arXiv subjects

I Made Joni

Publications and source records attributed to I Made Joni.

4 recordsLinked to original sources

arXiv2022

Nonlinear polarization effect of functionalized graphene quantum dots

Graphene quantum dots (GQDs) are nanoscale structures of graphene with quantum properties and edge effects that give photoluminescence properties. The effect of quantum confinement and differences in the nature of GQD structure makes its optical characteristics highly dependent on the size of the structure. This study explains a few exploratory semi empirical calculations of nonlinear polarization properties of functionalized GQD (fGQD) three dimensionally. Based on this, the calculation of the linear polarization and first hyperpolarization was performed by the finite field method, which is based on the expansion of the energy and dipole moment. As a result, the fGQD molecule dominantly has high optical nonlinear properties as indicated by the high \b{eta} values (71 to 4488 a.u.). In general, the first hyperpolarizabilities have a linear relationship with the dipole moments. It was potentially used for the second harmonic imaging microscopy (SHIM) application.

physics.comp-ph↗

arXiv2022

Thermal Transport in Twisted Bilayer Graphene: An Equilibrium Molecular Dynamics Study

Twisted bilayer graphene (tBLG) is two graphene layers placed on top of each other with a twist angle, making it has tunable thermal properties. In this paper, we report an analysis of thermal conductivity ($κ$), phonon density of states, and specific heat capacity of tBLG with various twist angles over a range of temperatures using equilibrium molecular dynamics simulations based on the Green-Kubo method. Simulation shows that stacking and twisting graphene layers lead to a decrease in the thermal conductivity, with the highest $κ$ at around room temperature owned by the tBLG with a twist angle of 3.89$^{\circ}$ followed by 16.43$^{\circ}$ and 4.41$^{\circ}$. We also perform quantum correction to the simulation results to show the process of increasing thermal conductivity at low temperatures.

cond-mat.mes-hall↗

arXiv2021

Quantitative analysis of iron sand mineral content from the south coast of Cidaun, West Java using rietveld refinement method

Iron sand is one of the abundant natural resources in Indonesia, especially on the south coast of Cidaun; West Java which is the basic material for building and metal industry. Iron mineral content is generally metal oxide such as magnetite, hematite and silica/quartz. Sand with iron content used in this study is derived from beach sand Desa Kertajadi, Kecamatan Cidaun, Kabupaten Cianjur, Jawa Barat. Then mass of 2 kg sand was separated using a magnetic separator in order to obtain magnetic and nonmagnetic mineral content. After nine rounds of separation takes two different types of samples that are no separation sand (TS) sample and concentrate in the third separation (S3) sample. The sample is then examined by X-Ray Diffraction (XRD) measurement and analyzed quantitatively using MAUD software to determine the content of Fe3O4 (magnetite) by using the Rietveld refinement method from XRD data. As the analysis result, the magnetite content contained in iron sand is counted quantitatively for each different sample. For iron sand samples (TS) yielding a 24.27 percent of magnetite and a third concentrate separation sample (S3) yields 61.98 percent.

physics.geo-ph↗

arXiv2021

Visualization the electrostatic potential energy map of graphene quantum dots

Graphene quantum dots (GQDs) represent single layers up to dozens of graphene layers smaller than 30 nm. GQDs are newish molecules that have aroused great interest in research because of their exceptional and manageable optical, electrical, chemical, and structural properties. In this work, we report electrostatic potential energy maps, or molecular electrostatic potential surfaces, illustrate the charge distributions of GQDs three-dimensionally. Knowledge of the charge distributions can be used to determine how GQDs interact with one another. To analyze the distribution of molecular charges accurately, a large number of electrostatic potential energy values must be calculated. The best way to transmit these data is to visualize them as in the electrostatic potential map. A ZINDO semi-empirical quantum chemistry method then imposes the calculated data onto an electron density model of the GQDs derived from the Schrödinger equation. To make the electrostatic potential energy data of GQDs easy to interpret, a color spectrum, with red as the lowest electrostatic potential energy value and blue as the highest, is employed to convey the varying intensities of the electrostatic potential energy values. The results of the four GQD models suggest that the energy of the ionization potential lies in a range of -7.20 eV to -5.31 eV and the electron affinity is -2.65 to -0.24 eV.

cond-mat.mtrl-sci↗