Sökning: "density functional theory"

Visar resultat 1 - 5 av 75 uppsatser innehållade orden density functional theory.

  1. 1. First Principle Calculations & Inelastic Neutron Scattering on the Single-Crystalline Superconductor LaPt2Si2

    Master-uppsats, KTH/Materialvetenskap

    Författare :Mazza Federico; [2020]
    Nyckelord :Superconductivity; LaPt2Si2; Inelastic Neutron Scattering; Charge Density Wave; Band Structure Calculations; DFT; SNIC; J-PARC; Supraledning; LaPt2Si2; neutronspridning; neutronspektroskopi; Bandberäkningar; DFT; J-PARC;

    Sammanfattning : This work presents a comprehensive study on single crystalline LaPt2Si2, in which superconductivity and a charge density wave (CDW) coexist. The usage of density functional theory (DFT) modeling and Inelastic Neutron Scattering has been the primary form of investigation, in order to determine all the characteristic features of the sample taken under consideration. LÄS MER

  2. 2. Spectroelectrochemical analysis of the Li-ion battery solid electrolyte interphase using simulated Raman spectra

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Fasta tillståndets fysik

    Författare :Edvin Andersson; [2020]
    Nyckelord :Lithium Ion Battery; Solid Electrolyte Interphase; Surface Enhanced Raman Spectroscopy; Density Functional Theory; LIB; SEI; SERS; DFT;

    Sammanfattning : Lithium Ion Batteries (LIBs) are important in today's society, powering cars and mobile devices. LIBs consist of a negative anode commonly made of graphite, and a positive cathode commonly made from transition metal oxides. Between these electrodes are separators and organic solvent based electrolyte. LÄS MER

  3. 3. Graph neural networks for prediction of formation energies of crystals

    Master-uppsats, Linköpings universitet/Institutionen för fysik, kemi och biologi

    Författare :Filip Ekström; [2020]
    Nyckelord :Machine learning; graph neural networks; formation energies; crystal; transfer learning; phase diagram; Maskininlärning; graf-neuronnät; formationsenergier; kristall; transfer learning; fasdiagram;

    Sammanfattning : Predicting formation energies of crystals is a common but computationally expensive task. In this work, it is therefore investigated how a neural network can be used as a tool for predicting formation energies with less computational cost compared to conventional methods. LÄS MER

  4. 4. Computational study of single protein sensing using nanopores

    Master-uppsats, Uppsala universitet/Materialteori

    Författare :Sebastian Cardoch; [2020]
    Nyckelord :nanopores; protein sensing; mini-proteins; silicon nitride; ionic current; molecular dynamics; density functional theory; amino acids;

    Sammanfattning : Identifying the protein content in a cell in a fast and reliable manner has become a relevant goal in the field of proteomics. This thesis computationally explores the potential for silicon nitride nanopores to sense and distinguish single miniproteins, which are small domains that promise to facilitate the systematic study of larger proteins. LÄS MER

  5. 5. A model for heterogenic catalytic conversion of carbon dioxide to methanol

    Kandidat-uppsats, Linköpings universitet/Institutionen för fysik, kemi och biologi

    Författare :Elin Johannesson; [2020]
    Nyckelord :Carbon dioxide; methanol; heterogeneous catalysis; zinc oxide; computational chemistry; density functional theory;

    Sammanfattning : Since our society became industrialised, the levels of carbon dioxide in our atmosphere have been steadily rising, to the point where it in early 2020 at is 413 ppm. The high concentration is causing several troubling effects worldwide because of the increase in mean temperature that it creates, which causes longer draughts, more severe floods, and rising seawater levels to name a few. LÄS MER