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Record W4411640082 · doi:10.1109/jlt.2025.3583258

Improved NPIN Junctions for 100 GHz InP Mach-Zehnder Modulators

2025· article· en· W4411640082 on OpenAlexafffund
Gavin P. Forcade, S. Schaefer, Tulasi Marini, Ronald Millett, Karin Hinzer, Kelvin Prosyk

Bibliographic record

VenueJournal of Lightwave Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsCiena (Canada)University of Ottawa
FundersMitacs
KeywordsMach–Zehnder interferometerOptoelectronicsIntegrated opticsOpticsMaterials scienceOptical communicationPhysicsTelecommunicationsInterferometryEngineering

Abstract

fetched live from OpenAlex

High-bandwidth (>100 GHz) and compact indium phosphide Mach-Zehnder modulators with npin junctions, designed for low contact resistance, can experience parasitic photocurrent self-amplification, leading to unpredictable performance. This work introduces a design modification to address self-amplification by inserting a new n-doped material at the np-junction. This material has a lower conduction-bandenergy-minimum than the neighboring layers, thereby increasing the barrier to electron flow across the npin junction. Mach-Zehnder modulators fabricated with this modification demonstrate a 20% reduction in self-amplification compared to unmodified devices. Moreover, the modification improves performance consistency, decreasing the standard deviation of measured self-amplification across devices from 14% to 5%. Using a calibrated model, we identify the electron-hole recombination lifetime due to defects within the p-doped layer as a key factor influencing self-amplification. Our model, which includes perimeter-induced short lifetimes of 7 ps in the p-doped layer reproduces the experimental results. Furthermore, the model predicts that devices with well passivated sidewalls resulting in lifetimes of 10 ns will have a self-amplification exceeding 20 unless the modification is incorporated, in which case self-amplification is 1.5. The contact resistance of npin structures is verified to be two orders of magnitude lower than that of corresponding pin structures.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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