Metadata-Version: 2.1
Name: lsprlib
Version: 0.20.6
Summary: lsprlib is a Python 3 scientific package for modelling UV-Vis spectral behaviour of metallic nanoparticle-dieletric composites.
Home-page: https://github.com/Arghantyr/LSPR-glass-transmittance
Author: Angantyr Krzysztof Orlinski
Author-email: kakoori@gmail.com
License: UNKNOWN
Description: # What is lsprlib?
        
        _lsprlib_ is a Python 3 scientific package for modelling UV-Vis spectral behaviour of metallic nanoparticle-dieletric composites.
        
        # Dependencies
        
        To run _lsprlib_ smoothly you will need:
        1. Python 3.4+
        2. Pandas 1.0.3+
        3. NumPy 1.18.1+
        4. SciPy 1.4.1+
        5. Statsmodels 0.11.0+
        6. Matplotlib 3.1.3+
        
        # What does lsprlib enable?
        
        _lsprlib_ enables one to approximate some spectroscopic features of metallic nanoparticle-dielectric composites, e.g. transmittance, absorbance, scattering cross-section. The model utilizes dipole approximation of Mie solution to Maxwell equations, described in more detail in article by Olson et al.<sup>1</sup>
        
        To perform a simulation, one needs to construct a composite, so matrix and metallic nanoparticles, so for each a set of refractive index and extinction coefficient data for simulated spectral range are necessary. The model **does not take into account possible interactions at the nanoparticle/matrix interface**, i.e. the composite absorbance is a simple sum of matrix and nanoparticle absorbances calculated for pristine materials.
        
        
        
        <sup>1</sup> _**Optical Characterization of Single Plasmonic Nanoparticles**_ - J. Olson, S. Dominguez-Medina, A. Hoggard, L.-Y. Wang, W.-Sh. Chang, S. Link; *Chem Soc Rev. 2015 January 7; 44(1): 40-57. doi: 10.1039/c4cs00131a.*
        
        # How to get it running?
        
        To install lsprlib package use [pip](https://pip.pypa.io/en/stable/) package manager:
        
        ```
        pip install lsprlib
        ```
        
        # Usage
        
        More examples on how to use the lspr_library and specific methods can be found in the documentation.
        The transmittance of 31nm silver nanoparticles homogeneously distributed in vacuum with concentration 5.8 &middot; 10<sup>13</sup> cm<sup>-3</sup>
        
        ```
        import lsprlib as lpl
        
        # Get the csv file with n,k values for silver in range 200-1000nm
        # spaced evenly every 1nm
        Ag = lpl.OpticalMaterial(name = "Silver",source = "n-k_Silver_200-1000nm_(1nm).csv")
        
        # Get n,k values for vacuum
        Vacuum = lpl.OpticalMaterial(name = "Vacuum",
                                 source = "n-k_data_for_vacuum_200-1000nm_(1nm).csv")
        
        # Create Ag nanoparticles with mean size of 31nm, standard deviation of 1nm
        # and concentration of 5.8e13 cm^-3
        nAg = lpl.Nanoparticle(name = "Silver nanoparticles", material=Ag,
                           size=31, concentration=5.8e13)
        
        # Set the transmittance measurement of a 1 micron thick sample of the composite
        (silver nanoparticles dispersed in vacuum); use "T_corr" for reflectance corrected result
        Transmittance = lpl.SpectralMeasurement("Measure the transmittance",
                                            matrix=Vacuum, nanoparticle=nAg,
                                            thickness=3).plot_results("T_corr")
        ```
        
        ![The result is a preformatted plot of the reflectance corrected transmittance](https://github.com/Arghantyr/LSPR-glass-transmittance/blob/master/example.jpg)
        
        # License
        lsprlib is distributed under [MIT](https://choosealicense.com/licenses/mit/) license.
        
        # Support
        If issue is spotted please open an issue on the [GitHub repo of the project](https://github.com/Arghantyr/LSPR-glass-transmittance/issues). For changes, upgrades and simillar refer to the [project's wiki site](https://github.com/Arghantyr/LSPR-glass-transmittance/wiki).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.4
Description-Content-Type: text/markdown
