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Record W4414036137 · doi:10.1021/acs.jpcc.5c04615

Time-Resolved Mapping of Charge Carrier Dynamics and Defect-Mediated Migration Barriers in TiO<sub>2</sub>

2025· article· en· W4414036137 on OpenAlexafffund
Bugrahan Guner, Mohammad Safikhani-Mahmoudi, Omur E. Dagdeviren

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2025
Typearticle
Languageen
FieldMaterials Science
TopicElectronic and Structural Properties of Oxides
Canadian institutionsÉcole de Technologie Supérieure
FundersFonds de recherche du Québec – Nature et technologiesCanada Economic Development for Quebec RegionsNatural Sciences and Engineering Research Council of CanadaÉcole de technologie supérieure
KeywordsDynamics (music)Charge (physics)Materials scienceCharge carrierChemical physicsEngineering physicsNanotechnologyStatistical physicsPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

The spatiotemporal behavior of charge carriers in metal oxides governs their performance in photocatalytic and electronic applications, yet remains poorly understood at the nanoscale. Here, we use time-resolved atomic force microscopy (TR-AFM) to map charge transport in TiO 2 under controlled surface irradiation and thermal conditions. Our measurements reveal pronounced spatial variability in carrier migration times and activation energies, driven by local defect landscapes. Irradiation-induced surface defects are found to lower migration barriers, enhancing carrier relaxation. Notably, we observe electrostatic memory effects, with residual electric fields modulating migration dynamics across hundreds of nanometers. Temperature-dependent studies further reveal a tunable interaction between defect-mediated migration and thermal activation. These findings provide direct insight into nanoscale charge transport in TiO 2 and highlight the role of defect engineering and thermal management in optimizing oxide-based devices for energy conversion and sensing.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.014
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.201
Teacher spread0.197 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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