Evidence map›Paper›PMID 41593327›Full record

ArticleScientific reports2026

Optimization of ultrafast laser ablation of stainless steel in burst mode based on experimentally validated simulations and analytical modelling.

Luis Omeñaca, Santiago Miguel Olaizola, Ainara Rodríguez, Mikel Gomez-Aranzadi, Isabel Ayerdi, Enrique Castaño

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Luis OmeñacaCEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, Donostia/San Sebastián, 20018, Spain.
Santiago Miguel OlaizolaCEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, Donostia/San Sebastián, 20018, Spain.
Ainara RodríguezCEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, Donostia/San Sebastián, 20018, Spain.
Mikel Gomez-AranzadiCEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, Donostia/San Sebastián, 20018, Spain.
Isabel AyerdiCEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, Donostia/San Sebastián, 20018, Spain.
Enrique CastañoCEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, Donostia/San Sebastián, 20018, Spain. ecastano@ceit.es.

Funding

HORIZON EUROPE Digital, Industry and Space 101091623 BILASURFHorizon Europe Programe 101086227 L4DNANO
6 · The paper itself

Abstract

Femtosecond lasers have proven to be a highly effective tool for surface micro- and nanomachining, offering high precision through minimal heat-affected zones compared to longer-pulse lasers. Moreover, recent advancements in burst technology show great promise for enhancing both efficiency and precision. This study investigates the dependence of fluence and number of sub-pulses on the ablation depth and diameter of 316 L Stainless Steel with a MHz intraburst repetition rate. An extended two-temperature model, incorporating the heat diffusion between sub-pulses, is introduced to predict ablation depth and diameter for varying number of sub-pulses. Simulated results are compared with experimental data, showing a good qualitative agreement between them. The findings reveal that burst mode can significantly improve ablation rates by mitigating efficiency loses at high fluence and provide insights into how to achieve the optimal parameters for its application.

Indexed as

Burst modeFemtosecond laserStainless steelTwo-Temperature model.Ultrafast Laser-Metal interaction

Identifiers

PMID41593327
PMCPMC12905436

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.