VARIFORC v. 5.0
Description
VARIFORC is a software for advanced processing of first-order reversal curve (FORC) measurements, written in Wolfram Mathematica. VARIFORC algorithms are designed to handle the opposed needs of localized measurement resolution preservation and noise suppression typical of most synthetic and natural magnetic materials. They have been implemented in several FORC processing tools and have become a standard in the scientific literature. VARIFORC also offers several plotting options and additional tools for quantitative analysis of the FORC function and extraction of coercivity distributions.
VARIFORC has a modular structure with different packages for data import, processing, and graphical rendering. It comes with a complete user manual containing detailed descriptions of each processing parameter, along with processing examples and a complete documentation of data formats, FORC protocols, and algorithms.
VARIFORC highlights:
- Compatible with the Wolfram Player Pro platform, a cost-effective alternative to a full Mathematica license (see https://store.wolfram.com/view/app/playerpro/ for pricing).
- Import raw FORC measurements in all formats and stack multiple measurements
- Correct artifacts such as drift, outliers, and first-point anomalies and provides several diagnostic parameters to assess measurement quality and instrumental problems.
- Track temporal changes in sequences of FORC measurements
- Perform lower branch subtraction with standard FORC measurement protocols and new protocols that include measurements of the lower hysteresis branch, for better data processing
- Calculates the FORC function or other types of first- and second-order derivatives over any rectangular FORC region, including regions that are only partially filled by data.
- Supports conventional processing with constant smoothing factor, as well as advanced options for lower hysteresis branch subtraction, de-shearing, variable smoothing factors, and smoothing factor limitations over critical regions, along with heteroscedastic error calculation and significance estimates.
- Handles all known types of regular and non-regular FORC functions with optimal noise suppression, avoiding smoothing artifacts.
- Advanced plotting options for best FORC diagram representation, including nonlinear color scales, contour lines, and quantile contour lines.
- Vertical profile normalization for the representation of interaction field distributions.
- Supports measurement de-shearing to remove or simulate the effect of internal field.
- Calculates coercivity distributions associated with different FORC measurement subsets.
- Extracts the central ridge and calculates the associated coercivity distribution.
- Supports measurement averaging, subtraction of background contributions, and calculation of measurement differences (e.g., before and after specimen treatment).
- Stores all processing parameters for traceability and replication on similar samples.
- Optional GUI interface for the assisted choice of optimal processing parameters.
Files
Example_FirstPointCorrection.zip
Files
(142.4 MB)
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Additional details
References
- Egli, R. (2013). VARIFORC: An optimized protocol for calculating non-regular first-order reversal curve (FORC) diagrams. Global and Planetary Change, 110, 302–320. http://dx.doi.org/10.1016/j.gloplacha.2013.08.003.
- Egli, R., (2021). Magnetic Characterization of Geologic Materials with First-Order Reversal-Curves. In: V. Franco and B. Dodrill (Eds.): Magnetic Measurement Techniques for Materials Characterization, Springer Nature Publishing Group, 455–604, https://doi.org/10.1063/978-3-030-70443-8_17.
- Roberts, A. P., D. Heslop, X. Zhao, H. Oda, R. Egli, R. J. Harrison, P. Hu, A. R. Muxworthy, T. Sato (2022). Unlocking information about fine magnetic particle assemblages from first-order reversal curve diagrams: Recent advances. Earth-Science Reviews, 227, 103950, https://doi.org/10.1016/j.earscirev.2022.103950.
- Egli, R., A.P. Chen, M. Winklhofer, K.P. Kodama, C.-S. Horng (2010). Detection of non-interacting single domain particles using first-order reversal curve diagrams. Geochemistry Geophysics Geosystems 11, Q01Z11, doi:10.1029/2009GC002916.
- Mullurkara, S. V., R. Egli, B.C. Dodrill, S. Tan, P.R. Ohodnicki Jr. (2023). Understanding magnetic interactions and reversal mechanisms in a spinodally decomposed cobalt ferrite using first order reversal curves. AIP Advances, 13, 025328, 10:1079229, https://doi.org/10.1063/9.0000562.