589457549, https://openalex.org/W1884797747, https://openalex.org/W2888521436, https://openalex.org/W2335066618, https://openalex.org/W2324780663, https://openalex.org/W3200048121, https://openalex.org/W2913594191, https://openalex.org/W3170862190, https://openalex.org/W2947139271, https://openalex.org/W3093999435, https://openalex.org/W3088988053, https://openalex.org/W2949095042, https://openalex.org/W2766856748, https://openalex.org/W3043238520, https://openalex.org/W3125542198, https://openalex.org/W3025104221, https://openalex.org/W2083850317, https://openalex.org/W3179411330, https://openalex.org/W3111304214, https://openalex.org/W3019011361, https://openalex.org/W2990354746, https://openalex.org/W2558907208, https://openalex.org/W2920912088, https://openalex.org/W3009486424, https://openalex.org/W3196960606, https://openalex.org/W3083878370, https://openalex.org/W3100541053, https://openalex.org/W2162393583, https://openalex.org/W3113477274, https://openalex.org/W3144721481, https://openalex.org/W2065251521, https://openalex.org/W4308917845, https://openalex.org/W2093771834, https://openalex.org/W2799692084, https://openalex.org/W4200331706, https://openalex.org/W2007395042, https://openalex.org/W2087698390, https://openalex.org/W1970127494, https://openalex.org/W1981368803, https://openalex.org/W2092157292, https://openalex.org/W2096747776, https://openalex.org/W3084354688, https://openalex.org/W4246301683, https://openalex.org/W3103736477 |
| referenced_works_count | 69 |
| abstract_inverted_index.a | 51, 62, 66 |
| abstract_inverted_index.We | 49 |
| abstract_inverted_index.an | 117 |
| abstract_inverted_index.as | 116, 124 |
| abstract_inverted_index.by | 76 |
| abstract_inverted_index.in | 105 |
| abstract_inverted_index.is | 41 |
| abstract_inverted_index.of | 7, 44, 61, 103 |
| abstract_inverted_index.to | 55, 142 |
| abstract_inverted_index.we | 119 |
| abstract_inverted_index.85% | 102 |
| abstract_inverted_index.Our | 130 |
| abstract_inverted_index.The | 71, 92 |
| abstract_inverted_index.and | 24, 79 |
| abstract_inverted_index.are | 74 |
| abstract_inverted_index.but | 32 |
| abstract_inverted_index.can | 20, 132 |
| abstract_inverted_index.for | 101, 127 |
| abstract_inverted_index.the | 13, 18, 45, 57, 88, 97 |
| abstract_inverted_index.Cu-S | 121 |
| abstract_inverted_index.Open | 89 |
| abstract_inverted_index.data | 73 |
| abstract_inverted_index.from | 87 |
| abstract_inverted_index.test | 107 |
| abstract_inverted_index.that | 28, 136 |
| abstract_inverted_index.with | 4 |
| abstract_inverted_index.Using | 113 |
| abstract_inverted_index.alloy | 83, 122 |
| abstract_inverted_index.alter | 21 |
| abstract_inverted_index.break | 25, 137 |
| abstract_inverted_index.data, | 108 |
| abstract_inverted_index.graph | 52 |
| abstract_inverted_index.model | 94 |
| abstract_inverted_index.taken | 86 |
| abstract_inverted_index.train | 50 |
| abstract_inverted_index.under | 65 |
| abstract_inverted_index.using | 37 |
| abstract_inverted_index.binary | 82 |
| abstract_inverted_index.energy | 5, 59, 99, 139 |
| abstract_inverted_index.linear | 111 |
| abstract_inverted_index.locate | 133 |
| abstract_inverted_index.neural | 53 |
| abstract_inverted_index.search | 47 |
| abstract_inverted_index.space. | 48 |
| abstract_inverted_index.steps, | 11 |
| abstract_inverted_index.strain | 35, 69, 128, 134 |
| abstract_inverted_index.system | 64 |
| abstract_inverted_index.theory | 40 |
| abstract_inverted_index.unseen | 106 |
| abstract_inverted_index.ammonia | 114 |
| abstract_inverted_index.because | 43 |
| abstract_inverted_index.density | 38 |
| abstract_inverted_index.improve | 143 |
| abstract_inverted_index.inhibit | 29 |
| abstract_inverted_index.network | 54 |
| abstract_inverted_index.predict | 56 |
| abstract_inverted_index.scaling | 26, 140 |
| abstract_inverted_index.strains | 104 |
| abstract_inverted_index.surface | 68 |
| abstract_inverted_index.trained | 93 |
| abstract_inverted_index.Catalyst | 90 |
| abstract_inverted_index.Cu-based | 81 |
| abstract_inverted_index.Project. | 91 |
| abstract_inverted_index.approach | 131 |
| abstract_inverted_index.barriers | 6 |
| abstract_inverted_index.catalyst | 19, 84, 144 |
| abstract_inverted_index.dominant | 14 |
| abstract_inverted_index.energies | 2, 23 |
| abstract_inverted_index.ensemble | 110 |
| abstract_inverted_index.example, | 118 |
| abstract_inverted_index.identify | 120 |
| abstract_inverted_index.pattern. | 70 |
| abstract_inverted_index.patterns | 36, 135 |
| abstract_inverted_index.predicts | 96 |
| abstract_inverted_index.proposed | 67 |
| abstract_inverted_index.randomly | 77 |
| abstract_inverted_index.reaction | 10, 30 |
| abstract_inverted_index.relaxing | 80 |
| abstract_inverted_index.response | 60, 100 |
| abstract_inverted_index.training | 72 |
| abstract_inverted_index.Straining | 17 |
| abstract_inverted_index.catalysts | 123 |
| abstract_inverted_index.catalyzed | 8 |
| abstract_inverted_index.complexes | 85 |
| abstract_inverted_index.correlate | 3 |
| abstract_inverted_index.desirable | 34 |
| abstract_inverted_index.generated | 75 |
| abstract_inverted_index.promising | 125 |
| abstract_inverted_index.relations | 141 |
| abstract_inverted_index.straining | 78 |
| abstract_inverted_index.synthesis | 115 |
| abstract_inverted_index.adsorption | 1, 22, 58, 98, 138 |
| abstract_inverted_index.baselines. | 112 |
| abstract_inverted_index.candidates | 126 |
| abstract_inverted_index.functional | 39 |
| abstract_inverted_index.mechanism. | 16 |
| abstract_inverted_index.determining | 12 |
| abstract_inverted_index.identifying | 33 |
| abstract_inverted_index.intractable | 42 |
| abstract_inverted_index.engineering, | 31 |
| abstract_inverted_index.engineering. | 129 |
| abstract_inverted_index.intermediate | 9 |
| abstract_inverted_index.microkinetic | 15 |
| abstract_inverted_index.performance. | 145 |
| abstract_inverted_index.successfully | 95 |
| abstract_inverted_index.outperforming | 109 |
| abstract_inverted_index.relationships | 27 |
| abstract_inverted_index.Small-molecule | 0 |
| abstract_inverted_index.high-dimensional | 46 |
| abstract_inverted_index.catalyst/adsorbate | 63 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5011906405 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I79576946 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8899999856948853 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.87586939 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |