TY - JOUR
T1 - PyTherNal
T2 - 4th International Conference on Research and Learning of Physics, ICRLP 2021
AU - Nanlohy, George Billy
AU - Yosia, Gabrian Granito
AU - Salim, Christopher
AU - Mariyanto, Mariyanto
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2022
Y1 - 2022
N2 - Thermomagnetic analysis is performed by bringing subject materials into its cooled and heated state, followed by analyzing the magnetic moment change. Performing these would result in obtaining the Curie Temperature of the materials, which is essential in estimating magnetic minerals contained in material samples. PyTherNal (Python Thermomagnetic Analyzer) is a thermomagnetic analysis tool in Python environment meant to assist in analyzing thermomagnetic data. The advantages of Python in its functionality and flexibility of being used in any operating system (OS) became the main reason for the program to be written in Python. PyTherNal is designed to assist in estimating Curie temperature of materials through thermomagnetic method, by locating the maximum curvature of the highest value of second (2nd) derivative of both cooling and heating data. To facilitate these, PyTherNal generates three figures, which are the curves for the thermomagnetic data, its 1st derivative, and its 2nd derivative. An advantage of the program is that it performs smoothing to increase the accuracy in estimating the Curie temperature as doing so would significantly minimize the variability of the derivative curve. Since the program is written in Python, it is open-source and therefore free to use. It is also capable of cross-platforming.
AB - Thermomagnetic analysis is performed by bringing subject materials into its cooled and heated state, followed by analyzing the magnetic moment change. Performing these would result in obtaining the Curie Temperature of the materials, which is essential in estimating magnetic minerals contained in material samples. PyTherNal (Python Thermomagnetic Analyzer) is a thermomagnetic analysis tool in Python environment meant to assist in analyzing thermomagnetic data. The advantages of Python in its functionality and flexibility of being used in any operating system (OS) became the main reason for the program to be written in Python. PyTherNal is designed to assist in estimating Curie temperature of materials through thermomagnetic method, by locating the maximum curvature of the highest value of second (2nd) derivative of both cooling and heating data. To facilitate these, PyTherNal generates three figures, which are the curves for the thermomagnetic data, its 1st derivative, and its 2nd derivative. An advantage of the program is that it performs smoothing to increase the accuracy in estimating the Curie temperature as doing so would significantly minimize the variability of the derivative curve. Since the program is written in Python, it is open-source and therefore free to use. It is also capable of cross-platforming.
UR - http://www.scopus.com/inward/record.url?scp=85135329562&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/2309/1/012035
DO - 10.1088/1742-6596/2309/1/012035
M3 - Conference article
AN - SCOPUS:85135329562
SN - 1742-6588
VL - 2309
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012035
Y2 - 1 September 2021 through 2 September 2021
ER -