MétaCan
Menu
Back to cohort
Record W4407857236 · doi:10.1002/mop.70133

Design Method of Power Chip Terminations With Lower Cost, Lower Voltage Standing Wave Ratio, and Broader Bandwidth

2025· article· en· W4407857236 on OpenAlexaff
Hao Peng, Na Xue, Ziyan Qi, Lifeng Chen, Jiming Chen, Yu Liu, Serioja Ovidiu Tatu, Tao Yang, Jiadong Pan, Feng Zhang

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsElectrical engineeringChipBandwidth (computing)VoltagePower (physics)Electronic engineeringEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

ABSTRACT In this paper, we deeply explore a design method for power chip terminations with low‐cost, low VSWR and broadband performance. Through a comprehensive investigation of existing power chip terminations, the electromagnetic leakage significantly impacts its performance. To address these issues, an electromagnetic constraint boundary has been introduced to enhance its VSWR. Considering the high cost of the gold plating process on the sides of chemical vapor deposition diamond substrates, an independent electromagnetic constraint metal carrier with a concave shape is proposed. TaN thin film is employed as the terminal matching load. Simulation results reveal that the VSWR of different substrates (ceramic and diamond substrates) are very similar. Consequently, this work presents a design, simulation, and measurement of a power chip termination applied to a ceramic substrate. Measurement results demonstrate that the VSWR is less than 1.5 over a frequency range of DC to 43.5 GHz, significantly outperforming existing commercial power chip terminations. In addition, the fluctuation of VSWR across the broadband operating frequencies has been discussed in detail.

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 score0.420
Threshold uncertainty score0.577

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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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 routes1
Has abstractyes

Explore more

Same venueMicrowave and Optical Technology LettersSame topicElectromagnetic Compatibility and Noise SuppressionFrench-language works237,207