A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO3/La2NiO4 Article Swipe

View

Guang-Chen Liu , Songge Yang , Yu Zhong ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1016/j.mtphys.2025.101940

Related Topics

Materials Science

Artificial Intelligence

Machine Learning

Computer Science

Active Learning (Machine Learning)

User Interface

Algorithm

Support Vector Machine

Concepts

Materials science Lattice (music) Artificial intelligence Interface (matter) Machine learning Computer science Active learning (machine learning) Computational learning theory User interface Interface design Algorithm Support vector machine

Metadata

Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.mtphys.2025.101940
OA Status: hybrid
References: 39
OpenAlex ID: https://openalex.org/W7105851665

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W7105851665

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.1016/j.mtphys.2025.101940

Digital Object Identifier
Title: A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO3/La2NiO4

Work title
Type: article

OpenAlex work type
Language: en

Primary language
Publication year: 2025

Year of publication
Publication date: 2025-11-17

Full publication date if available
Authors: Guang-Chen Liu, Songge Yang, Yu Zhong

List of authors in order
Landing page: https://doi.org/10.1016/j.mtphys.2025.101940

Publisher landing page
Open access: Yes

Whether a free full text is available
OA status: hybrid

Open access status per OpenAlex
OA URL: https://doi.org/10.1016/j.mtphys.2025.101940

Direct OA link when available
Concepts: Materials science, Lattice (music), Artificial intelligence, Interface (matter), Machine learning, Computer science, Active learning (machine learning), Computational learning theory, User interface, Interface design, Algorithm, Support vector machine

