Evidence map›Paper›PMID 36144021›Full record

ArticleMicromachines2022

Prediction Model for Liquid-Assisted Femtosecond Laser Micro Milling of Quartz without Taper.

Hongbing Yuan, Zhihao Chen, Peichao Wu, Yimin Deng, Xiaowen Cao, Wenwu Zhang

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Hongbing YuanFaculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo 315211, China.
Zhihao ChenFaculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo 315211, China.
Peichao WuNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Yimin DengFaculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo 315211, China.
Xiaowen CaoNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Wenwu ZhangNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The strong nonlinear absorption effect and “cold” processing characteristics of femtosecond lasers make them uniquely advantageous and promising for the micro- and nanoprocessing of hard and brittle materials, such as quartz. Traditional methods for studying the effects of femtosecond laser parameters on the quality of the processed structure mainly use univariate analysis methods, which require large mounts of experiments to predict and achieve the desired experimental results. The method of design of experiments (DOE) provides a way to predict desirable experimental results through smaller experimental scales, shorter experimental periods and lower experimental costs. In this study, a DOE program was designed to investigate the effects of a serious of parameters (laser repetition frequency, pulse energy, scan speed, scan distance, scan mode, scan times and laser focus position) on the depth and roughness (Ra) of the fabricated structure through the liquid-assisted femtosecond laser processing of quartz. A prediction model between the response variables and the main parameters was defined and validated. Finally, several blind holes with a size of 50 × 50 μm2 and a depth of 200 μm were fabricated by the prediction model, which demonstrated the good consistency of the prediction model.

Indexed as

design of experiment (DOE)femtosecond laserliquid assistedprediction model

Identifiers

PMID36144021
PMCPMC9503145

What OpenQuestion holds

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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.