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Record W4409994271 · doi:10.1103/physrevx.15.021035

Strongly Interacting, Two-Dimensional, Dipolar Spin Ensembles in (111)-Oriented Diamond

2025· article· en· W4409994271 on OpenAlexfundno aff
Lillian B. Hughes, Simon A. Meynell, Weijie Wu, Shreyas Parthasarathy, Lingjie Chen, Zhiran Zhang, Zilin Wang, Emily J. Davis, Kunal Mukherjee, Norman Y. Yao, Ania C. Bleszynski Jayich

Bibliographic record

VenuePhysical Review X · 2025
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsnot available
FundersDivision of Materials ResearchArmy Research OfficeNatural Sciences and Engineering Research Council of CanadaCenter for Ultracold Atoms, Massachusetts Institute of TechnologyCalifornia NanoSystems InstituteUniversity of California, Santa BarbaraMultidisciplinary University Research InitiativeMaterials Research Science and Engineering Center, Harvard UniversityNational Defense Science and Engineering GraduateU.S. Department of EnergyU.S. Department of DefenseNational Science Foundation
KeywordsDiamondSpin (aerodynamics)DipolePhysicsCondensed matter physicsChemical physicsMaterials scienceQuantum mechanics

Abstract

fetched live from OpenAlex

Systems of spins with strong dipolar interactions and controlled dimensionality enable new explorations in quantum sensing and simulation. In this work, we investigate the creation of strong dipolar interactions in a two-dimensional ensemble of nitrogen-vacancy (NV) centers generated via plasma-enhanced chemical vapor deposition on (111)-oriented diamond substrates. We find that diamond growth on the (111) plane yields high incorporation of spins, both nitrogen and NV centers, where the density of the latter is tunable via the miscut of the diamond substrate. Our process allows us to form dense, preferentially aligned, 2D NV ensembles with volume-normalized ac sensitivity down to <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mrow> <a:msub> <a:mrow> <a:mi>η</a:mi> </a:mrow> <a:mrow> <a:mi>ac</a:mi> </a:mrow> </a:msub> <a:mo>=</a:mo> <a:mn>810</a:mn> <a:mtext> </a:mtext> <a:mtext> </a:mtext> <a:mi>pT</a:mi> <a:mtext> </a:mtext> <a:mi mathvariant="normal">μ</a:mi> <a:msup> <a:mrow> <a:mi mathvariant="normal">m</a:mi> </a:mrow> <a:mrow> <a:mn>3</a:mn> <a:mo>/</a:mo> <a:mn>2</a:mn> </a:mrow> </a:msup> <a:mtext> </a:mtext> <a:msup> <a:mrow> <a:mi>Hz</a:mi> </a:mrow> <a:mrow> <a:mo>−</a:mo> <a:mn>1</a:mn> <a:mo>/</a:mo> <a:mn>2</a:mn> </a:mrow> </a:msup> </a:mrow> </a:math> . Furthermore, we show that (111) affords maximally positive dipolar interactions among a 2D NV ensemble, which is crucial for leveraging dipolar-driven entanglement schemes and exploring new interacting spin physics.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.055
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.363
Teacher spread0.349 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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