New tool for analyzing MuSR data for semiconductors
ORAL
Abstract
This presentation introduces a tool that is currently in development to aid in the analysis of Muon Spin Research (MuSR) data.
The primary existing tools include “MSRFIT” [1] (based on the MINUIT – Function Minimization and Error Analysis” package), “WiMDA (Windows Muon Data Analysis)” [2] and “musrfit: A Free Platform-Independent Framework for μSR Data Analysis” [3].
These have been the standard preliminary analysis tools for the major labs including TRIUMF, STFC-RAL and PSI, respectively, and work well enough for an initial pass at the data but do not allow the user to easily customize the models used in the fit, post-processing and can be quite cumbersome to work with especially for someone new to the field.
The time is ripe to harness newer, more user-friendly computer language and interfaces to increase the flexibility of the analysis packages and greatly improve the accessibility for the user.
MuSR is an experimental technique that can provide us with many insights into the electronic and magnetic properties and fundamental behavior of materials and interactions within. [4,5]
When applied to semiconductors, materials with tunable electronic and magnetic behaviors, we can ultimately use this information to, for instance, develop more efficient technologies including solar panels other electronic devices. Here we introduce MuSR, an example class of materials relevant to the work and a new tool for analyzing these data.
[1] Flaschin, Brewer et al. cmms.triumf.ca/msrfit
[2] F. Pratt. Physica B: Condensed Matter 289-290 (2000) 710-714
[3] A. Suter, B.M. Wojek Physica Procedia 30 (2012) 69
[4] P.W. Mengyan. `The role of muons in semiconductor research' in Characterisation and Control of Defects in Semiconductors ed. F.~Tuomisto (IET: London, 2019).
[5] S.J. Blundell et al. Muon Spectroscopy: An Introduction (Oxford University Press: Oxford 2021).
The primary existing tools include “MSRFIT” [1] (based on the MINUIT – Function Minimization and Error Analysis” package), “WiMDA (Windows Muon Data Analysis)” [2] and “musrfit: A Free Platform-Independent Framework for μSR Data Analysis” [3].
These have been the standard preliminary analysis tools for the major labs including TRIUMF, STFC-RAL and PSI, respectively, and work well enough for an initial pass at the data but do not allow the user to easily customize the models used in the fit, post-processing and can be quite cumbersome to work with especially for someone new to the field.
The time is ripe to harness newer, more user-friendly computer language and interfaces to increase the flexibility of the analysis packages and greatly improve the accessibility for the user.
MuSR is an experimental technique that can provide us with many insights into the electronic and magnetic properties and fundamental behavior of materials and interactions within. [4,5]
When applied to semiconductors, materials with tunable electronic and magnetic behaviors, we can ultimately use this information to, for instance, develop more efficient technologies including solar panels other electronic devices. Here we introduce MuSR, an example class of materials relevant to the work and a new tool for analyzing these data.
[1] Flaschin, Brewer et al. cmms.triumf.ca/msrfit
[2] F. Pratt. Physica B: Condensed Matter 289-290 (2000) 710-714
[3] A. Suter, B.M. Wojek Physica Procedia 30 (2012) 69
[4] P.W. Mengyan. `The role of muons in semiconductor research' in Characterisation and Control of Defects in Semiconductors ed. F.~Tuomisto (IET: London, 2019).
[5] S.J. Blundell et al. Muon Spectroscopy: An Introduction (Oxford University Press: Oxford 2021).
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Presenters
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Drake R Dotson
Northern Michigan University
Authors
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Drake R Dotson
Northern Michigan University
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Rick (P.W.) Mengyan
Northern Michigan University