Top concepts (fields/topics) attached by OpenAlex
Cited by: 0

Total citation count in OpenAlex
References (count): 39

Number of works referenced by this work

Full payload

id	https://openalex.org/W7105851665
doi	https://doi.org/10.1016/j.mtphys.2025.101940
ids.doi	https://doi.org/10.1016/j.mtphys.2025.101940
ids.openalex	https://openalex.org/W7105851665
fwci	0.0
type	article
title	A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO3/La2NiO4
biblio.issue
biblio.volume	59
biblio.last_page	101940
biblio.first_page	101940
topics[0].id	https://openalex.org/T11948
topics[0].field.id	https://openalex.org/fields/25
topics[0].field.display_name	Materials Science
topics[0].score	0.3998958170413971
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	Machine Learning in Materials Science
topics[1].id	https://openalex.org/T12046
topics[1].field.id	https://openalex.org/fields/25
topics[1].field.display_name	Materials Science
topics[1].score	0.10940802842378616
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	MXene and MAX Phase Materials
topics[2].id	https://openalex.org/T12557
topics[2].field.id	https://openalex.org/fields/16
topics[2].field.display_name	Chemistry
topics[2].score	0.08182866126298904
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/1604
topics[2].subfield.display_name	Inorganic Chemistry
topics[2].display_name	Inorganic Chemistry and Materials
is_xpac	False
apc_list.value	4250
apc_list.currency	USD
apc_list.value_usd	4250
apc_paid.value	4250
apc_paid.currency	USD
apc_paid.value_usd	4250
concepts[0].id	https://openalex.org/C192562407
concepts[0].level	0
concepts[0].score	0.6950273513793945
concepts[0].wikidata	https://www.wikidata.org/wiki/Q228736
concepts[0].display_name	Materials science
concepts[1].id	https://openalex.org/C2781204021
concepts[1].level	2
concepts[1].score	0.5637893676757812
concepts[1].wikidata	https://www.wikidata.org/wiki/Q6497091
concepts[1].display_name	Lattice (music)
concepts[2].id	https://openalex.org/C154945302
concepts[2].level	1
concepts[2].score	0.4857484698295593
concepts[2].wikidata	https://www.wikidata.org/wiki/Q11660
concepts[2].display_name	Artificial intelligence
concepts[3].id	https://openalex.org/C113843644
concepts[3].level	4
concepts[3].score	0.4806714653968811
concepts[3].wikidata	https://www.wikidata.org/wiki/Q901882
concepts[3].display_name	Interface (matter)
concepts[4].id	https://openalex.org/C119857082
concepts[4].level	1
concepts[4].score	0.4617341458797455
concepts[4].wikidata	https://www.wikidata.org/wiki/Q2539
concepts[4].display_name	Machine learning
concepts[5].id	https://openalex.org/C41008148
concepts[5].level	0
concepts[5].score	0.39581403136253357
concepts[5].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[5].display_name	Computer science
concepts[6].id	https://openalex.org/C77967617
concepts[6].level	2
concepts[6].score	0.3278528153896332
concepts[6].wikidata	https://www.wikidata.org/wiki/Q4677561
concepts[6].display_name	Active learning (machine learning)
concepts[7].id	https://openalex.org/C50292564
concepts[7].level	3
concepts[7].score	0.3120728135108948
concepts[7].wikidata	https://www.wikidata.org/wiki/Q2462783
concepts[7].display_name	Computational learning theory
concepts[8].id	https://openalex.org/C89505385
concepts[8].level	2
concepts[8].score	0.30269065499305725
concepts[8].wikidata	https://www.wikidata.org/wiki/Q47146
concepts[8].display_name	User interface
concepts[9].id	https://openalex.org/C139366241
concepts[9].level	2
concepts[9].score	0.2716854512691498
concepts[9].wikidata	https://www.wikidata.org/wiki/Q135707
concepts[9].display_name	Interface design
concepts[10].id	https://openalex.org/C11413529
concepts[10].level	1
concepts[10].score	0.26797330379486084
concepts[10].wikidata	https://www.wikidata.org/wiki/Q8366
concepts[10].display_name	Algorithm
concepts[11].id	https://openalex.org/C12267149
concepts[11].level	2
concepts[11].score	0.25335487723350525
concepts[11].wikidata	https://www.wikidata.org/wiki/Q282453
concepts[11].display_name	Support vector machine
keywords[0].id	https://openalex.org/keywords/lattice
keywords[0].score	0.5637893676757812
keywords[0].display_name	Lattice (music)
keywords[1].id	https://openalex.org/keywords/interface
keywords[1].score	0.4806714653968811
keywords[1].display_name	Interface (matter)
keywords[2].id	https://openalex.org/keywords/active-learning
keywords[2].score	0.3278528153896332
keywords[2].display_name	Active learning (machine learning)
keywords[3].id	https://openalex.org/keywords/computational-learning-theory
keywords[3].score	0.3120728135108948
keywords[3].display_name	Computational learning theory
keywords[4].id	https://openalex.org/keywords/user-interface
keywords[4].score	0.30269065499305725
keywords[4].display_name	User interface
language	en
locations[0].id	doi:10.1016/j.mtphys.2025.101940
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S2898609469
locations[0].source.issn	2542-5293
locations[0].source.type	journal
locations[0].source.is_oa	False
locations[0].source.issn_l	2542-5293
locations[0].source.is_core	True
locations[0].source.is_in_doaj	False
locations[0].source.display_name	Materials Today Physics
locations[0].source.host_organization	https://openalex.org/P4310320990
