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Peer-Review Record

A Matrix Effect Correction Method for Portable X-ray Fluorescence Data

Appl. Sci. 2022, 12(2), 568; https://doi.org/10.3390/app12020568
by Jilong Lu, Jinke Guo, Qiaoqiao Wei, Xiaodan Tang, Tian Lan, Yaru Hou and Xinyun Zhao *
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2022, 12(2), 568; https://doi.org/10.3390/app12020568
Submission received: 12 November 2021 / Revised: 24 December 2021 / Accepted: 30 December 2021 / Published: 7 January 2022
(This article belongs to the Section Chemical and Molecular Sciences)

Round 1

Reviewer 1 Report

The manuscript deals with a more complete multiple regression analysis for treating portable XRF data, specifically trace element analysis. The method is well presented and supported by statistics.

I would recommend the manuscript for publication after revision of the following points:

Some small comments:

Line 70: please provide reference to the manufacturer of the portable spectrometer

  1. Results and discussion

- Please describe how and which software you use to perform these regressions and scatter plots.

- Please provide higher resolution figures, they are quite low in quality.

- I would recommend putting a figure that shows the different XRF spectra exemplary for each class of reference material.

- Can you comment on the feasibility and sensitivity to detect Mg and Al ? (Here again the spectrum would help to visualize this)

A general comment:

Can you comment on the fact that you use 40 kV for performing the whole regression “equally” for very different elements (with different atomic number). The coefficients alpha-i, alpha-j, and u-I, are affectect by instruments conditions. How about using different voltages: for example 10 kV for elements with Z<30. And another thing, is there a possibility to use filters in the acquisition of the spectra? How would this affect the reference values you calculate?

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

The article is interesting on pXRF analysis using 16 certified reference materials. Some major elements were selected as correction indicators to correct the analysis results with application of a new method based on multiple linear regression analysis.

On the first look article is interesting, but I can't say if the samples are enough to support a new correction method. 

Background on specific (similar samples) could be enhanced with new  literature (last 3 years).

Also quality of images is low.

Author Response

Please see the attachment

Author Response File: Author Response.docx

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