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Mathematical Gnostics, a Powerful Method of Evaluating Experimental Heat Capacity Data

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    SYSNO ASEP0438848
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeThe record was not marked in the RIV
    TitleMathematical Gnostics, a Powerful Method of Evaluating Experimental Heat Capacity Data
    Author(s) Wagner, Zdeněk (UCHP-M) RID, SAI, ORCID
    Andresová, Adéla (UCHP-M) RID, SAI
    Bendová, Magdalena (UCHP-M) RID, ORCID, SAI
    Machanová, Karolina (UCHP-M) RID, SAI
    Rotrekl, Jan (UCHP-M) RID, ORCID, SAI
    Source TitleBook of Full Papers, Lecture Programme. - Frankfurt am Main : IChemE, 2014 - ISBN N.
    Pagess. 28-33
    Number of pages6 s.
    Publication formMedium - C
    ActionInternational Conference on Distillation and Absorption 2014 /10./
    Event date14.09.2014-17.09.2014
    VEvent locationFriedrichshafen
    CountryDE - Germany
    Event typeEUR
    Languageeng - English
    CountryDE - Germany
    Keywordsmathematical gnostics ; critical assessment ; heat capacity
    Subject RIVCF - Physical ; Theoretical Chemistry
    R&D ProjectsLG12032 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    Institutional supportUCHP-M - RVO:67985858
    AnnotationThe work demonstrates a powerful method of data analysis based on algorithms of mathematical gnostics and shows its application for evaluation of experimental heat capacity data. The method was first used during the initial setup and testing the functionality of a newly bought calorimeter. The stability of the calorimeter was examined and the optimum heating rate was determined. The optimum is chosen in order to maximize the signal to noise ratio. It is estimated as a temperature rate where the values of heat capacities obtained in repeated measurement have narrowest tolerance interval and narrowest interval of typical data. Heat capacities of three ionic liquids were further measured in the temperature range of 20–75 °C and repeatability analyzed by algorithms of mathematical gnostics. The width of the interval of typical data is less than 0.25 % in all cases
    WorkplaceInstitute of Chemical Process Fundamentals
    ContactEva Jirsová, jirsova@icpf.cas.cz, Tel.: 220 390 227
    Year of Publishing2015
    Electronic addresshttp://hdl.handle.net/11104/0242198
Number of the records: 1  

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