locations[0].source.host_organization_name	Elsevier BV
locations[0].source.host_organization_lineage	https://openalex.org/P4310320990
locations[0].license	cc-by
locations[0].pdf_url
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	Materials Today Physics
locations[0].landing_page_url	https://doi.org/10.1016/j.mtphys.2025.101940
indexed_in	crossref
authorships[0].author.id	https://openalex.org/A2153628671
authorships[0].author.orcid	https://orcid.org/0000-0001-7569-1510
authorships[0].author.display_name	Guang-Chen Liu
authorships[0].author_position	first
authorships[0].raw_author_name	Guangchen Liu
authorships[0].is_corresponding	True
authorships[1].author.id	https://openalex.org/A2224830399
authorships[1].author.orcid	https://orcid.org/0000-0001-8768-9311
authorships[1].author.display_name	Songge Yang
authorships[1].author_position	middle
authorships[1].raw_author_name	Songge Yang
authorships[1].is_corresponding	False
authorships[2].author.id	https://openalex.org/A2026209636
authorships[2].author.orcid	https://orcid.org/0000-0001-5428-1774
authorships[2].author.display_name	Yu Zhong
authorships[2].author_position	last
authorships[2].raw_author_name	Yu Zhong
authorships[2].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/10.1016/j.mtphys.2025.101940
open_access.oa_status	hybrid
open_access.any_repository_has_fulltext	False
created_date	2025-11-17T00:00:00
display_name	A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO3/La2NiO4
has_fulltext	False
is_retracted	False
updated_date	2025-11-18T23:42:31.664661
primary_topic.id	https://openalex.org/T11948
primary_topic.field.id	https://openalex.org/fields/25
primary_topic.field.display_name	Materials Science
primary_topic.score	0.3998958170413971
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	Machine Learning in Materials Science
cited_by_count	0
locations_count	1
best_oa_location.id	doi:10.1016/j.mtphys.2025.101940
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S2898609469
best_oa_location.source.issn	2542-5293
best_oa_location.source.type	journal
best_oa_location.source.is_oa	False
best_oa_location.source.issn_l	2542-5293
best_oa_location.source.is_core	True
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	Materials Today Physics
best_oa_location.source.host_organization	https://openalex.org/P4310320990
best_oa_location.source.host_organization_name	Elsevier BV
best_oa_location.source.host_organization_lineage	https://openalex.org/P4310320990
best_oa_location.license	cc-by
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
best_oa_location.is_accepted	True
best_oa_location.is_published	True
best_oa_location.raw_source_name	Materials Today Physics
best_oa_location.landing_page_url	https://doi.org/10.1016/j.mtphys.2025.101940
primary_location.id	doi:10.1016/j.mtphys.2025.101940
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S2898609469
primary_location.source.issn	2542-5293
primary_location.source.type	journal
primary_location.source.is_oa	False
primary_location.source.issn_l	2542-5293
primary_location.source.is_core	True
primary_location.source.is_in_doaj	False
primary_location.source.display_name	Materials Today Physics
primary_location.source.host_organization	https://openalex.org/P4310320990
primary_location.source.host_organization_name	Elsevier BV
primary_location.source.host_organization_lineage	https://openalex.org/P4310320990
primary_location.license	cc-by
primary_location.pdf_url
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	Materials Today Physics
primary_location.landing_page_url	https://doi.org/10.1016/j.mtphys.2025.101940
publication_date	2025-11-17
publication_year	2025
referenced_works	https://openalex.org/W3129420155, https://openalex.org/W2046746459, https://openalex.org/W2978461098, https://openalex.org/W2807962003, https://openalex.org/W2037520782, https://openalex.org/W2055100431, https://openalex.org/W2740598477, https://openalex.org/W2063313748, https://openalex.org/W3041512563, https://openalex.org/W4200464202, https://openalex.org/W4364381813, https://openalex.org/W2963339823, https://openalex.org/W4205426733, https://openalex.org/W2956468808, https://openalex.org/W2886026382, https://openalex.org/W2749006386, https://openalex.org/W2980888952, https://openalex.org/W3035012408, https://openalex.org/W2788484525, https://openalex.org/W4282041110, https://openalex.org/W2775708988, https://openalex.org/W2778051509, https://openalex.org/W2541404351, https://openalex.org/W4310135808, https://openalex.org/W2017591438, https://openalex.org/W4377263839, https://openalex.org/W2057671148, https://openalex.org/W2097731891, https://openalex.org/W2090608158, https://openalex.org/W2112383255, https://openalex.org/W2083287340, https://openalex.org/W2051434435, https://openalex.org/W2502655619, https://openalex.org/W2949676527, https://openalex.org/W2010289393, https://openalex.org/W2484171837, https://openalex.org/W2081741271, https://openalex.org/W1991922600, https://openalex.org/W2113975159
referenced_works_count	39
abstract_inverted_index
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	3
citation_normalized_percentile.value	0.6750882
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False