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Record W4213192013 · doi:10.1080/21663831.2022.2029779

Nanomaterials by severe plastic deformation: review of historical developments and recent advances

2022· article· en· W4213192013 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials Research Letters · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersJapan Society for the Promotion of ScienceRussian and Eurasian Centre, St. Antony's College, University of OxfordCore Research for Evolutional Science and TechnologyNational Science Foundation of Sri LankaMinistry of Education, Culture, Sports, Science and TechnologyRussian Science FoundationMinistry of Education and Science of the Russian FederationCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorConselho Nacional de Desenvolvimento Científico e TecnológicoNational Natural Science Foundation of ChinaFundação de Amparo à Pesquisa do Estado de São PauloDeutsche ForschungsgemeinschaftNational Science FoundationIowa State UniversityAgence Nationale de la Recherche
KeywordsSevere plastic deformationMaterials scienceComposite materialElectron backscatter diffractionSuperplasticityExtrusionAccumulative roll bondingEqual channel angular extrusionMetallurgyPressingMicrostructure

Abstract

fetched live from OpenAlex

Severe plastic deformation (SPD) is effective in producing bulk ultrafine-grained and nanostructured materials with large densities of lattice defects. This field, also known as NanoSPD, experienced a significant progress within the past two decades. Beside classic SPD methods such as high-pressure torsion, equal-channel angular pressing, accumulative roll-bonding, twist extrusion, and multi-directional forging, various continuous techniques were introduced to produce upscaled samples. Moreover, numerous alloys, glasses, semiconductors, ceramics, polymers, and their composites were processed. The SPD methods were used to synthesize new materials or to stabilize metastable phases with advanced mechanical and functional properties. High strength combined with high ductility, low/room-temperature superplasticity, creep resistance, hydrogen storage, photocatalytic hydrogen production, photocatalytic CO2 conversion, superconductivity, thermoelectric performance, radiation resistance, corrosion resistance, and biocompatibility are some highlighted properties of SPD-processed materials. This article reviews recent advances in the NanoSPD field and provides a brief history regarding its progress from the ancient times to modernity. Abbreviations: ARB: Accumulative Roll-Bonding; BCC: Body-Centered Cubic; DAC: Diamond Anvil Cell; EBSD: Electron Backscatter Diffraction; ECAP: Equal-Channel Angular Pressing (Extrusion); FCC: Face-Centered Cubic; FEM: Finite Element Method; FSP: Friction Stir Processing; HCP: Hexagonal Close-Packed; HPT: High-Pressure Torsion; HPTT: High-Pressure Tube Twisting; MDF: Multi-Directional (-Axial) Forging; NanoSPD: Nanomaterials by Severe Plastic Deformation; SDAC: Shear (Rotational) Diamond Anvil Cell; SEM: Scanning Electron Microscopy; SMAT: Surface Mechanical Attrition Treatment; SPD: Severe Plastic Deformation; TE: Twist Extrusion; TEM: Transmission Electron Microscopy; UFG: Ultrafine Grained. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.293
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it