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P. Dimitrakis

Publications and source records attributed to P. Dimitrakis.

6 recordsLinked to original sources
arXiv2025

SiNx RRAMs performance with different stoichiometries

The microstructure of SiNx is strongly affected by its stoichiometry, x. The stoichiometry of SiNx thin films can be modified by adjusting the gas flow rates during LPCVD deposition. The deficiency or excess of Si atoms enhance the formation of defects such as nitrogen vacancies, silicon dangling bonds etc., and thus can enable performance tuning of the resulting MIS RRAM devices. DC electrical characterization, impedance spectroscopy and constant voltage stress measurements were carried out to investigate the properties of non-stoichiometric silicon nitride films as resistive switching material. The average SET time for each device was measured by applying voltage ramps. Improvement in the SET/RESET voltages and SET time is observed. Finally, the stoichiometric film exhibits the lowest breakdown acceleration factor, while the Si-rich film the highest.

cond-mat.mtrl-sci↗
arXiv2025

Resistance Switching Properties of Stoichiometric and Nitrogen Implanted Silicon Nitride Nanolayers on N and P-Type Si Substrates

This paper examines the resistive switching characteristics of LPCVD SiNx MNOS ReRAM cells on both heavily doped n- and p-type silicon substrates, focusing on the effects of nitrogen doping. Detailed comparisons of electrical properties through nitrogen implantation reveal variations in trap density and SET-RESET voltages between n and p conductivity Si substrates. Impedance spectroscopy further elucidates the conductive path formation and its resistance.

cond-mat.mtrl-sci↗
arXiv2025

Effect of Al2O3 on the operation of SiNX-based MIS RRAMs

The role of a 3 nm Al2O3 layer on top of stoichiometric LPCVD SiNx MIS RRAM cells is investigated by using various electrical characterization techniques. The conductive filament formation is explained, and a compact model is used to fit the current voltage curves and find its evolution during each operation cycle. The conduction in SiNx is also studied.

physics.app-ph↗
arXiv2023

Quantum gate algorithm for reference-guided DNA sequence alignment

Reference-guided DNA sequencing and alignment is an important process in computational molecular biology. The amount of DNA data grows very fast, and many new genomes are waiting to be sequenced while millions of private genomes need to be re-sequenced. Each human genome has 3.2 B base pairs, and each one could be stored with 2 bits of information, so one human genome would take 6.4 B bits or about 760 MB of storage (National Institute of General Medical Sciences). Today most powerful tensor processing units cannot handle the volume of DNA data necessitating a major leap in computing power. It is, therefore, important to investigate the usefulness of quantum computers in genomic data analysis, especially in DNA sequence alignment. Quantum computers are expected to be involved in DNA sequencing, initially as parts of classical systems, acting as quantum accelerators. The number of available qubits is increasing annually, and future quantum computers could conduct DNA sequencing, taking the place of classical computing systems. We present a novel quantum algorithm for reference-guided DNA sequence alignment modeled with gate-based quantum computing. The algorithm is scalable, can be integrated into existing classical DNA sequencing systems and is intentionally structured to limit computational errors. The quantum algorithm has been tested using the quantum processing units and simulators provided by IBM Quantum, and its correctness has been confirmed.

q-bio.BM↗
arXiv2023

Quantum algorithm for de novo DNA sequence assembly based on quantum walks on graphs

De novo DNA sequence assembly is based on finding paths in overlap graphs, which is a NP-hard problem. We developed a quantum algorithm for de novo assembly based on quantum walks in graphs. The overlap graph is partitioned repeatedly to smaller graphs that form a hierarchical structure. We use quantum walks to find paths in low rank graphs and a quantum algorithm that finds Hamiltonian paths in high hierarchical rank. We tested the partitioning quantum algorithm, as well as the quantum algorithm that finds Hamiltonian paths in high hierarchical rank and confirmed its correct operation using Qiskit. We developed a custom simulation for quantum walks to search for paths in low rank graphs. The approach described in this paper may serve as a basis for the development of efficient quantum algorithms that solve the de novo DNA assembly problem.

q-bio.BM↗