When electromagnetic radiation impinges on an scatterer, in general, a part of the radiation power is scattered, another part is absorbed and the rest of the radiation power is transmitted through the obstacle. In infrared transmission spectroscopy, the transmitted light is collected in order to identify the part that is lost from the initial radiation power of the source. The lost part is expected to describe the absorption properties of the scatterer. When a substantial part of the light is lost due to scattering, the interpretation of the data becomes difficult, since it is difficult to decide if the radiation power at a certain wavelength is lost due to scattering or chemical absorption. If the wavelength of the electromagnetic wave is comparable to the size of the scatterer, the part of the radiation power that is lost due to scattering is very high. When the scatterer has spherical symmetry, the scattering is called Mie type scattering.
In the infrared spectroscopy of single cells and tissues, strong Mie scattering signatures distort the spectra. The chemical interpretation of the absorption peaks and the multivariate analysis is difficult in this case. Therefore, there is a need for algorithms that can separate the chemical information (absorption) from the physical properties (scattering). Has during recent years contributed substantially to the development of spectral correction methods for removing Mie type scattering and other spectral distortions. The group developed algorithms that are today used by a broad community in the field.
In energy physics Mie type scattering is also an interesting and very modern topic. In order to reduce material costs and to increase efficiency of solar cells, often spherical nanostructures are added to the top of solar cells, to the back-reflecting layer or inside the absorbing layer. In these cases, the photons are scattered all around the nanostructures. Thus, they spend more time in the neighborhood of the absorbing layer and increase the probability of an electron-hole pair production. More electron-hole pairs contribute to the increase of the produced electricity. This means with nanostructures the efficiency of the solar cells can be enhanced. In order to understand the efficiency increase the rationale of the light scattering in these nanostructures needs to be understood. When the nanostructures have spherical symmetry, the scattering is Mie type scattering. The Mie type scattering is highly complex in the case of nanostructures with spherical structures, since the coupling of the spheres needs to be taken into account. Our aim is to understand the Mie scattering and the coupled modes between nanospheres and use this knowledge to design new architectures of solar cells with increased efficiency.
Combining spectral and image information in the analysis of hyperspectral imaging data
Research Council of Norway (FRINATEK project Nº. 289518)
Development of a New Ray Model for Understanding the Coupling Between Dielectric Spheres for Photovoltaics with Higher Efficiency
Research Council of Norway (FRINATEK project Nº. 250678)
Hyperspectral imaging in biophysics and energy physics
Research Council of Norway (ISPNATTEK project Nº. 216687)
Advancing 3D Chemical Imaging: FTIR Spectro-microtomography, FTIR Spectro-microlaminography and Hyperspectral Data Analysis
National Science Foundation - USA (Chemical Measurement & Imaging project Nº: 1508240)
Kong B., Brandsrud M.A., Heitmann Solheim J., Nedrebø I., Blümel R., Kohler A.
Effects of the coupling of dielectric spherical particles on signatures in infrared microspectroscopy
Scientific Reports 12 (2022) 13327
Solheim J.H., Zimmermann B., Tafintseva V., Dzurendová S., Shapaval V., Kohler A.
The Use of Constituent Spectra and Weighting in Extended Multiplicative Signal Correction in Infrared Spectroscopy.
Molecules 27 (2022) 1900
Heitmann Solheim J., Borondics F., Zimmermann B., Sandt C., Muthreich F., Kohler A.
An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples.
Journal of Biophotonics 14 (2021) e202100148
Seim E., Kohler A., Lukacs R., Brandsrud M.A, Marstein E.S, Olsen E., Blümel R.
Wave chaos enhanced light trapping in optically thin solar cells
Chaos 31 (2021) 063136
Blazhko U., Shapaval V., Kovalev V., Kohlera A.
Comparison of augmentation and pre-processing for deep learning and chemometric classification of infrared spectra
Chemometrics and Intelligent Laboratory Systems 215 (2021) 104367.
Brandsrud M.A., Blümel R., Lukacs R., Seim E., Stensrud Marstein E, Olsen E., Kohler A.
Investigation of resonance structures in optically thin solar cells
Journal of Photonics for Energy, 11 (2021) 024501.
Brandsrud M.A., Blümel R., Heitmann Solheim J., Kohler A.
The effect of deformation of absorbing scatterers on Mie-type signatures in infrared microspectroscopy
Scientific Reports 11 (2021) 4675
Almklov Magnussen E., Heitmann Solheim J., Blazhko U., Tafintseva V., Tøndel K., Liland K.H., Dzurendova S., Shapaval V., Kohler A.
Deep convolutional neural network recovers pure absorbance spectra from highly scatter‐distorted spectra of cells
Journal of Biophotonics (2020) e202000204.
Schofield A.J., Blümel R., Kohler A., Lukacs R., Hirschmugl C.J.
Extracting pure absorbance spectra in infrared microspectroscopy by modeling absorption bands as Fano resonances.
Journal of Chemical Physics 150 (2019) 154124.
Heitmann Solheim J., Gunko E., Petersen D., Grosserruschkamp F., Gerwert K., Kohler A.
