arXiv subjects

Aferdita Xhameni

Publications and source records attributed to Aferdita Xhameni.

5 recordsLinked to original sources

arXiv2025

Impact of irradiation conditions on the magnetic field sensitivity of spin defects in hBN nano flakes

We study $V_{\mathrm{B}}^-$ centres generated by helium focused ion beam (FIB) irradiation in thin ($\sim$70 nm) hBN nanoflakes, in order to investigate the effect of implantation conditions on the key parameters that influence the magnetic field sensitivity of $V_{\mathrm{B}}^-$ quantum sensors. Using a combination of photoluminescence, optically detected magnetic resonance, and Raman spectroscopy, we examine the competing factors of maximising signal intensity through larger $V_{\mathrm{B}}^-$ concentration against the degradation in spin coherence and lattice quality observed at high ion fluences. Our results indicate that both the $V_{\mathrm{B}}^-$ spin properties and hBN lattice parameters are largely preserved up to an ion fluence of $10^{14}$ ions/cm$^2$, and beyond this significant degradation occurs in both. At the optimal implantation dose, an AC magnetic sensitivity of $\sim 1\,\mu\mathrm{T}/\sqrt{\mathrm{Hz}}$ is achieved. Using the patterned implantation enabled by the FIB, we find that $V_{\mathrm{B}}^-$ centres and the associated lattice damage are well localised to the implanted regions. This work demonstrates how careful selection of fabrication parameters can be used to optimise the properties of $V_{\mathrm{B}}^-$ centres in hBN, supporting their application as quantum sensors based on 2D materials.

physics.app-ph↗

arXiv2025

High-accuracy inference using HfO$_x$S$_y$/HfS$_2$ Memristors

We demonstrate high accuracy classification for handwritten digits from the MNIST dataset ($\sim$98.00$\%$) and RGB images from the CIFAR-10 dataset ($\sim$86.80$\%$) by using resistive memories based on a 2D van-der-Waals semiconductor: hafnium disulfide (HfS$_2$). These memories are fabricated via dry thermal oxidation, forming vertical crossbar HfO$_x$S$_y$/HfS$_2$ devices with a highly-ordered oxide-semiconductor structure. Our devices operate without electroforming or current compliance and exhibit multi-state, non-volatile resistive switching, allowing resistance to be tuned using voltage pulse trains. Using low-energy potentiation and depression pulses (0.7V-0.995V, 160ns-350ns), we achieve 31 ($\sim$5 bits) stable conductance states with high linearity, symmetry, and low variation over 100 cycles. Key performance metrics-such as weight update, quantisation, and retention-are extracted from these experimental devices. These characteristics are used to simulate neural networks with our resistive memories as weights. Neural networks are trained on state-of-the-art (SOTA) digital hardware (CUDA cores) and a baseline inference accuracy is extracted. IBM's Analog Hardware Acceleration Kit (AIHWKIT) is used to modify and remap digital weights in the pretrained network, based on the characteristics of our devices. Simulations account for factors like conductance linearity, device variation, and converter resolution. In both image recognition tasks, we demonstrate excellent performance, similar to SOTA, with only $<$0.07$\%$ and $<$1.00$\%$ difference in inference accuracy for the MNIST and CIFAR-10 datasets respectively. The forming-free, compliance-free operation, fast switching, low energy consumption, and high accuracy classification demonstrate the potential of HfO$_x$S$_y$/HfS$_2$-based resistive memories for energy-efficient neural network acceleration and neuromorphic computing.

physics.app-ph↗

arXiv2024

Forming and Compliance-free Operation of Low-energy, Fast-switching HfO$_x$S$_y$/HfS$_2$ Memristors

We demonstrate low energy, forming and compliance-free operation of a resistive memory obtained by the partial oxidation of a two-dimensional layered van-der-Waals semiconductor: hafnium disulfide (HfS$_2$). Semiconductor - oxide heterostructures are achieved by low temperature ($<300^{o}$C) thermal oxidation of HfS$_2$ in dry conditions, carefully controlling process parameters. The resulting HfO$_x$S$_y$/HfS$_2$ heterostructures are integrated between metal contacts, forming vertical crossbar devices. Forming-free, compliance-free resistive switching between non-volatile states is demonstrated by applying voltage pulses and measuring the current response in time. We show non-volatile memory operation with an R$_{ON}$/ R$_{OFF}$ of 102, programmable by 80ns WRITE and ERASE operations. Multiple stable resistance states are achieved by modulating pulse width and amplitude, down to 60ns, $<$ 20pJ operation. This demonstrates the capability of these devices for low - energy, fast-switching and multi-state programming. Resistance states were retained without fail at 150$^o$C over 10$^4$s, showcasing the potential of these devices for long retention times and resilience to ageing. Low-energy resistive switching measurements were repeated in vacuum (8.6 mbar) showing unchanged characteristics and no dependence of the device on surrounding oxygen or water vapour. Using a technology computer-aided design (TCAD) tool, we explore the role of the semiconductor layer in tuning the device conductance and driving gradual resistive switching in 2D HfO$_x$ - based devices.

physics.app-ph↗

arXiv2024

Controlled Fabrication of Native Ultra-Thin Amorphous Gallium Oxide from 2D Gallium Sulfide for Emerging Electronic Applications

Oxidation of two-dimensional (2D) layered materials has proven advantageous in creating oxide/2D material heterostructures, opening the door for a new paradigm of low-power electronic devices. Gallium (II) sulfide ($\beta$-GaS), a hexagonal phase group III monochalcogenide, is a wide bandgap semiconductor with a bandgap exceeding 3 eV in single and few layer form. Its oxide, gallium oxide (Ga$_2$O$_3$), combines large bandgap (4.4-5.3 eV) with high dielectric constant (~10). Despite the technological potential of both materials, controlled oxidation of atomically-thin $\beta$-GaS remains under-explored. This study focuses into the controlled oxidation of $\beta$-GaS using oxygen plasma treatment, achieving ultrathin native oxide (GaS$_x$O$_y$, ~4 nm) and GaS$_x$O$_y$/GaS heterostructures where the GaS layer beneath remains intact. By integrating such structures between metal electrodes and applying electric stresses as voltage ramps or pulses, we investigate their use for resistive random-access memory (ReRAM). The ultrathin nature of the produced oxide enables low operation power with energy use as low as 0.22 nJ per operation while maintaining endurance and retention of 350 cycles and 10$^4$ s, respectively. These results show the significant potential of the oxidation-based GaS$_x$O$_y$/GaS heterostructure for electronic applications and, in particular, low-power memory devices.

physics.app-ph↗

arXiv2022

A precision method for integrating shock sensors in the lining of sports helmets by additive manufacturing

An additive manufacturing method is presented for embedding optical fibre-based pressure sensors into the lining of sports helmets to monitor head impact in contact sports. Proof-of-concept thermoplastic polyurethane (TPU) helmet padding segments with embedded sensors are demonstrated for their sensitive shock-monitoring capabilities. The system offers a cost-effective solution for manufacturing consumer products at scale, is unobtrusive, and can be powered by medical-grade cell batteries requiring low maintenance.

physics.ins-det↗