Hi, I'm Stefan Jordi Giurgiu

1. Introduction

This work explores the field of topological quantum materials, covering quantum insulators through the study of diverse quantized Hall Effects, both theoretically and practically via computer-based condensed matter simulation.

2. Theoretical Framework

Topological Insulators & Hall Effect

The study delves into the Integer Quantum Hall Effect (IQHE) where Hall conductance is quantized. We analyzed the role of the Berry Phase and the Chern Number as topological invariants (integers) that characterize the quantized Hall conductivity.

BHZ Model

We focused on the Bernevig-Hughes-Zhang (BHZ) model for HgTe/CdTe quantum wells. In the topological regime (thickness > 6.3 nm), the band structure inverts, creating conducting edge states protected by Time Reversal Symmetry (TRS).

3. Computational Simulation

Using Python and the kwant library, we implemented the effective BHZ Hamiltonian to simulate a nanoribbon of HgTe.

• Bulk Bands: Observed the energy gap opening in the bulk material.
• Surface Bands: Verified the existence of "X"-shaped crossing lines within the forbidden gap (Dirac cones), indicating massless edge states.
• Probability Density: The simulation confirmed that for states within the gap, the probability density is localized at the edges, decaying exponentially towards the center.

4. Topological Qubits

The project also reviewed the theoretical basis of Majorana Fermions and the Kitaev Chain model. Majorana Zero Modes (MZMs) in topological superconductors offer potential for robust topological quantum computing, where qubits are protected from local decoherence.

1. Introduction

Polyoxometalates (POMs) are complex molecular nanoclusters. This project applied the POMSimulator software to model the speciation of uranyl in carbonate media, treating the uranyl-carbonate system as a heteropolyoxometalate. The goal was to reproduce and validate speciation results under varying conditions.

2. Methodology

• Preparation: Identification of chemical species and modelling using Amsterdam Density Functional (ADF) to obtain initial geometries.
• Simulation: Used POMsimulator to calculate formation constants.
• Scaling: Constants were scaled using Python scripts. The "Best_rmse" method (individual adjustment) proved most accurate compared to universal scaling.

3. Results & Discussion

We successfully generated speciation diagrams (distribution of species vs pH). A critical finding was the instability of the model when the carbonate-to-uranium ratio approached 10:1.

Progressive ratio testing (1:0.9 to 1:0.3) showed that valid models decreased drastically as carbonate concentration increased. However, for lower ratios, the clustered species diagrams matched experimental literature well.

4. Conclusions

The workflow confirmed that POMSimulator is a powerful tool for complex inorganic systems. The best_rmse scaling strategy is essential for accuracy. Future work involves resolving the high-ratio instability to extend the analysis to different temperatures.

1. Introduction and Context

Air pollution and acid rain pose significant risks to local agriculture. This work investigates whether acid rain is a real risk factor for wheat plantations in the Alcover area through a rigorous experimental approach.

2. Experimental Methodology

Three complementary experiments were designed to evaluate the impact:

• Experiment 1 (Monitoring): Tracking pH values and conductivity of real rainwater in Alcover, detecting the presence of sulfates and nitrates.
• Experiment 2 (Artificial Atmosphere): Creating a controlled atmosphere to replicate and observe the water acidification process by gaseous pollutants.
• Experiment 3 (Germination): Studying the effect of different acid concentrations on the germination rate of wheat seeds.

3. Results and Conclusions

The study provided quantitative data on wheat resistance to acidic conditions. A direct correlation was observed between increased acidity and a decreased germination rate, establishing risk thresholds for local crops.

This work stands out for the application of the scientific method to solve a local environmental issue, using analytical chemistry tools (pH testers, test strips) and statistical analysis of biological data.