An open source code for Mie Extinction EMSC for infrared microscopy spectra of cells and tissues.
Journal of Biophotonics 12 (2019) e201800415
Brandsrud M.A., Seim E., Lukacs R., Kohler A., Marstein E.S., Olsen E., Blümel R.
Exact ray theory for the calculation of the optical generation rate in optically thin solar cells.
Physica E: Low-dimensional Systems and Nanostructures 105 (2019) 125 – 138.
Seim E., Kohler A., Lukacs R., Brandsrud M.A, Stensrud Marstein E., Olsen E., Blümel R.
Chaos: A new mechanism for enhancing the optical generation rate in thin-film solar cells.
SPIE West 10913 (2019). Chaos 29 (2019) 093132
Konevskikh T., Lukacs R., Kohler A.
An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues
Journal of Biophotonics 11 (2018) DOI: 10.1002/jbio.201600307
Blümel R., Lukacs R., Zimmermann B., Bağcıoğlu M., Kohler A.
Observation of Mie ripples in the synchrotron FTIR spectra of spheroidal pollen grains.
Journal of the Optical Society of America A 35 (2018) 1769.
Azarfar G., Aboualizadeh E., Walter N.M., Ratti S., Olivieri C., Norici A., Nasse M., Kohler A., Giordano M., Hirschmugl C.J.
Estimating and correcting interference fringes in infrared spectra in infrared hyperspectral imaging.
Analyst 143 (2018) 4674.
Hovde Liland K., Kohler A., Afseth N.K.
Model-based pre-processing in Raman spectroscopy of biological samples.
Journal of Raman Spectroscopy (2016) DOI: 10.1002/jrs.4886.
Konevskikh T., Lukacs R., Blümel R., Ponossov A., Kohler A.
Mie scatter corrections in single cell infrared microspectroscopy.
Faraday Discussions 187 (2016) 235.
Konevskikh T., Ponossov A., Blumel R., Lukacs R., Kohler A.
Fringes in FTIR spectroscopy revisited: understanding and modelling fringes in infrared spectroscopy of thin films.
Analyst 140 (2015) 3969.
Lukacs R., Blümel R., Zimmermann B., Bağcıoğlu M., Kohler A.
Recovery of absorbance spectra of micrometer-sized biological and inanimate particles.
Analyst 140 (2015) 3273.
Zimmerman B., Kohler A.
Optimizing Savitzky-Golay parameters for improving spectral resolution and quantification in infrared spectroscopy. Applied Spectroscopy.
Applied Spectroscopy. 67 (2013) 892.
Bassan P., Sachdevaa A., Kohler A., Hughes C., Henderson A., Boyle J., Shanks J.H., Brown M., Clarke N.W., Gardner P.
FTIR Microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm.
Analyst 137 (2012) 1370.
Afseth N.K., Kohler A.
Extended multiplicative signal correction in vibrational spectroscopy, a tutorial.
Chemometrics and Intelligent Laboratory Systems 117 (2012) 92.
Bassan P., Kohler A., Martens H., Lee J., Byrne H., Gardner P.
The RMieS-EMSC correction algorithm for infrared spectra of biological cells: Extension using full Mie scattering theory and speed optimisation using graphics processing unit (GPU) computing.
Biophotonics Journal 3 (2010) 609.
Bassan P., Kohler A., Martens H., Lee J., Byrne H.J., Dumas P., Gazi E., Brown M., Clarke N., Gardner P.
Resonant Mie Scattering (RMieS) Correction of Infrared Spectra from Highly Scattering Biological Samples.
Analyst 135 (2010) 268.
Kohler A., Böcker U., Warringer J., Blomberg A., Omholt S.W., Stark E., Martens H.
Reducing inter-replicate variation in Fourier-transform infrared spectroscopy by extended multiplicative signal correction.
Applied spectroscopy 63 (2009) 296.
Kohler A., Sulé-Suso J., Sockalingum G.D., Tobin M., Bahrami F., Yang Y., Pijanka J., Dumas P., Cotte M., Martens H.
Estimating and correcting Mie scattering in synchrotron based microscopic FTIR spectra by extended multiplicative signal correction (EMSC).
Applied Spectroscopy 62 (2008) 259.
Martens H., Bruun S.W., Adt I., Sockalingum G.D., Kohler A.
Pre-processing in biochemometrics: correction for path-length and temperature effects of water in FTIR bio-spectroscopy by EMSC.
Journal of Chemometrics 20 (2006) 402.
Bruun S.W., Kohler A., Adt I., Sockalingum G.D., Manfait M., Martens H.
Correcting attenuated total reflection-Fourier transform infrared spectra for water vapour and carbon dioxide.
Applied Spectroscopy 60 (2006) 1029.
Thennadil S., Martens H., Kohler A.
Physics-based Multiplicative Scatter Correction Approaches for Improving the Performance of Calibration Models.
Applied Spectroscopy 60 (2006) 315.
Kohler A., Kirschner C., Oust A., Martens H.
Extended multiplicative signal correction as a tool for separation and characterisation of physical and chemical information in Fourier transform infrared microscopy images of cryo-sections of beef loin.
Applied Spectroscopy 59 (2005) 707.