Researcher Directory
Nadya Amalia is a researcher and member of the Quantum Simulation research group. Her research primarily focuses on conducting ab initio studies using density functional theory (DFT) calculations. She is interested in understanding the atomic-level characteristics that shape materials’ physical and mechanical properties. She employs computational techniques to investigate how different materials behave to achieve this. Her research is relevant to condensed matter physics and materials science, particularly in the context of material design and exploration.
- Research Keywords: Density-functional theory, Condensed matter physics, Computational physics, Materials science
- Contact: nadya.amalia(at)brin.go.id or nady003(at)brin.go.id
- Metrics: Google Scholar, Scopus
- Dr. | Department of Physics, Institut Teknologi Bandung, Indonesia.
- M.Si. / M. Sc. | Department of Physics, Institut Teknologi Bandung, Indonesia.
- S.Si. / B. Sc. | Department of Physics, Universitas Lambung Mangkurat, Indonesia
- 2023-present, Researcher, BRIN Research Center for Quantum Physics, Indonesia.
- 2022-2023, Researcher, BRIN Research Center for Quantum Physics, Indonesia.
- 2021-2022, Researcher, BRIN Research Center for Metallurgy and Materials, Indonesia.
- 2020-2021, Researcher, LIPI Research Center for Metallurgy and Materials, Indonesia.
- 2016-2020, Tutorial Assistant, Institut Teknologi Bandung, Indonesia.
- 2012-2013, Research Assistant, Universitas Lambung Mangkurat, Indonesia.
- P. Lubis, N. Amalia, S. A. Wella, and Sholihun, “Thermoelectric Properties of Monolayer and Bilayer Buckled XTe (X= Ge, Sn, and Pb)“, Adv. Nat. Sci.: Nanosci. Nanotechnol. 13, 025008 (2021).
- N. Amalia, E. Yuliza, D. O. Margaretta, F. D. Utami, N. Surtiyeni, S. Viridi, and M. Abdullah, “A Novel Method for Characterizing Temperature-dependent Elastic Modulus and Glass Transition Temperature by Processing the Images of Bending Cantilever Slender Beams at Different Temperatures“, AIP Adv. 8, 115201 (2018).
- N. Amalia, A. E. Fahrudin, and A. V. Nasrulloh, “Indonesian Vowel Recognition using Artificial Neural Network Based on the Wavelet Features“, Int. J. Electr. Comput. Eng. 3, 260-269 (2013).