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Record W2897724063 · doi:10.2351/1.5061945

Process optimization for improving drilling efficiency in EWT solar cell manufacturing

2010· article· en· W2897724063 on OpenAlexaff
Henrikki Pantsar, Thomas Eisenbeis, M. Rekow, R. Murison, Hans Herfurth, Stefan H. Heinemann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsOsta Bio Technologies (Canada)
Fundersnot available
KeywordsWaferLaser drillingCommon emitterLaserDrillingAmplifierMaterials scienceLaser beam machiningLaser power scalingMechanical engineeringAutomotive engineeringComputer scienceProcess engineeringOpticsOptoelectronicsEngineering

Abstract

fetched live from OpenAlex

Pulse parameter optimization is a key element in reaching higher drilling rates in the production of Emitter Wrap Through (EWT) solar cells. Manufacturing of these cells relies on fast laser drilling of silicon wafers. In order to create a cost case for EWT manufacturing, not only the drilling rate, but also the investment costs and cost of ownership have to be taken into account. In this aspect using fewer lower power lasers with a capability to maximize energy efficiency in drilling is an important factor. Master Oscillator Power Amplifier fiber laser concept allows for independent adjustment of pulse width, energy and temporal shape. This capability can be exploited for improving the drilling process efficiency. Combined with a FPGA controller, one can drill holes at unprecedented speeds. It was shown that a single hole can be drilled through a 210 µm silicon wafer using less than 3 mJ of energy; consequently 6,250 holes per second could be drilled using 18.2 W laser power. The results were compared to q-switched lasers by mimicking the shape of a high peak power q-switched pulse.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.503

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 head0.207
Teacher spread0.203 · 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 designSimulation or modeling
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

Citations2
Published2010
Admission routes1
Has abstractyes

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