Investigation of features for prediction modeling of nano-scale conduction with time-dependent calculation of electron wave packet

The model to predict the electron transmission probability from the random impurity distribution in a two-dimensional nanowire system by combining the time evolution of the electron wave function and machine learning is proposed. We have shown that the intermediate state of the time evolution calculation is a great advantage for efficient modeling by machine learning. The features for machine learning are extracted by analyzing the time variation of the electron density distribution using time evolution calculations. Consequently, the prediction error of the model is improved by performing machine learning based on the features. The proposed method provides a useful perspective for analyzing the motion of electrons in nanoscale semiconductors.

Chemically-induced controlled growth of CsPbBr3 perovskite nanocrystals

Trihalide perovskite nanocrystals have recently emerged as a new class of superior nanoscale semiconductors due to their outstanding optoelectronic properties. A family of all-inorganic CsPbX3 (X=Cl, Br, and I) perovskite nanocrystals is of a particular interest, due to its higher resistance to moisture, heat, and continuous irradiation. In this thesis work a novel chemical route was designed and studied for inducing the growth of CsPbBr3 perovskite nanocrystals at room temperature by intentional depletion of stabilizing ligands, leading to the nanocrystals' fusion. The growth of nanocrystals was achieved from 8 nm to 35 nm in average lateral dimensions, while preserving their optical and colloidal integrity. The thickness was found to be approx. 14 nm. Both UV-visible absorption and photoluminescence emission spectra indicated a red shift in the grown nanocrystals, compared to that of as-synthesized 8 nm nanocrystals. It was determined that the growth of NCs happened in all three dimensions, supporting the theory of induced fusion. The discovered chemical route for triggering post-synthetic growth of as-synthesized perovskite nanocrystals offered a new perception on understanding the role of stabilizing surfactants on the surface of perovskite nanocrystals. It was shown experimentally that the ligands not only participated in colloidal stabilization and photoluminescence enhancement, but also could be efficiently employed for post-synthetic manipulation of nanocrystals' size, band gap and shape.

Self-assembling peptide semiconductors

Semiconductors are central to the modern electronics and optics industries. Conventional semiconductive materials bear inherent limitations, especially in emerging fields such as interfacing with biological systems and bottom-up fabrication. A promising candidate for bioinspired and durable nanoscale semiconductors is the family of self-assembled nanostructures comprising short peptides. The highly ordered and directional intermolecular π-π interactions and hydrogen-bonding network allow the formation of quantum confined structures within the peptide self-assemblies, thus decreasing the band gaps of the superstructures into semiconductor regions. As a result of the diverse architectures and ease of modification of peptide self-assemblies, their semiconductivity can be readily tuned, doped, and functionalized. Therefore, this family of electroactive supramolecular materials may bridge the gap between the inorganic semiconductor world and biological systems.