A5036353285- Machine Learning in Materials Science
- Hydrogen Storage and Materials
- Conducting polymers and applications
- Electrochemical sensors and biosensors
- Nuclear Materials and Properties
- Chalcogenide Semiconductor Thin Films
- Advanced Semiconductor Detectors and Materials
- Analytical Chemistry and Sensors
- Advancements in Battery Materials
- Magnetic Properties and Synthesis of Ferrites
- ZnO doping and properties
- Iron oxide chemistry and applications
- Gold and Silver Nanoparticles Synthesis and Applications
- Transition Metal Oxide Nanomaterials
- MXene and MAX Phase Materials
- Crystallography and molecular interactions
- Multiferroics and related materials
- Boron and Carbon Nanomaterials Research
- Characterization and Applications of Magnetic Nanoparticles
- Analytical chemistry methods development
- Solid-state spectroscopy and crystallography
- Fuel Cells and Related Materials
- Supercapacitor Materials and Fabrication
- Surface Roughness and Optical Measurements
- Advanced Battery Materials and Technologies
University of Belgrade
2013-2023
Vinča Institute of Nuclear Sciences
2015-2023
Abstract Theoretical tools or structure–property relations that enable the prediction of metal hydrides are enormous interest in developing new hydrogen storage materials. Density functional theory (DFT) is one such approach provides accurate hydride formation energies, which, if complemented with vibrational zero‐point energy and other contributions, enthalpies. However, this time consuming and, therefore, often avoided, hindering modeling experimental behavior. The recent implementation...
One of the key properties determining metal hydride applicability in energy storage and conversion is enthalpy formation. Theoretical tools or structure-property relations which enable prediction this other hydrides are therefore huge interest toward development new materials. Density functional theory (DFT) one such approach that provides accurate formation energies, which, if complemented with vibrational zero-point contributions, provide enthalpies. However, time-consuming often avoided,...
The paper presents results of investigation ZnO nanopowder doped with Fe by means X-ray photoelectron spectroscopy (XPS). XPS analysis confirmed presence all constitutive elements at the sample surface. Surface composition was quantitatively determined and interpreted in light possible influences, among which most pronounced effects are inhomogeneous charging surface contamination.
Hydride formation in metals is a widely studied and applied phenomenon necessary to transition clean energy solutions various technological applications. We focus on three perspective applications of these materials, namely near-ambient hydrogen storage, storage compressor alkali metal conversion electrodes, demonstrate acceleration the research achieved by utilizing data-driven approach. Graph neural network was developed using transfer learning approach from MEGNet model data related...
As an extension of our previous studies multi-component semiconductors doped with magnetic impurities, this paper gives a comprehensive insight into electronic and local structure crystalline Cd0.98Co0.02Se, Cd0.98Co0.02Se0.9S0.1, Cd0.98Co0.02Se0.9Te0.1. Detailed characterization Co Se environment overall influence S(Te) (co)doping on the host crystal has been obtained by X-ray absorption fine (XAFS) technique calculations. Important structural information bond lengths disorder parameters...
One of the key properties determining metal hydride applicability in energy storage and conversion is enthalpy formation. Theoretical tools or structure-property relations which enable prediction this other hydrides are therefore huge interest toward development new materials. Density functional theory (DFT) one such approach that provides accurate formation energies, which, if complemented with vibrational zero-point contributions, provide enthalpies. However, time-consuming often avoided,...